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To keep up with the big data challenges in modern review, adopting a technology-enabled approach is critical. Modern technology like AI can help case teams defensibly cull datasets and gain unprecedented early insight into their data. But if downstream document review teams are unable to optimize technology within their workflows and review tasks, many of the early benefits gained by technology can quickly be lost.In a recent episode of Law & Candor, I was happy to discuss the ongoing evolution of document review—including the challenges of incorporating available technologies. We explored some of the most pressing eDiscovery challenges, including today’s data complexity, and how to break through the barriers that keep document review stuck in the manual, linear review model. We also discussed the value of expertise and where it may be applied to optimize review in various phases of a project. Here are my key takeaways from our conversation.Increasing data complexity challenges and entrenched manual review paradigms Today’s digital data—a wellspring of languages, emojis, videos, memes, and unique abbreviations—looks nothing like the early days of electronic information, and it is certainly a universe away from the paper world where legal teams had to plow through documents with paper cuts, redaction tape, and all. Yet, that “paper process” thinking—the manual, linear review model—still has a firm hold in the legal community and presents an unfortunate barrier to optimizing review. The evolution is telling. As digital data began to take over, the early AI adopters and the “humans need to look at everything” review camps staked their ground. Although the two are moving closer together as time goes on, the use of technology is not as highly leveraged as it could be, leaving clients to pay the high costs of siloed review when technology-enabled processes could enhance accuracy and reduce costs. There are a variety of factors that can contribute to this resistance, but it may also be simply a matter of comfort; it’s always easier to do what you already know in the face of changes that may seem too difficult or complex to contemplate. For the best result, know when and where to leverage available technologies in the review process Human beings are certainly a core component of the document review process, and they always will be, but thinking about the entire review lifecycle strategically, from collection through trial preparation, is critical when it comes to understanding where you can gain value from technology. Technology should be considered a supplement to—not a substitute for—human assessment and knowing where to use it effectively is important. When considering the overall document review process, two key questions are: Where can you get more value by using technology? And where are the potential areas of either nuanced or high-risk communications that may require a more individualized assessment? The goal, after all, isn’t to replace humans with technology, but rather to replace outmoded contract review factories with smarter alternatives that leverage the strengths of both technology and human expertise. A smaller review team, coupled with experts who can effectively apply machine learning and linguistic modeling techniques in the right place, is a much more efficient and cost-effective approach than simply using a stable of reviewers. Technology buyers need to understand what a given tech does, how it differs from other products, and what expertise should be deployed to optimize its use Ironically, the profusion of viable tech options that can applied to expedite document review may be off-putting, but this is a “many shades of gray” situation. Many products do similar things and it is important to understand what the differences are—they may be significant. Today’s tools are quite powerful and layering them alongside the TAR tools that document review teams have become more familiar with is what allows for the true optimization of the review process. These tools are not plug-and-play, however. You need to know what you’re doing. It takes specific expertise to be able to assess the needs of the matter, the nature of the data, the efficacy of the appropriate tools, and whether they’re providing the expected result. Collaboration is still the critical core component of document reviewAnd let’s not forget that document review is a collaborative process between client counsel, project managers, and the review team. Within this crucial collaboration, specific expertise at various points in the process ensures the best result, including: • Expertise in review consulting to assess the right options for both the data that’s been collected and the project goals.• Individualized experts in both the out-of-the-box TAR technology as well as any proprietary technology being used so that the tech can be fine-tuned to optimize the benefits.• A core team of expert human reviewers with the appropriate skills.Experimentation with technology can help bridge the divideWith so many products available to enhance the document review workflow, it makes sense to test potential options. Running a parallel process for a particular aspect of the review to get comfortable with a new product can be very helpful. For example, privilege review, which is an expensive part of the review process, could be a good place to test an alternate workflow. An integrated approach works bestThe bottom line is that an integrated approach, advanced technology, and human expertise, is the best solution. The technology to increase the efficiency and effectiveness of document review is out there and most of it has been shown to be low risk and high value. The cost-effectiveness of an integrated approach has been shown over and over again: In using the appropriate technology, budgets can be reduced, and savings reinvested in new matters. It is up to the client and their legal and technology teams to work together in deciding what combination of tools makes the most sense for their organization and matter types. Just make sure to call upon those with the appropriate expertise to provide guidance. For more examples of how AI and human expertise are optimizing review, check out our review solutions page. ai-and-analytics; ediscovery-reviewai-big-data, blog, managed-review, ai-and-analytics, ediscovery-reviewai-big-data; blog; managed-reviewmary newman

A time-saving tool that consolidates different names for the same entity can make all the difference. One of the many challenges of electronic information and messaging rests in ascertaining the actual identity of the message creator or recipient. Even when only one name is associated with a specific document or communication, the identity journey may have only just begun.The many forms our monikers take as they weave in and out of the digital realm may hold no import for most exchanges, but they can be critical when it comes to eDiscovery and privilege review, where accurate identification of individuals and/or organizations is key.It’s difficult enough when common names are shared among many individuals (hello, John Smith?), but the compilation of our own singular name variations and aliases as they live in the realm of digital text and metadata make life no less complicated. In addition, the electronic format of names and email addresses as they appear in headers or other communications can also make a difference. Attempts to consolidate these variations when undertaking document review is painstaking and error-prone.Not metadata — people. Enter “name normalization.” Automated name normalization tools come to the rescue by isolating and consolidating information found in the top-level and sub-level email headers. Automated name normalization is designed to scan, identify, and associate the full set of name variants, aliases, and email addresses for any individual referenced in the data set, making it easier to review documents related to a particular individual during a responsive review.The mindset shift from email sender and recipient information as simply metadata to profiles of individuals is a subtle but compelling one, encouraging case teams and reviewers to consider people-centric ways to engage with data. This is especially helpful when it comes to identifying what may be—and just as importantly what is not—a potentially privileged communication.Early normalization of names can optimize the privilege workflow.When and how name normalization is done can make a big difference, especially when it comes to accelerating privilege review. Name normalization has historically been a process executed at the end of a review for the purpose of populating information into a privilege log or a names key. However, performing this analysis early in the workflow can be hugely beneficial.Normalizing names at the outset of review or during the pre-review stage as data is being processed enables a team to gain crucial intelligence about their data by identifying exactly who is included in the correspondence and what organizations they may be affiliated with. With a set of easy-to-decipher names to work with instead of a mix of full names, nicknames, initials without context, and other random information that may be even more confusing, reviewers don’t have to rely on guesswork to identify people of interest or those whose legally-affiliated or adversarial status may trigger (or break) a privilege call.Name normalization tools vary, and so do their benefits. Not all name normalization tools are created equal, so it is important to understand the features and benefits of the one being used. Ideally, the algorithm in use maximizes the display name and email address associations as well as the quality and legibility of normalized name values, with as little cleanup required as possible. Granular fielded output options, including top level and sub-header participants is also helpful, as are simple tools for categorizing normalized name entities based on their function, such as privilege actors (e.g., in-house counsel, outside counsel, legal agent) and privilege-breaking third parties (e.g., opposing counsel, government agencies). The ability to automatically identify and classify organizations as well as people (e.g., government agencies, educational institutions, etc.) is also a timesaver.Identification of privilege-breaking third parties is important: although some third parties are acting as agents of either the corporation or the law firms in ways that would not break privilege, others likely would. Knowing the difference can allow a team to triage their privilege review by either eliminating documents that include the privilege breakers from the review entirely, significantly reducing the potential privilege pile, or organizing the review with this likelihood in mind, helping to prevent any embarrassing privilege claims that could be rejected by the courts.Products with such features can provide better privilege identification than is currently the norm, resulting in less volume to manage for privilege log review work later on and curtailing the re-reviews that sometimes occur when new privilege actors or breakers come to light later in the workflow. This information enables a better understanding of any outside firms and attorneys that may not have been included in a list of initial privilege terms and assists in prioritizing the review of documents that include explicit or implied interaction with in-house or outside counsel.Other privilege review and logging optimizers. Other analytics features that can accelerate the privilege review process are coming on the scene as AI tools become more accepted for document review. Privilege Analytics from within Lighthouse Matter Analytics can help review teams with this challenging workflow, streamlining and prioritizing second pass review with pre-built classifiers to automate identification of law firms and legal concepts, tag and tier potentially privileged documents, detect privilege waivers, create privilege reasons, and much more.Interested in how Name Normalization works in Privilege Analytics? Let us show you!ediscovery-review; ai-and-analyticsblog, name-normalization, privilege-review, ediscovery-review, ai-and-analyticsblog; name-normalization; privilege-reviewlighthouse

Have you ever had this scenario – multiple team members from different groups come to you frustrated because the working relationship between their groups is “broken?” Legal is saying they aren’t getting what they need, IT says they are providing what’s asked, and finance doesn’t understand why we are paying our outside vendor for something that the internal IT and legal teams are “supposed to do.” You are responsible for process improvement among these groups so the questions and frustration lands on your desk! This is a common issue. So common, in fact, that this was a big part of a recent Legal Operators webinar I attended. The good news is that the solution may be simple.Often times, the issue revolves around language and how different departments are using the words differently. Let’s explore the above scenario a bit further. The legal team member says they asked IT to gather all data from a certain “custodian.” The IT team took that to mean all “user-created data” on the network from one certain employee, so that is what they provided. They didn’t, however, gather the items on the person’s desktop nor did they gather records that the person created in third-party systems such as the HR and sales systems that the company uses. The legal team, therefore, asked the outside vendor to collect the “missing” data and that vendor sent a bill for their services. Finance is now wondering why we are paying for collecting data when we have an IT team that does that. The issue is that different teams have slightly different interpretations of the request. Although this scenario is eDiscovery specific, this can happen in any interaction between departments. As legal operations is often responsible for process improvement as well as the way legal functions with other departments, the professionals in that group find themselves trying to navigate the terminology. To prevent such misunderstandings in the future, you can proactively solve this problem through a dictionary.Creating a dictionary can be really simple. It is something I have seen one person start on their own just by jotting down words they hear from different groups. From there, you can share that document and ask people to add to it. If you already have a dictionary of your company acronyms, you can either add to it or you can create a specific “data dictionary” for the purposes of legal and IT working together. Another option is to create a simple word document for a single use at the outset of a project. Which solution you select will vary based on the need you are trying to solve. Here are some considerations when you are building out your dictionary.What is the goal of the data dictionary? Most commonly I have seen the goal to be to improve the working relationship of specific teams long term. However, you may have a specific project (e.g., creation of a data map or implementation of Microsoft 365) that would benefit from a project-specific dictionary.Where should it live? This will depend on the goal, but make sure you choose a system that is easy to access for everyone and that doesn’t have a high administrative burden. Choosing a system that the teams are using for other purposes in their daily work will increase the chances of people leveraging this dictionary.Who will keep it updated? This is ideally a group effort with one accountable person who will make any final decisions on the definitions and own updating in the future. There will be an initial effort to populate many terms and you may want a committee of 2 or 3 people to edit definitions. After this initial effort, you can allow access to everyone to edit the document or you can have representatives from each team. The former allows the document to be a living, breathing document and encourages updating, however, may require more frequent oversight by the master administrator. The latter allows each group to have its own oversight but increases the burden of updating. Whichever method you choose, the ultimate owner of the dictionary should review it quarterly to ensure it is staying up to date.Who will have access? I recommend broader access over more limited access, especially for the main groups involved. The more people understand each other’s vocabulary, the easier it is for teams to work together. However, you should consider your company’s access policies when making this decision.What should it include? All department-specific business terms. It is often hard to remember what vernacular in your department is specific to your department as you are so steeped in that language. One easy way to identify these terms is to assign a “listener” from another department in each cross-functional meeting you have for a period. For example, for the next 3 weeks, in each meeting that involves another department, ask one person from that other department to write down any words they hear that are not commonly used in their department. This will give you a good starting point for the dictionary.Note that. although I am talking about a cross-functional effort in the above, this dictionary can also be leveraged within a department. I have found it very effective to create a legal ops dictionary that includes terms from all other departments that you pick up in your work with those other departments. This can still help your goal of resolving confusion and will allow you to get to a common understanding quickly as you are then better equipped with the language that will make your ask clear to the other team.legal-operationsediscovery-process, legal-ops, blog, legal-operations,ediscovery-process; legal-ops; bloglighthouse

Executive SummaryThe GDPR and Data Subject Access Requests (DSARs) are a key reason why companies are starting to focus their attention on information governance strategically, as opposed to simply reacting each time they get a request. With GDPR, companies have seen a significant increase in DSARs and the resulting requirement to look inwardly at their data landscape is timed perfectly with advances in cloud computing.Inconsistent NeedOver the last 20 years, I have assisted clients in responding to triggering events such as litigation and investigations by helping to identify where their data is and how to retrieve, preserve, and filter it for legal review. Rarely have those same clients been interested in proactively implementing information governance frameworks and policies without a consistent need to do so. A General Counsel once told me they face an investigation about as often as every Olympic cycle, so they don’t prioritise resources to prepare for such an infrequent event.The GDPR and associated DSAR obligations have provided exactly this motivation. However, this stick has combined with the carrot of cloud computing to provide the right mix of requirement and capability, not just to make compliance a token project stream within a company, but an enterprise-wide strategic initiative to focus on how data is generated, accessed, managed, and deleted. Common and Civil Law EnvironmentsThroughout my career, I have worked closely with companies in mainland Europe and the Middle East on cross-border litigation and investigations. In my experience, companies operating in civil law jurisdictions are not as familiar with the eDiscovery process as their common law counterparts unless they have faced regulatory scrutiny (such as companies in the financial services or technology industry). This is because they and their counsel do not face the same discovery obligations and thus have not traditionally focused on gathering evidence to produce to a court or third party. The result is inadequate retention procedures and disconnected strategies regarding data management.However, one thing all companies have in common is that using technology to make data management more efficient has become essential as data volumes grow. For example, DSAR responses may not be as ‘normal’ in mainland Europe as they are in the US or UK, but they have universally added motivation to those tasked with managing data within the company.Information Governance Buy-InNow that awareness has increased on the significant consequences of holding certain data longer than you need, senior leadership is prioritising (even at board level) how to effectively manage data within the company. This comes at a time when most companies have moved or are moving to the Cloud. According to Microsoft, “97% of Fortune 500 and 95% of Fortune 1000 companies have Office 365.” Notably, these companies are not moving to the Cloud for compliance or eDiscovery reasons, they are doing so for overall enterprise reasons including streamlining IT operations by moving off premise, giving employees access to modern workplace tools, and for security purposes. But as a bonus, when it comes to comprehensive cloud platforms such as Office 365, information governance, compliance, and eDiscovery tools are already included.Cloud Relevance for Legal TeamsNow that companies are shifting their focus to information governance, what can legal teams do to utilise the investment they’ve made in cloud computing? Since business efficiencies are important but not what legal is primarily concerned about, risk management is the key and to that end, data management is the order of the day. With increased GDPR penalties looming and cloud capabilities at their disposal, lawyers are now turning to the central pillars of information governance – document retention, categorisation, preservation, defensible deletion, identification, collection, and, depending on cloud maturity, data migration.For example, utilising functionality within Office 365, a company has a fighting chance to develop very effective and granular document retention policies that actually work and are dynamic (rather than a dusty document no one ever refers to). Categorising a document (or having it automatically categorised) when it is created, as well as determining, based on its content, when it will be deleted, is a very powerful capability. Setting email and chat message retention based on a defined policy is a significant achievement that goes a long way to limiting what data is kept and for how long.Not Just TechnologyAs GDPR and the Cloud have revolutionised information governance and provided the motivation and capability to address new and existing risks and inefficiencies, for these technology solutions to work in the long term, there needs to be a strong focus on people and processes. Change management has always been the Achilles heel of technology implementation and it is no different for Office 365 when it comes to effective information governance. First and foremost, understanding who in the company has responsibility for various processes needs to be determined. For example, who will respond to a DSAR? Who will create the data searches, preserve the data, and retrieve it for review? When it comes to labelling a document, what is the criteria for determining what qualifies as personal data? How does the technology assist in the decision making? How can a remediation exercise tie into an ongoing retention policy?Overall ComplianceIt is very hard for a multinational company to become 100% GDPR compliant. However, the Cloud offers significant capability for a company to take very reasonable and appropriate measures that go a long way. It’s better to be in the middle of the sheep pack than on the outside when the wolf is close and modern cloud technology allows companies to develop enterprise-wide frameworks to better manage their data. Let the regulators worry about companies with no demonstrable plans, not those who have made comprehensive changes to their data landscape. Even for companies that are not used to the fraught discovery world of US or even UK discovery, information governance has become a key priority due to GDPR and increasingly complex data environments that can now be managed in an effective and coordinated manner.More on this topic can be found in this article, Three Steps to Tackling Data Privacy Compliance Post GDPR. To discuss this article further, please feel free to reach out to me at MBrown@lighthouseglobal.com. data-privacycloud, gdpr, dsars, blog, data-privacy,cloud; gdpr; dsars; blogmichael brown

In a recent post, we discussed that requesting parties often demand more transparency with a Technology Assisted Review (TAR) process than they do with a process involving keyword search and manual review. So, how do you get started using (and understanding) TAR without having to defend it? A fairly simple approach: start with some use cases that don’t require you to defend your use of TAR to outside parties.Getting Comfortable with the TAR WorkflowIt’s difficult to use TAR for the first time in a case for which you have production deadlines and demands from requesting parties. One way to become comfortable with the TAR workflow is to conduct it on a case you’ve already completed, using the same document set with which you worked in that prior case. Doing so can accomplish two goals: You develop a better understanding of how the TAR algorithm learns to identify potentially responsive documents: Based on documents that you classify as responsive (or non-responsive), you will see the algorithm begin to rank other documents in the collection as likely to be responsive as well. Assuming your review team was accurate in classifying responsive documents manually, you will see how those same documents are identified as likely to be responsive by the algorithm, which engenders confidence in the algorithm’s ability to accurately classify documents. You learn how the TAR algorithm may identify potentially responsive documents that were missed by the review team: Human reviewers are only human, and they sometimes misclassify documents. In fact, many studies would say they misclassify them regularly. Assuming that the TAR algorithm is properly trained, it will often more accurately classify documents (that are responsive and non-responsive) than the human reviewers, enabling you to learn how the TAR algorithm can catch mistakes that your human reviewers have made.Other Use Cases for TAREven if you don’t have the time to use TAR on a case you’ve already completed, you can use TAR for other use cases that don’t require a level of transparency with opposing counsel, such as: Internal Investigations: When an internal investigation dictates review of a document set that is conducive to using TAR, this is a terrific opportunity to conduct and refine your TAR process without outside review or transparency requirements to uphold. Review Data Produced to You: Turnabout is fair play, right? There is no reason you can’t use TAR to save costs reviewing the documents produced to you to while determining whether the producing party engaged in a document dump. Prioritizing Your Document Set for Review: Even if you plan to review the entire set of potentially responsive documents, using TAR can help you prioritize the set for review, pushing documents less likely to be responsive to the end of the queue. This can be useful in rolling production scenarios, or if you think that eventual settlement could obviate the need to reduce the entire collection.Combining TAR technology with efficient workflows that maximize the effectiveness of the technology takes time and expertise. Working with experts who understand how to get the most out of the TAR algorithm is important. But it can still be daunting to use TAR for the first time in a case where you must meet a stringent level of defensibility and transparency with opposing counsel. Applying TAR to use cases first where that level of transparency is not required enables your company to get to that efficient and effective workflow—before you have to prove its efficacy to an outside party.ediscovery-review; ai-and-analyticstar-predictive-coding, ediscovery-review, ai-and-analyticstar-predictive-codingmitch montoya

When you’re a kid, you love easy games to learn and play, whether they’re interactive games, board games or card games. One of the first card games many kids learn how to play is “Go Fish.” It’s easy to learn because you simply ask the other player if they have any cards of a certain kind (e.g., “got any Kings?”) – if they do, you collect those cards from them; if they don’t, they say “Go Fish” and you have to draw a card from the deck and your turn ends. Easy, right?Conducting keyword searching without a planned, controlled process that includes testing and verifying the results is somewhat like playing “Go Fish” – you might get lucky and retrieve the documents you need to support your case (without retrieving too many others) and you might not. Yet many lawyers and legal professionals think they “get” keyword searching. Why? Because they learned keyword searching in law school using Westlaw and Lexis? Or they understand how to use “Google” to locate web pages related to their topics? But these examples are designed to identify a single item (or handful of items) related to one topic that you seek.Keyword searching for electronic discovery is about balancing recall and precision to produce a proportional volume of electronically-stored information (ESI) that is responsive to the case, which could be thousands or even millions of responsive documents, depending on the issues of the case.Five Common Keyword Searching MistakesWith that in mind, here are five common mistakes that lawyers and legal professionals make when conducting keyword searches:1. Poor Use of Wildcards: Wildcard characters can be helpful in expanding the scope of the search, but only if you use them well — and understand how they are applied by the search engine you’re using (warning: don’t use Google’s search engine as an exemplar). Poorly placed or ill-advised wildcard character(s) can completely blow up a search. A few years ago, there was a case where one of the goals was to identify documents that related to apps on devices (mobile and PC), so the legal team decided to use a search term “app*” to retrieve words like “app”, “application”, “apps”, etc. Great, right? Not when that same term also retrieves terms like “appear”, “apparent”, “applied”, “appraise”, etc. A better search in this case would have been (app or apps or application*). Make sure to think through word variability and consider word formulations that could be hit by the search. Also consider whether wildcard operators are attached at the appropriate place in the stem of a word so that all of the variants are hit. If not, the search might target too many unrelated words or omit words you want to capture.2. Use of Noise or Stop Words: To keep retrieval responsive even in large databases, most platforms don’t index certain common words that appear regularly (defined as “noise” or “stop” words), yet many legal professionals fail to exclude these noise words in the searches they conduct – yielding unexpected results. Search terms such as “management did” or “counseled out” won’t work if “did” and “out” are noise words that can’t be retrieved. There are typically 100 or more words that are not indexed by a typical platform, so it’s important to understand what they are and plan around them in creating searches that can get you as close as possible to your desired result.3. Starting with Searches That Are Too Broad: Another common mistake is to start with searches that are too broad, assuming that you’ll get a result that will be easy to narrow down through additional search. In fact, you may get a result that makes it nearly impossible to determine what might be causing your search to retrieve unexpected results. Keyword search works best when the hard work has been done up front, either by working with subject matter experts who have provided insight into likely vocabulary used (e.g., shorthand, code words, slang) or via a targeted exploration of the document population. That knowledge, coupled with the effective use of Boolean operators like AND, OR, and NOT, should enable you to craft initial searches that put targeted words in the appropriate context, increasing the likelihood that relevant material will be found at the outset. That result will provide the necessary fodder for developing additional searches that are more precise.4. Failing to Test What’s Retrieved: Many legal professionals create a search, perform that search and then proceed to review without testing the results. Performing a random sample on the results could quickly identify a search that is considerably overbroad and would result in a low prevalence rate of responsive documents, driving up costs for review and production. Testing the result set to ensure the search is properly scoped is well worth the time and effort to take that extra step in terms of potential cost savings. Better to review an extra few hundred documents than an extra hundred thousand documents.5. Failing to Test What’s Not Retrieved: It’s just as important to test the documents that were not retrieved in a search to identify areas that were potentially missed. Not only does a random sample of the “null set” help identify searches that were too narrow in scope, they also are important in addressing defensibility concerns related to your search process if it is challenged by opposing counsel.The ”Go Fish” analogy isn’t an original one – then New York Magistrate Judge Andrew J. Peck used it in his article Search, Forward over nine years ago (October 2011) when he observed that “many counsel still use the “Go Fish” model of keyword search.” If you’re making some of the mistakes listed above, you might be doing so as well. Proper keyword searching is an expert planned and managed process that avoids these mistakes to maximize the proportionality and defensibility of your discovery process. It’s not a kid’s game, so make sure you don’t treat it like one.ediscovery-reviewblog, -keyword-search, ediscovery-review,blog; keyword-searchlighthouse

Investigators experienced in interrogating data know that there may be more to a communication than meets the eye. Whether from intentional or unconscious behavior, clues abound.When key facts are conveyed in nuanced or disguised language, it is important to explore the available collection of documents and communications with a linguistic and forensic sensibility. Although a difficult endeavor, the payoff is high when previously hidden meaning and intent surfaces in your investigation. In the process, individual finds often lead to a larger set of findings providing you a deeper understanding of who exactly knew or did what, and how they felt about it.Follow the ScentUnlike for a typical discovery request, searching for hidden meaning and intent in large data sets requires an ability to pinpoint nuanced — and often indirect — textual cues. This capability is distinct from relevance-based classification techniques such as TAR, which are optimized to ensure consistent coverage for a topic across a large data set. When looking for possible subterfuge or heightened emotion, for example, the task is more akin to incremental detective work than it is batch or prioritized classification. As such, it is useful to frame your efforts within an iterative search workflow that brings you into contact with potentially interesting content and communications, while also allowing you an ability to pivot off your search to explore particular key people, events, and timelines where interesting content appears to be clustered. Make a ListAn important first step in searching for key content you might otherwise be missing is to develop or tailor pre-existing lists of keywords and phrases targeting the types of behaviors and sentiments you are interested in uncovering.For example, if you are investigating possible fraud, you may want to focus part of your search on isolating communications in which there are textual traces suggesting concealment. Some concealment-related phrases to add to a keyword list for a fraud investigation could include “do not share this,” “take off line,” or “delete email,” to name just a few.Additionally, if you are interested in isolating internal chatter conveying strong concern or worry, you could include items like “atrocious,” “huge mistake,” “ill advised,” or “ordeal.” Ziti? Or Fraud?Apart from language expressing worry or concealment, other language worth targeting to get at hidden meaning and intent could include profanity and slang. Also, keep in mind the cultural context in which the communications and documents you are searching through were produced. For example, in a recent bribery and corruption case in NY state involving NY state government officials and private business executives, “ziti” (or “zitti”) was used as a code word to refer to bribes and extortion money. This particular code word in this context was borrowed from the language used by organized crime in New York and surrounding states.Stay on TopicGiven the richness of language and culture, keyword lists targeting hidden figurative meaning can grow to hundreds, even thousands, of words and phrases. To avoid a deluge of hits, it is useful to pair these special keywords with broad issue indicators to make sure you are targeting not only figurative language, but also potentially relevant content. For example, if you are interested in isolating potential fraud around billing practices, one possible tactic would be to leverage proximity search by pairing fraud-related terms like “unusual” with a broad topical keyword term “billing” (e.g., unusual /50 bill[s,ed,ing]). Using this tactic in a systematic way across targeted sentiments and topics will get you a richer result set to focus your in-depth review on.Prepare Ahead of TimeAs with any search effort, setting up your data by threading email conversations and identifying near-duplicate sets of documents are two of the many approaches available to winnow down and prioritize the set of documents you perform targeted searches on. Techniques such as name normalization can also be especially helpful when your aim is to understand who is communicating with whom on a consistent basis.Keep Smiling It is also useful to explore how best to tailor the indexing of your data for searching — for instance, emojis are often used in key relevant conversations, yet they are rarely indexed automatically for search in review platforms. From both a discovery and investigative perspective, this can be a big blind spot. Preliminary research on the topic shows an increase in the number of US cases referring to emoji as evidence increased from 33 in 2017 to 53 in 2018.Searching for key content conveyed through nuanced language is a complex task that is substantively distinct from relevance and topic classification. With the right mindset, workflow, and tools, you will be able to structure and manage this effort in order to isolate key facts otherwise left hidden that are relevant to your case.ai-and-analyticsblog, key-document-identification, fraud-detection, ai-and-analytics,blog; key-document-identification; fraud-detectionlighthouse

Facing a second request can be painful, kind of like searching for a needle in a haystack exacerbated by a strict deadline looming above it all. And, as volumes of data continue to grow and types of data become increasingly complex, these matters are often inefficient and costly, while getting to the key documents (needles) quickly can feel like an insurmountable challenge.In the 2019 Antitrust Leadership Panel, I gathered together a group of top antitrust experts to discuss the grueling challenges, the role of technology and emerging trends, and a few concrete recommendations for progress to make second requests more efficient and less costly. The video series of the panel was very well received and I have since been asked by several viewers, “So, Bill, how do I apply these ideas to my current antitrust practice or process? How do I find the needles in the haystack?”In this blog, I will answer just that and distill the key takeaways from the panel to share with your team so that you can be better equipped to tackle a second request and find the critical needle in that giant, ever-evolving haystack of data.Lesson 1: Technology is a must, but so is trust.Our expert panelists all agreed that although the usage of technology can be challenging to negotiate with the DOJ and the FTC, its application is paramount in getting to key documents quickly. With that in mind, the first phase in preparing for your next second request and conquering the haystack of data is to leverage technology. Here are some simple steps to get you started:It’s critical to understand what technology is out there and what it can do (i.e. AI, predictive coding, email threading, deduplication, etc.). Ensure you and your team stay on top of what each of these tools does and how you can leverage them in second requests. Understanding and educating yourself on all aspects of the technology is key to increasing the government’s trust and acceptance of new tools they may not be familiar with…more on that in the next step.Once you understand what technology options are available and have the best probability for success in your specific case, select the tool or tools that make the most sense for your team and secure them (i.e. by leveraging your vendor’s tools or procuring them in house). Work with your vendor or in-house team to develop sound evidence that will persuade the DOJ and FTC to accept technology so that it can be more broadly used and leveraged within your matters. This will allow you to save significant time and money and, who knows, if we all did it the DOJ and FTC may be more likely to accept itLesson 2: Proportionality can save you time and money, leverage it.The panel also discussed that although the DOJ and FTC sometimes don’t seem to make proportionality a priority in second requests and may intentionally request broader swaths of data to buy more time outside of the strict statutory guidelines, it’s clear that proportionality should be a primary focus for both parties to limit the burdensome amount of data that must be collected and reviewed. Consider this next set of steps as another way to potentially save time and money when trying to dig through the haystack of second request data.When faced with a second request, first discuss amongst your team what arguments for proportionality can be made.Ensure your arguments for proportionality are based on compelling evidence and bring them to the DOJ and FTC at the onset of the second request.If your argument is not accepted on one matter, work with your vendor to focus on building more evidence to get the DOJ and FTC on the side of proportionality in your next matter.Lesson 3: Privilege review tools can be a privilege in the long run.According to the panelists, having better and more user-friendly privilege review tools would result in a significantly improved second request process for everyone involved. So, how do you take concrete action on that? Here are a few additional steps to improve the privilege review process and break down one of the most burdensome parts of tackling the haystack.Reach out to your vendor and ask what tools and solutions they have around privilege review.Test out their privilege tools on your next matter and provide feedback for continuous process improvement.Work with your vendor to develop customized privilege tools using advanced analytics to find privileged documents more quickly and easily.When leveraging privilege tools, be sure to track solid metrics and develop new evidence to showcase to the DOJ and FTC why they can trust the advanced technology.Share these takeaways within your team and apply the steps that make sense for your practice so that the next time you’re faced with a daunting second request and a seemingly insurmountable amount of data, you’ll be well positioned to tackle the challenge and find the right needles in the haystack from the onset.Want to discuss this topic more? Feel free to reach out to me at BMariano@lighthouseglobal.com.To explore related content, click the links below:Antitrust Leadership Panel: Time and CostAntitrust Leadership Panel: The Role of TechnologyAntitrust Leadership Panel: Evolving for the Futureai-and-analytics; antitrustanalytics, hsr-second-requests, blog, ai-and-analytics, antitrustanalytics; hsr-second-requests; blogbill mariano

In honor of International Women’s Day 2019, Lighthouse highlighted a few female thought leaders who are changing the game in the eDiscovery, compliance, and information governance space. Check out our featured ladies below and discover what they are doing to lead change as well as some of their key tips for success: Take a look at our 2020 International Women's Day Campaign!diversity-equity-and-inclusionediscovery-process, blog, diversity-equity-and-inclusion,ediscovery-process; bloglighthouse

Your team is facing a wall of mounting compliance requirements and internal investigations, as well as a few larger litigations you fear you may not be able to handle given internal resource constraints. Each case involves unwieldy amounts of data to wade through, and that data must be collected from constantly-evolving data sources—from iPhones to Microsoft Teams to Skype chats. You’re working with your IT team to ensure your company’s most sensitive data is protected throughout the course of all those matters.All of this considered, your team is faced with vetting eDiscovery vendors to handle the large litigation matters and ensuring those vendors can effectively protect your company’s data. Simultaneously, you are shouldering the burden of hosting a separate eDiscovery platform for internal investigations with a legal budget that is already stretched thin. Does this sound familiar? Welcome to the life of a modern in-house attorney. Now more than ever, in-house counsel need to identify cost-effective ways to improve the effectiveness and efficiency of their eDiscovery matters and investigations with attention to the security of their company’s data. This is where adopting a cloud-based self-service, spectra eDiscovery platform can help. Below, I’ve outlined how moving to this type of model can ease many of the burdens faced by corporate legal departments.1. The Added Benefit of On-Demand Scalability‍A cloud-based, self-service, spectra platform provides your team the ability to quickly transfer case data into a cutting-edge review platform and access it from any web browser. You’re no longer waiting days for a vendor to take on the task with no insight into when the data will be ready. With a self-service, spectra solution, your team holds the reigns and can make strategic decisions based on what works best for your budget and organization. If your team has the bandwidth to handle smaller internal investigations but needs help handling large litigations, a scalable self-service, spectra model can provide that solution. If you want your team to handle all matters, large and small, but you worry about collecting from unique sources like Microsoft Teams or need help defensibly culling a large amount of data in a particular case, a quality self-service, spectra provider can handle those issues and leave the rest to you. In short, a self-service, spectra solution gives you the ability to control your own fate and leverage the eDiscovery tools and expertise you need, when you need them. 2. Access to the Best eDiscovery Tools – Without the Overhead Costs A robust self-service, spectra eDiscovery solution gives your team access to the industry’s best eDiscovery tools, enabling you to achieve the best outcome on every matter for the most efficient cost. Whether you want to analyze your organization’s entire legal portfolio to see where you can improve review efficiency across matters, or you simply want to leverage the best tools from collection to production, the right solution will deliver. And with a self-service, spectra model, your team will have access to these tools without the burden of infrastructure maintenance or software licensing. A quality self-service, spectra provider will shoulder these costs, as well as the load of continuously evaluating and updating technology. Your team is free to do what it is does best: legal work.3. The Peace of Mind of Reliable Data Security In a self-service, spectra eDiscovery model, your service provider shoulders the data security risk with state-of-the-art infrastructure and dedicated IT and security teams capable of remaining attentive to cybersecurity threats and evolving regulatory standards. This not only allows you to lower your own costs and free up valuable internal IT resources, but also provides something even more valuable than cost savings—the peace of mind that comes with knowing your company’s data is being managed and protected by IT experts.4. Flexible, Predictable Pricing and Lower Overall Costsself-service, spectra pricing models can be designed around your team’s expectations for utilization—meaning you can select a pricing structure that fits your organization’s unique needs. From pay-as-you-go models to a subscription-based approach, self-service, spectra pricing often differs from traditional eDiscovery pricing in that it is clear and predictable. This means you won’t be blindsided at the close of the month with hidden charges or unexpected hourly fees from a law firm or vendor. Add this type of transparent pricing to the fact that you will no longer be shouldering technology costs or paying for vendor services you don’t need, and the result is a significantly lower eDiscovery overhead that can fit within any legal budget. These four benefits can help corporations and in-house counsel teams significantly improve eDiscovery efficiency and reduce costs. For more information on how to move your organization to a self-service, spectra eDiscovery model, be sure to check out our other articles related to the self-service, spectra eDiscovery revolution – including tips for overcoming self-service, spectra objections and building a self-service, spectra business case.ediscovery-review; ai-and-analyticsself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; bloglighthouse

In honor of International Women’s Day 2020, Lighthouse is featuring female leaders within the industry who actively choose to challenge stereotypes, fight bias, broaden perceptions, improve situations, and celebrate women's achievements. Below are spotlights on each of our 2020 featured females helping to make a gender equal world. Check them out!1. What does a gender-equal world mean to you? It means a meritocracy where everyone with skill, hard work, and imagination may aspire to, and actually can achieve, the highest level regardless of gender. It means the elimination of explicit and implicit biases that can skew professional relationships and result in disparate opportunities. It means having a voice and a seat at the table earned through performance and not being sidelined because of gender.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I was raised in a counter-stereotypical environment. My mother was the primary breadwinner and a full-time working professional, while my father took on most of the childcare responsibilities after a full work day of physical labor that began at 5 a.m. I grew up playing backyard tackle football with my brother and male family friends in mud, ice, and rain, and they did not go easy on me. I then joined the Marine Corps. Until a few years ago, I never had the perception that there were limits on what I could achieve because I am female.Unfortunately, I am now intimately aware of the ugly reality of gender discrimination. My experiences allow me to better understand the elements that contribute to disparate treatment and what can be done to address them. Raising awareness of these issues in a more vocal way is in the works. I have never been afraid to challenge the status quo (like using predictive coding in 2012) and I will continue to do so to effectuate positive change.When faced with bias in the past, I researched and gathered information regarding best practices to address such issues. I presented recommendations to leadership and organized events to build community and provide training. I continue to provide mentorship and support to other women. And, I challenge stereotypes by persevering as a working mom in big law.3. How do you celebrate other women's achievements? I like to spread awareness of other women’s achievements and provide other women opportunities to shine. I go out of my way to ensure key decision makers know about the accomplishments of other women.4. What recommendations do you have for others looking to ensure a gender equal workplace? For those trying to establish best practices internally, there are a myriad of resources available. For example, the Center for Worklife Law, spearheaded by the Professor Joan Williams, provides an array of practical tools, model policies, training, and best practice guides. Vote with your feet and dollars. If efforts to effectuate change internally fall on deaf ears, go somewhere else where there is a demonstrated commitment to providing a level playing field. Dentons is truly invested in supporting women, as apparent through their review processes, bias training and safeguards, development and authentic leadership diversity. Support vendors and consultants who demonstrate gender equality. Be cognizant of who you work with and keep busy. Build community.1. What does a gender-equal world mean to you? To me a gender-equal world means not having to over analyze each piece of my daily life to assure my value is recognized by all participants. It means not having to change my approach, tone, or demeanor to be heard by my male colleagues. It means I can be ME.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I personally challenge stereotypes at my firm by being a strong leader, volunteering for important projects, speaking up in meetings, offering feedback to my colleagues equally, male and female. Importantly, I recognize my value to the firm. I am BRAVE. I am CONFIDENT.3. How do you celebrate other women's achievements? Through my leadership in the GOIC Lean In Circle and membership in the Diversity and Inclusion Committee at Orrick, I help host events and provide a forum for women’s accomplishments to be recognized. When working with my colleagues and teams I assure that credit earned is given.4. What recommendations do you have for others looking to ensure a gender equal workplace? Be persistent! Be ambitious! Don’t settle. Recognize your value. People live up to expectations. Make your value known, expect credit. If you don’t get it, seek it out. If you don’t expect to get the next big project, you may never get it. Volunteer and make your voice heard.1. What does a gender-equal world mean to you? A human is recognized for "their" personality and knowledge in all capacities. Mental and physical health are supported and provided for without bias. "We" are respected for virtues both positive and negative.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? Initially and always, listening. What's the reason for the bias? Challenging the responses with actions, calmness, and, ultimately, calling out the unbalanced views. Empathy to all is the sincerest way to "fight" and remove bias.3. How do you celebrate other women's achievements? I like to send notes or cards to congratulate as a small but personal article of celebration. Telling women how fantastic the achievements are and discussing them in other communities. Sharing the knowledge equates to opening new conversations or relighting old topics.4. What recommendations do you have for others looking to ensure a gender equal workplace? Develop an altruistic culture focusing on team dynamics, envelop clients into team and workspace initiatives, and, importantly, talk about it! Publicise the how, the who, and the why.1. What does a gender-equal world mean to you? It means fair treatment across the gender identity spectrum. It does not mean we have to look, talk, or act the same. We all bring something unique to the conversation and should be celebrated equally for our contributions. Rights, opportunities, obligations, and pay should not take gender into consideration. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? My workplace makes diversity a priority. That being said bias still exists, often when you least expect it. When you experience bias, gather your thoughts, speak up, and don’t tolerate bad behavior. Set an example by never apologizing for being at the table. Your opinion matters so speak with authority. 3. How do you celebrate other women's achievements? We’re often bad at celebrating our own achievements, making it more important that we celebrate each other. Words of encouragement when things don’t go as expected and notes of recognition when they do. Use your organization's award, bonus, and feedback structure, especially if achievements were missed by the broader group. 4. What recommendations do you have for others looking to ensure a gender equal workplace? Begin with the end in mind. My organization works hard to expand our candidate pool, rethink our interview process so that a diverse panel interviews candidates, and set up mentor and onboarding programs that match diverse candidates. For my team, work life balance, flexibility, and open communication have been key.1. What does a gender-equal world mean to you? I aspire to a world where we equally value the attributes of all genders and celebrate the power of teams of people with different experiences, perspectives, and strengths. It may seem funny, but when traveling for business, I am often struck by the fact that I am the only woman in the hotel restaurant at breakfast. It would be inspiring to see that change. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? My career path and non-partner role defy stereotypes. In my role, I strive to create an environment where it is safe to disagree and challenge the status quo. The success of my team shows that when you refuse to do things as they have always been done by the same people who have always done them, great things can happen. But, most of all, I love what I do contrary to stereotypes!3. How do you celebrate other women's achievements? As a team we foster meaningful relationships and connections among women so that we can lift each other up and challenge one another. We are active in Women in eDiscovery and She Breaks the Law, and recently nominated 16 women to the ABA Women in Tech list. When selecting vendors, technology solutions, and making investments via our legal tech fund, we look at whether the company has women in senior leadership roles. 4. What recommendations do you have for others looking to ensure a gender equal workplace? Re-imagine the skill set and talent profiles for new hires. Women are under-represented in senior leadership positions in the legal and technology industries. To expand your talent pool, look for candidates in other industries and value innate ability over previous titles and years of experience. Give early opportunities and invest in creating the next generation of women leaders. 1. What does a gender-equal world mean to you? At a basic level, gender equality means having gender never enter into the equation. However, for my everyday reality, it means a workplace where being a working mother that values and prioritizes time with her family does not count against me and is actually celebrated. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? As a manager, I promote an environment that has open and honest communication and treats everyone equally. As a mother, I am raising my two young boys to think of women as not just equals, but as powerful forces. 3. How do you celebrate other women's achievements? As the world comes closer to gender equality, it is important that we reward all individuals in a way that does not create a greater divide. At a basic level, this means rewarding people for the quality of work they do and not just the number of hours they put in. 4. What recommendations do you have for others looking to ensure a gender equal workplace? There are a number of actions companies and individuals can take to help ensure gender equality in the workplace. These can be as simple as removing names from resumes to make them gender neutral, create pay bands based on position and not previous salary, and using gender neutral leave policies. 1. What does a gender-equal world mean to you? A world where gender is no longer a barrier to equal opportunity. A world free of the biases and prejudice currently associated with gender, both overtly and unconsciously, where everyone has a chance to develop their potential. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I support diversity in groups and teams, both during the hiring phase and after hiring. When hiring, I work with recruiters to ensure a diverse applicant pool. When managing, I encourage inclusion and collaboration, thereby allowing for a wide range of perspectives and opinions from which everyone will benefit.3. How do you celebrate other women’s achievements? Whenever a female colleague accomplishes something important, I take the time to recognize, support and encourage her. Where possible, I do so in person. In addition, and where necessary, I also use one of the other myriad avenues for such recognition, including email, phone, text, social media, company intranet.4. What recommendations do you have for others looking to ensure a gender equal workplace? Use best efforts to support and encourage diversity, and celebrate important accomplishments. Start during hiring, working with recruiters to ensure it includes both women and men. When managing, encourage inclusion and collaboration, encourage everyone to develop their potential, and take the time to celebrate the successes.1. What does a gender-equal world mean to you? Girls are often encouraged to believe they can do anything they set out to do, as long as they aren’t too loud about it, because, after all, they must behave like proper young ladies. In a gender-equal world, girls should be as brash as they wish and women should tout their accomplishments.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I lead by example, making sure my voice is heard. When I run meetings, I ensure that every participant has the opportunity to contribute if they wish. I acknowledge great ideas put forth by women when their male counterparts try to co-opt them.3. How do you celebrate other women’s achievements? I choose words carefully when describing women’s achievements to ensure they are gender-neutral and give credit that is deserved. I use active voice to indicate a female team member has worked for her accomplishments, rather than phrases that seem to imply she was lucky to have something happen for her.4. What recommendations do you have for others looking to ensure a gender equal workplace? If you feel overlooked in the workplace, develop allies and mentors. Allies are female and male counterparts who will amplify your voice. Mentors can help navigate workplace politics and educate male-dominated leadership on the importance of gender equality.1. What does a gender-equal world mean to you? A gender-equal world is on in which all people, regardless of their sex, have the same opportunities and receive equal compensation.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I definitely lead by example. As a leader in my organization, I also have a responsibility to identify and correct when stereotypes or biases surface. I find one-on-one conversations with a person who has articulated the stereotype or bias is effective. Some people don't even realize that they have biases. It is important to me that I am known for cultivating a fair work environment for everyone.3. How do you celebrate other women’s achievements? Women need more professional mentors. I seek mentors out myself and I have served as a mentor for many other women in my career. I celebrate the achievements of the women I have mentored with a personal note or even a quick text. I have close professional female counterparts at other organizations. We are intentional about staying connected. Congregations with these ladies at industry events often turn into think tanks of sorts and we are always celebrating someone's latest accomplishment. Women have to hold up and support other women.4. What recommendations do you have for others looking to ensure a gender equal workplace? If you are in the job market, look at the leadership of the organization. That will speak volumes about their efforts to ensure a gender equal workplace. Ask about their commitments to gender quality and any corporate programs they have in place to support those efforts. If you are in a company that lacks in this area, take the initiative to raise it and spearhead a proposal to help them elevate their efforts.A big shout out to the women who participated in our International Women's Day Campaign focused on #EachforEqual! Take a look at our 2019 International Women's Day Campaign. diversity-equity-and-inclusionediscovery-process, blog, diversity-equity-and-inclusion,ediscovery-process; bloglighthouse

Planning the best ways to find key documents will pay off in the long run. Getting to the bottom of alleged claims is often a high-stakes race to find critical information amidst an avalanche of data. Regardless of whether you are conducting an internal investigation, early case assessment, or preparing for depositions, there is no time to waste. Although it’s surely tempting to dive right into document reviews to find the key documents that will shed light on the matter at hand, litigators and investigators know that good preparation leads to a better result.Conducting fact-finding in a reactive manner by skipping upfront preparation diminishes the ability to systematically investigate the full set of allegations and compromises the development of a comprehensive factual narrative. Here are a few things to keep in mind as you prepare.Consider the source(s).To conduct efficient fact-finding through key document identification, you need to first take stock of the various sources of data available for review and then map them to the type of evidence they may contain.Is the evidence you are looking for likely to reside in reports, communications, or memos? Are there particular sets of custodial data that are likely more important to understanding the case than others? Are inbound consumer marketing solicitations to employees, or bulk email news alerts likely to contain important information for the case? Taking the time to consider these questions and articulate hypotheses about where important evidence may reside allows you to effectively prioritize which data sets to search through first.What are the targets?In addition to prioritizing the data, it’s critically important to articulate the array of evidence you are looking for based on the set of allegations at issue. Your understanding of the case will certainly evolve as fact-finding progresses, but defining evidentiary targets in advance better enables you to assess later on whether you have diligently investigated all possible angles. Moreover, defining discrete targets for fact-finding allows you to articulate searches at a more granular level. Rather than leveraging one fully encompassing crude keyword search to hunt for key documents, creating a net of many targeted searches will lead to more comprehensive results in a more efficient manner.What tools should you use?Another key to efficient and successful fact-finding is selecting the right data analytics tools that will help reduce the noise and boost the signal. For example, threading email conversations and identifying near-duplicate sets of documents are two of the many approaches available to winnow down and prioritize the set of documents you perform targeted searches on. Techniques such as name normalization can also be especially helpful when your aim is to understand who is communicating with whom about which underlying facts. It might even be worth investigating how to best tailor the way the data is indexed for searching — for instance, emojis are often used in key conversations useful in investigations yet they are rarely indexed for search in review platforms unless you explicitly specify them to be.Understanding the data, articulating an evidentiary approach, and equipping yourself with the right data analytics helps ensure that critical facts do go undiscovered. Although it’s natural to want to get right into the thick of it, skilled counsel know that high-stakes fact-finding is a complex affair requiring forethought and preparation. And once in place, a well-informed search strategy can be quickly executed allowing your team to spend more time understanding the significance of key documents, and less time re-evaluating and tinkering with approaches for finding them.Want to know more? Watch “Winning the Race for the Facts: Case Studies on How to Leverage Technology and Search Expertise for Investigations and Case Preparation,” a joint webinar with H5 and Covington & Burling, for further tips on finding key documents for investigations.ediscovery-reviewblog, -key-document-identification, kdi, ediscovery-review,blog; key-document-identification; kdilighthouse

Ever since ABA Model Rule of Professional Conduct 1.1 [1] was modified in 2012 to include an ethical obligation for attorneys to “keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology [2]” (emphasis added), attorneys in almost every state have had a duty to stay abreast of how technology can both help and harm clients. In other words, most attorneys practicing law in the United States have an ethical obligation to not only understand the risks created by the technology we use in our practice (think data breaches, data security, etc.), but also to keep abreast of technology that may benefit our practice.Nowhere is this obligation more implicated than within the eDiscovery realm. We live in a digital world and our communications and workplaces reflect that. Almost any discovery request today will involve preserving, collecting, reviewing, and producing electronically stored information (ESI) – emails, text messages, video footage, Word documents, Excels, PowerPoints, social media posts, collaboration tool data – the list is endless. To respond to ESI discovery requests, attorneys need to use (or in many cases, hire someone who can use) technology for every step of the eDiscovery process – from preservation to production. Under Model Rule 1.1, that means that we must stay abreast of that technology, as well as any other technology that may be beneficial to completing those tasks more effectively for our clients (whether we are providing legal advice to an organization as in-house counsel or externally through a law firm).In this post, I posit that in the very near future, this ethical obligation should include a duty to understand and evaluate the benefits of leveraging Artificial Intelligence (AI) during almost any eDiscovery matter, for a variety of different use cases.AI in eDiscoveryFirst, let’s level set by defining the type of technology I’m referring to when I use the term “AI,” as well as take a brief look at how AI technology is currently being used within the eDiscovery space. Broadly speaking, AI refers to the capability of a machine to imitate intelligent human behavior. Within eDiscovery, the term is often also used broadly to refer to any technology that can perform document review tasks that would normally require human analysis and/or review.There is a wide range of AI technology that can help perform document review tasks. These include everything from older forms of machine learning technology that can analyze the text of a document and compare it to the decisions made about that document by a human to predict what the human decision would be on other documents to newer generations of analytics technology that can analyze metadata and language used within documents to identify complicated concepts, like the sentiment and tone of the author. This broad spectrum of technology can be incredibly beneficial in a number of important document review use cases – the most common of which I have outlined below: Culling Data - One of the most common use cases for AI technology within eDiscovery is leveraging it to identify documents that are relevant to the discovery request and need to be produced. Or, conversely, identify documents that are irrelevant to the matter at hand and do not need to be produced. AI technology is especially proficient at identifying documents that are highly unlikely to be responsive to the discovery request. In turn, this helps attorneys and legal technologists “cull” datasets, essentially eliminating the need to have a human review every document in the dataset. Newer AI technology is also better at identifying documents that would never be responsive to any document request (i.e., “junk” documents) so that these documents can be quickly removed from the review queue. More advanced AI technology can do this by aggregating previously collected data from within an organization as well as the attorney decisions made about that data, and then use advanced algorithms to analyze the language, text, metadata, and previous attorney decisions to identify objectively non-responsive junk documents that are pulled into discovery request collections time and time again. Prioritizing and Categorizing Data - Apart from culling data, AI can also be used to simply make human review more efficient. Advanced AI technology can be used to identify specific concepts and issues that attorneys are looking for within a dataset and group them to expedite and prioritize attorney review. For example, if a litigation involves an employee accused of stealing company information, advanced AI technology can analyze all the employee’s communications and digital activities and identify any anomalies, such as an activity that occurred during abnormal work hours or communications with other employees with whom they normally would not have reason to interact. The machine can then group those documents so that attorneys can review them first. This identification and prioritization can be critical in evaluating the matter as a whole, as well as helping attorneys make better strategic decisions about the matter. Review prioritization can also simply help meet court-imposed production deadlines on time by enabling human reviewers to focus on data that can go out the door quickly (i.e., documents that the machine identified as highly likely to be responsive but also highly unlikely to involve issues that would require more in-depth human review like privilege, confidentiality, etc.). Identifying Sensitive Information - On the same note, AI technology is now more adept at identifying issues that usually require more in-depth human review. Newer AI technology that uses advanced Natural Language Processing (NLP) and analyzes both the metadata and text of a document is much better at identifying documents that contain sensitive information, like attorney-client privileged communications, company trade secrets, or personally identifiable information (PII). This is because more advanced NLP can take context into account and, therefore, more accurately identify when an internal attorney is chatting with other employees over email about the company fantasy football rankings vs. when they are providing actual legal advice about a work-related matter. It can do this by analyzing not only the language being used within the data, but also how attorneys are using that language and with whom. In turn, this helps attorneys conducting eDiscovery reviews prioritize documents for review, expedite productions, and protect privileged information.Attorneys’ Ethical Obligation to Consider the Benefits of AI in eDiscovery The benefits of AI in eDiscovery should now be clear. It is already infeasible to conduct a solely human linear review of terabytes of data without the help of AI technology to cull and/or prioritize data. A review of that amount of data (performed by humans reviewing one document at a time) can require months and even years, a virtual army of human reviewers (all being paid at an hourly rate), as well as the training, resources, and technology necessary for those reviewers to perform the work proficiently. Because of this, AI technology (via technology assisted review (TAR)) has been widely accepted by courts and used by counsel to cull and prioritize large sets for almost a decade.However, while big datasets involving terabytes of data were once the outliers in the eDiscovery world, they are now quickly becoming the norm for organizations and litigations of all sizes due to exploding data volumes. To put the growing size of organizational data in context, the total volume of data being generated and consumed has increased from 33 zettabytes worldwide in 2018 to a predicted 175 zettabytes in 2025[3]. This means that soon, even the smallest litigation or investigation may involve terabytes of data to review. In turn, that means that AI technology will be critical for almost any litigation involving a discovery component.And that means that we as attorneys will have an ethical duty to keep abreast of AI technology to competently represent our clients in matters involving eDiscovery. As we have seen above, there is just no way to conduct massive document reviews without the help of AI technology. Moreover, the imperative task of protecting sensitive client data like attorney-client privilege, trade secret information, and PII (which all can be hidden and hard to find amongst massive amounts of data) also benefits from leveraging AI technology. If there is technology readily available that can lower attorney costs and client risk, while ensuring a more consistent and accurate work product, we have a duty to our clients to stay aware of that technology and understand how and when to leverage it.But this ethical obligation should not scare us as attorneys and it doesn’t mean that every attorney will need to become a data scientist in order to ethically practice law in the future. Rather, it just means that we, as attorneys, will just need to develop a baseline knowledge of AI technology when conducting eDiscovery so that we can effectively evaluate when and how to leverage it for our clients, as well as when and how to partner with appropriate eDiscovery providers that can provide the requisite training and assist with leveraging the best technology for each eDiscovery task.ConclusionAs attorneys, we have all adapted to new technology as our world and our clients have evolved. In the last decade or so, we have moved from Xerox and fax machines to e-filings and Zoom court hearings. The same ethic that drives us to evolve with our clients and competently represent them to the best of our ability will continue to drive us to stay abreast of the exciting changes happening around AI technology within the eDiscovery space.To discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com.‍[1] “Client-Lawyer Relationship: A lawyer shall provide competent representation to a client. Competent representation requires the legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.” ABA Model Rules of Professional Conduct, Rule 1.1.[2] See Comment 8, Model Rules of Professional Conduct Rule 1.1 (Competence)[3] Reinsel, David; Gantz, John; Rydning, John. “The Digitization of the World From Edge to Core.” November 2018. Retrieved from https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf. An IDC White Paper, Sponsored by SEAGATE.ai-and-analyticsanalytics, ai-big-data, ediscovery-process, red-flag-reporting, departing-onboarding-employee, prism, blog, focus-discovery, ai-and-analytics,analytics; ai-big-data; ediscovery-process; red-flag-reporting; departing-onboarding-employee; prism; blog; focus-discoverysarah moran

Below is a copy of a featured blog written by Debora Motyka Jones for CLOC's Legal Operations Blog.One of the most common complaints I hear from General Counsels and Chief Legal Officers is that they are not able to sit at a table full of their executive peers and provide metrics on how legal is impacting the core business. Sure, they are able to show their own department’s spending, tasks, and resource allocation. But wouldn’t it be nice to tell the business when revenue will hit? Or insights about what organizational behaviors are leading to inefficiency and, if changed, will impact spending. More specifically, as the legal operations team member responsible for metrics, wouldn’t it be great to share these key insights with your GC as well as your finance, sales, IT, and other department counterparts? Good news! Legal has this type of information, it is just a matter of identifying and mining it!Keeping metrics has become table stakes in today’s legal department and it often falls on the shoulders of legal operations to track and share those metrics. In fact, CLOC highlights business intelligence as a core competency for the legal operations function. Identifying metrics, cleansing those metrics, and putting them forth can be quite a lift, but once you have the right metrics in place, you are able to make data-driven decisions about how to staff your team, what external resources you need, and drive efficiencies. If you are still at the early stages of figuring out which metrics you should track for your department, there are many good resources out there including a checklist of potential metrics by Thompson Reuters, and a blog by CLOC on where to start. HBR also conducts a survey so you can see what other departments are seeing – this can be helpful for setting targets and/or seeing how you compare. When you analyze these and other resources, you will notice that many of the metrics are legal department centric. Though they are helpful for the department, they are not very meaningful when they are sitting around the table with executives doing strategic business planning for the business as a whole. So what types of metrics can legal provide in those settings and how do you capture them? There are many ways to go about this, but I have highlighted a few that can provide a robust discussion at the executive table.Leading Indicators of RevenueMost companies are reviewing the top line with some frequency and in many industries it is a challenge to predict the timing of that revenue. Given its position at the end of the sales cycle, in the contracting phase, legal has excellent access to information about revenue and the timing thereof. Here are the most common statistics your legal department can provide in that area:New Customer Acquisition: Number of Customer Contracts Signed this Month – Signing up paying customers is a direct tie to revenue and the legal department holds the keys to one of the last steps pre-revenue: contract signing. By identifying the type of contract that leads to revenue, the legal department is able to share with the business how many new customers are coming online. The metric is typically a raw number and can be compared against the number of contracts in a prior period. If not all customers who sign this contract lead to revenue, you will want to report (or at least know) the ratio of contracts to paying customers in order to give an accurate picture. Once you have been tracking this metric, you may want to take it a step further and identify and contracts that come earlier in the process. For example, in some companies, prospective clients sign NDAs earlier in the sales cycle. By reporting on the number of NDAs signed, you will start to see a ratio of the number of NDA to the number of MSAs and can give even earlier visibility into the customer acquisition pipeline.Expected New Customers: Contracts in Negotiation and Contract Negotiation Length – If your company has negotiated contracts then reporting on the number of contracts in negotiation can also help with revenue planning. Knowing the typical length of that negotiation will give an indication as to the timing of that revenue.Expected Revenue: Timing – The final piece of the revenue puzzle is when the above revenue will hit. You can work with the finance team to get the typical time between contract signing and revenue. This will often vary by contract size so layering in the contract size is helpful. If contract size if not available in the contract itself, that is likely information that sales keep so they can report that metrics if legal cannot.The two departments most interested in all three the above metrics are likely to be sales and finance but depending on the detail reported at the executive level, these may be executive-level metrics. If the above seems like a lot, know that many contract management tools and/or contract artificial intelligence tools can mine your contracts for the above information.Efficiency in Business OperationsLegal operations also has a unique ability to look back and reflect on the efficiency in some areas of business operations. More specifically, in the course of litigation and investigations, cross sections of the business are examined with hindsight and as we all know, hindsight is 20/20. Providing that look back information to the business can help in overall business efficiency. In addition, legal has access to payment clauses, in contracts, that can ensure efficiency in cash management. Here are some helpful statistics your legal department can provide on the state of legal operations.Early Payment Discount Usage: Number of Contracts with Early Payment and Percentage of Early Payment Discounts Used – When signing vendor contracts, there are often provisions allowing for discounts if certain terms – e.g. payment within a short timeframe, are met. Although this may be fresh on everyone’s mind at the time of negotiation, this often gets lost over time. Using current technologies, the legal operations team can identify these contracts and provide the number of contracts in which such provisions exist. You can then work with finance to determine how many of these provisions are being leveraged – e.g. is the business actually paying early and taking the percentage reduction. The savings for the business can be material by just providing visibility into this area.Data Storage: How Much Data to Keep – A common IT pain point is storage management and having to add servers in order to keep up with the business needs. With cloud technologies, IT often knows how much space they have allocated to each user’s mail or individual drives but what is unknown is how much data users are keeping on their machines or in collaborations tools and shared drives. With data collections for litigation or regulatory matters, the legal team has access to this information. This information can help IT understand its storage needs and put in place technologies to minimize storage per person thereby saving on storage costs.Business Intelligence from Active Matters – This one isn’t a specific metric. Instead, this is more focused on the business intelligence that comes out of the legal department’s unique position as a reviewer of sets of documents. In litigation or investigations, the legal department has access to a cross section of data that the business doesn’t pull together in the regular course of business. Technology is now advanced enough to be able to provide business insights from this data that can be shared with the business as a whole.Example #1: Artificial intelligence can be used to create compliance models that show correlations between expense reports, trade journals, and sales behavior to identify bad behaviors. Sharing these types of learnings from matters can open up discussions among executives as to which learnings deserve a deeper dive. As an aside, you could also imagine a scenario where this same logic can also be used inversely – when combined with revenue it could identify effective sales behaviors – although this is something that would be a bigger lift and I would expect the sales department to drive this type of work.Example #2: The amount of duplicative data is a common metric reported in litigations or investigations. Sharing this with your IT team can highlight an easy storage win and legal can help craft a plan of how to attack duplicative data thereby leading to lower storage costsI would be remiss if I didn’t mention that there are opportunities for the legal department in these metrics as well. By using these metrics, as well as the artificial intelligence mentioned above, legal operations can resource plan and drive savings within the legal department. For example, the number of NDAs and sales contracts can inform staffing. Technology can identify contracts or other documents that are repetitive and automate the handling of those documents. Within litigation and investigations, technology can identify objectively non-responsive data so that it does not need to be collected as well as identify sources that are lower risk which don’t require outside counsel review and previously collected data that can be re-used.I hope that with the above metrics, you’re able to participate in some great business discussions and show how your legal department is not only effective in its own right but how integral a unit it is to driving the core business.ai-and-analytics; legal-operationsreporting, legal-ops, blog, ai-and-analytics, legal-operationsreporting; legal-ops; bloglighthouse

Evolving analytics tools and methods can help expedite review.Analyze this! No, we’re not talking about the 1999 movie starring Robert DeNiro and Billy Crystal, but rather analytics mechanisms that many organizations are using today to streamline discovery. As these mechanisms become more sophisticated, it pays to keep abreast of the ways in which they can impact a review, including how data can be organized, visualized, identified and reduced.For example, conceptual clustering can identify groups of topics that might be clearly responsive or non-responsive. Communication visualization maps can identify communication patterns of key parties within a data collection And, of course, predictive coding can train a supervised machine learning algorithm to identify potentially responsive and non-responsive documents based on classifications of other documents.But there are other use cases for eDiscovery analytics many organizations aren’t taking advantage of that make eDiscovery workflows even more efficient and more cost effective. To improve the efficiency of eDiscovery workflows, organizations can now implement technology with the following analytics features.Email Threading and Near Duplicate IdentificationYou may have heard the famous phrase “Insanity is doing the same thing over and over again expecting a different result.” But, in document review, insanity is simply doing the same thing over and over again. De-duplication using hash values identifies documents that are exact duplicates in content and format, but there is considerable additional content within document collections that is also duplicated within documents that aren’t exact matches. Email conversation threads contain considerable duplicative information, but conversations between multiple people can branch off, so you can’t just assume that the last message for the thread contains the entire thread discussion.Documents converted to PDF may be identical in content but not format, so they have different hash values and are not “de-duped.” ESI collections often include multiple drafts of documents that have both duplicative and unique content. To avoid over-capture of duplicates and gain visibility into email branches, organizations can now employ advanced analytics that can help in the following ways:Utilize advanced algorithms to identify email thread relationships and individual emails in a thread with unique contentGroup similar documents with flexible near-duplicate identification to easily review and compare to determine whether the differences are significantIdentify exact content duplicates with only formatting differences that hash de-duplication would not catch.Name Normalization and Entity AnalysisWhat’s in a name? Potentially, a whole lot of options! If the sixth US president were alive today and sending emails, here are some ways that you might see him represented within the collection:John AdamsJohnny AdamsJohn Q. AdamsQ. AdamsQuincy AdamsAdams, JohnAdams, John Q.Adams, J.Q.Adams, J. Quincyjadams@xyzcorp.com/O=XYZCORP/OU=EXCHANGE ADMINISTRATIVE GROUP (FYDIBOHF23SPDLT)/CN=RECIPIENTS/CN=jadamsAdams@gmail.comAnd potentially more…That’s a lot of variation – just for one person! Case teams often waste significant time and energy sorting through the numerous variations of names and email addresses for individuals in a matter. Advanced analytics solutions can be used to automated name normalization algorithms to link different name variations and email addresses to a single individual, format those names uniformly and aggregate the normalized participants that appear across an entire email thread group. The result? Refined results that streamline processes such as privilege logging without the intensive manual cleanup typically associated with the process.Metadata AnalyticsAI-driven analytics applied to the metadata can streamline eDiscovery by:a) identifying mass email communications so that reviewers can focus on more likely responsive emails;b) filtering email signature images and other extraneous embedded objects; andc) remediating data populations with missing or incomplete metadata by auto-detecting and populating email metadata fields on inbound productions.Privilege AnalyticsAutomated categorization and classification powered by advanced analytics can also be applied to privilege review to weed out non-responsive and non-privileged material early and rapidly identify, elevate and prioritize potentially privileged information. Customizable rules to exclude disclaimers and boilerplate language can also improve the accuracy of that identification process by eliminating many false positives.As most privilege determinations involve considerations of nuance and context, human judgments are a necessary part of the process. Pre-built and customized linguistic models, name normalization and email thread identification can extend those automated privilege determinations more quickly through the collection, with automated identification of legal concepts, privilege actors and law firms and a reusable asset with consistent propagation of privilege designations across matters.And clean name normalization outputs, along with automated and customizable privilege reasons assigned to each document expedite privilege log creation, significantly decreasing the manual cleanup often associated with this time-consuming task.Personal Identifiable Information (PII) DetectionFinally, with all of the data privacy requirements associated with recent regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), identifying and protecting PII has become a requirement within every phase of the eDiscovery lifecycle. Using analytics and pattern matching through regular expressions (RegEx) to identify common format numbers such as passport IDs, social security numbers, drivers license numbers and credit card numbers, as well as identification of common form types that often contain PII (such as loan applications or IRS forms) will help flag those documents so that they can be adequately protected throughout the process.Newer, more advanced AI-driven analytics solutions go a step further by utilizing highly precise classifiers to model the way in which different forms of supported personal data appear in data populations. These automated solutions provide rapid identification of likely and potential PII, resulting in rapid insights and immediate access to the most relevant documents first.ConclusionYou may be using analytics to streamline parts of your eDiscovery process, but there are always new use cases being identified to leverage analytics to make your eDiscovery workflows more efficient. Even Analyze This had a sequel!For more information on ways H5 Matter Analytics® can assist your organization in creating efficiencies and expediting eDiscovery workflows, click here.ediscovery-reviewblog, -ediscovery, data-analytics, document-review, ediscovery-review, aiandanalyticsblog; ediscovery; data-analytics; document-reviewlighthouse

Artificial intelligence (AI) has proliferated across industries, in popular culture, and in the legal space. But what does AI really mean? One way to look at it is in reference to technology that lets lawyers and organizations efficiently manage massive quantities of data that no one’s been able to analyze and understand before.While AI tools are no longer brand new, they’re still evolving, and so is the industry’s comfort and trust in them. To look deeper into the technology available and how lawyers can use it Lighthouse hosted a panel featuring experts Mark Noel, Director of Advanced Client Data Solutions at Hogan Lovells, Sam Sessler, Assistant Director of Global eDiscovery Services at Norton Rose Fulbright, Bradley Johnston, Senior Counsel eDiscovery at Cardinal Health, and Paige Hunt, Lighthouse’s VP of Global Discovery Solutions.Some of the key themes and ideas that emerged from the discussion include:Defining AIMeeting client expectationsUnderstanding attorneys’ duty of competenceIdentifying critical factors in choosing an AI toolAssessing AI’s impact on process and strategyThe future of AI in the legal industryDefining AIThe term “AI” can be misleading. It’s important to recognize that, right now, it’s an umbrella term encompassing many different techniques. The most common form of AI in the legal space is machine learning, and the earliest tools were document review technologies in the eDiscovery space. Other forms of AI include deep learning, continuous active learning (CAL), neural networks, and natural language processing (NLP).While eDiscovery was a proving ground for these solutions, the legal industry now sees more prebuilt and portable algorithms used in a wide range of use cases, including data privacy, cyber security, and internal investigations.Clients’ Expectations and Lawyers’ DutiesThe broad adoption of AI technologies has been slow, which comes as no surprise to the legal industry. Lawyers tend to be wary of change, particularly when it comes at the hands of techniques that can be difficult to understand. But our panel of experts agreed that barriers to entry were less of an issue at this point, and now many lawyers and clients expect to use AI.Lawyers and clients have widely adopted AI techniques in eDiscovery and other privacy and security matters. However, the emphasis from clients is less about the technology and more about efficiency. They want their law firms and vendors to provide as much value as possible for their budgets.Another client expectation is reducing risk to the greatest extent possible. For example, many AI technologies offer the consistency and accuracy needed to reduce the risk of inadvertent disclosures.Mingled with client expectations is a lawyer’s duty to be familiar with technology from a competency standpoint. We aren’t to the point in the legal industry where lawyers violate their duty of competence if they don’t use AI tools. However, the technology may mature to the point where it becomes an ethical issue for lawyers not to use AI.Choosing the Right AI ToolDecide Based on the Search TaskThere’s always the question of which AI technology to deploy and when. While less experienced lawyers might assume the right tool depends on the practice area, the panelists all focused on the search task. Many of the same search tasks occur across practice areas and enterprises.Lawyers should choose an AI technology that will give them the information they need. For example, Technology-assisted review (TAR) is well-suited to classifying documents, whereas clustering is helpful for exploration.Focus More on FeaturesTeams should consider the various options’ features and insights when purchasing AI for eDiscovery. They also must consider the training protocol, process, and workflow. At the end of the day, the results must be repeatable and defensible. Several solutions may be suitable as long as the team can apply a scientific approach to the process and perform early data assessment. Additional factors include connectivity with the organization’s other technology and cost.The process and results matter most. Lawyers are better off looking at the system as a whole and its features in deciding which AI tech to deploy instead of focusing on the algorithm itself.Although not strictly necessary, it can be helpful to choose a solution the team can apply to multiple problems and tasks. Some tools are more flexible than others, so reuse is something to consider.Some Use Cases Allow for ExperimentationThere’s also the choice between a well-established solution versus a lesser-known technology. Again, defensibility may push a team toward a well-known and respected tool. However, teams can take calculated risks with newer technologies when dealing with exploratory and internal tasks.A Custom Solution Isn’t NecessaryThe participants noted the rise in premade, portable AI solutions more than once. Rarely will it benefit a team to create a custom AI solution from scratch. There’s no need to reinvent the wheel. Instead, lawyers should always try an off-the-shelve system first, even if it requires fine-tuning or adjustments.AI’s Impact on ProcessThe process and workflow are critical no matter which solution a team chooses. Whether for eDiscovery, an internal investigation, or a cyber security incident, lawyers need accurate and defensible results.Some AI tools allow teams to track and document the process better than others. However, whatever the tool’s features, the lawyers must prioritize documentation. It’s up to them to thoughtfully train the chosen system, create a defensible workflow, and log their progress.As the adage goes: garbage in, garbage out. The effort and information the team inputs into the AI tool will influence the validity of the results. The tool itself may slightly influence the team’s approach. However, any approach should flow from a scientific process and evidence-based decisions.AI’s Influence on StrategyThere’s a lot of potential for AI to help organizations more strategically manage their documents, data, and approach to cases. Consider privileged communications and redactions. AI tools enable organizations to review and classify documents as their employees create them—long before litigation or another matter. Classification coding can travel with the document, from one legal matter to another and even across vendors, saving organizations time and money.Consistency is relevant, too. Organizations can use AI tools to improve the accuracy and uniformity of identifying, classifying, and redacting information. A well-trained AI tool can offer better results than people who may be inconsistently trained, biased, or distracted.Another factor is reusing AI technology for multiple search tasks. Depending on the tool, an organization can use it repeatedly. Or it can use the results from one project to the next. That may look like knowing which documents are privileged ahead of time or an ongoing redaction log. It can also look like using a set of documents to better train the algorithm for the next task.The Future of AIThe panelists wrapped the webinar by discussing what they expect for the future of AI in the legal space. They agreed that being able to reuse work products and the concept of data lakes will become even greater focuses. Reuse can significantly impact tasks that have traditionally had a huge cost burden, such as privilege reviews and logs, sensitive data identification, and data breach and cyber incidents.Another likelihood is AI technology expanding to more use cases. While lawyers tend to use these tools for similar search tasks, the technology itself has potential for many other legal matters, both adversarial and transactional. To hear more of what the experts had to say, watch the webinar, “Deploying Modern Analytics for Today’s Critical Data Challenges.” ai-and-analytics; ediscovery-review; lighting-the-path-to-better-ediscoveryai-big-data, blog, data-reuse, project-management, ai-and-analytics, ediscovery-reviewai-big-data; blog; data-reuse; project-managementai-analyticslighthouse

Much of the workforce has been forced into remote work due to social distancing requirements because of the pandemic, and that includes the workforce conducting services related to electronic discovery. Many providers have been forced into remote work for services including collection and review. Other providers have been already conducting those services remotely for years, so they were well prepared to continue to provide those services remotely during the pandemic.Make no mistake, it’s important to select a review provider that has considerable experience conducting remote reviews which extends well before the pandemic. Not all providers have that level of experience. But the success of your reviews isn’t about location, location, location; it’s about process, process, process — and the ability to manage the review effectively regardless of where it’s conducted. Here are four best practices to make your document reviews more efficient and cost effective, regardless of where they’re conducted:Maximize culling and filtering techniques up front: Successful reviews begin with identifying the documents that shouldn’t be reviewed in the first place and removing them from the document collection before starting review. Techniques for culling the document collection include de-duplication and de-nisting and identification of irrelevant domains. But it’s also important to craft a search that maximizes the balance between recall and precision to exclude thousands of additional documents that might otherwise be needlessly reviewed, saving time and money during document review.Combine subject matter and best practice expertise: Counsel understands the issues associated with the case, but they often don’t understand how to implement sophisticated discovery workflows that incorporate the latest technological approaches (such as linguistic search) to maximize efficiency. It’s important to select the provider that knows the right questions to ask to combine subject matter expertise with eDiscovery best practices to ensure an efficient and cost-effective review process. It’s also important to continue to communicate and adjust workflows during the case as you learn more about the document collection and how it relates to the issues of the case.Conduct search and review iteratively: Many people think of eDiscovery document review as a linear process, but the most effective reviews today are those that implement an iterative process that that interweave search and review to continue to refine the review corpus. The use of AI algorithms and expert-designed linguistic models to test, measure and refine searches is important to achieve a high accuracy rate during review, so remember the mantra of “test, measure, refine, repeat” for search and review to maximize the quality of your search and review process.Consider producing iteratively, as well: Discovery is a deadline driven process, but that doesn’t mean you have to wait for the deadline to provide your entire production to opposing counsel. Rolling productions are common today to enable producing parties to meet their discovery obligations over time, establishing goodwill with opposing counsel and demonstrating to the court that you have been meeting your obligations in good faith along the way if disputes occur. Include discussion of rolling productions in your Rule 26(f) meet and confer with opposing counsel to enable you to manage the production more effectively over the life of the project.You’re probably familiar with the famous quote from The Art of War by Sun Tzu that “every battle is won or lost before it is ever fought,” which emphasizes the importance of preparation before proceeding with the task or process you plan to perform. Regardless where your review is being conducted, it’s not the location, location, location that will determine the success of your review, but the process, process, process. After all, it’s called “managed review” for a reason!ediscovery-reviewblog, -document-review, ediscovery-review,blog; document-reviewlighthouse

What is data reuse? There are many different flavors and not everyone thinks about it the same way. In the context of eDiscovery, subject-matter specific work product in the form of responsiveness or issue coding often comes to mind and is then immediately dismissed as untenable given that the definitions for these can change from matter to matter. This is just one tiny piece of what’s possible, however. We need to consider the entire EDRM from end to end. What else has already been done, and what can be gained from it?First, there’s the source data itself. The underlying electronically stored information (ESI) is foundational to the reuse of data as a whole. Many corporations deal with frequent litigation and investigations, and those matters often include the same or at least overlapping players, i.e. the “frequent flier” custodians. This means the same data is relevant to multiple matters, which means it can be reused. There’s the potential for a one-to-many relationship here. In other words, instead of starting from scratch with each new project by going back to the same sources to collect the same data, why not take stock of what has been collected already? Compare the previously collected inventory to what is required for each specific matter, and then return to the well for the difference as needed. It may be as simple as a “refresh” to capture a more recent date range, or, even better, there’s no new collection to be done at all.Next up is the processed data. Once it’s collected, a lot of time, effort, and money are spent transforming ESI into a more consumable format. Extracting and indexing the metadata such that it can easily be searched and reviewed in your platform of choice takes real effort. Considering the lift, utilizing data that has already undergone processing makes a lot of sense. Depending on volume, significant savings in terms of timeline and fees are often realized, and this is not a one-time thing. The same data often comes up over and over across multiple matters, compounding savings over time.Finally, after processing comes review, which is where reusing existing work product comes in. This isn’t limited to relevance calls, which may or may not consistently apply across matters. There’s limited application for the reuse of subject-matter specific work product as mentioned earlier. The real treasure trove is all the different types of static work product – the ones that remain the same across matters regardless of the relevance criteria – and there are so many! One valuable step that is often overlooked is the ability to dismiss portions of the data population upfront. Often there is some chunk of data that will simply never be of interest. These are the “junk” or “objectively non-relevant” files that can clog a review. For example, automatic notifications, spam advertisements, and other mass mailings can contribute a lot of volume and rarely have any chance of including relevant content. Also, think about redactions and what often drives them: PII, PHI, trade secret, IP, etc. These are a pain to deal with, so why force the need to do so repeatedly? And, what about privilege? Identifying it is one thing, and then there are the incredibly time intensive privilege log entries that follow. These don’t change, and the cost to handle them can be steep. On top of that, they are incredibly sensitive, so ensuring accuracy and consistency is key. That’s pretty difficult to accomplish from matter to matter if you rely on different reviewers starting over each time.At the end of the day, no one wants to waste time and effort on unnecessary tasks, especially considering how often intense deadlines loom right out of the gate. The key is understanding what has already been done that overlaps with the matter at hand and leveraging it accordingly. In other words, know what you have and use it to avoid performing the same task twice wherever possible.ai-and-analytics; ediscovery-reviewediscovery-process, data-re-use, blog, ai-and-analytics, ediscovery-reviewediscovery-process; data-re-use; bloglighthouse

As summarized in the first installment of our two-part blog series, President Biden recently issued a sweeping Executive Order aimed at improving the nation’s cybersecurity defense. The Order is a reaction to increased cybersecurity attacks that have severely impacted both the public and private sectors. These recent attacks have evolved to a point that industry solutions have a much more difficult time detecting encryption and file state changes in a reasonable timeframe to prevent an actual compromise. The consequence is that new and evolving ransomware and malware attacks are now getting past even the biggest solution providers and leading scanners in the industry.Thus, while on its face, many of the new requirements within the Order are aimed at federal agencies and government subcontractors, the ultimate goal appears to be to create a more unified national cybersecurity defense across all sectors. In this installment of our blog series, I will outline recommended steps for private sector organizations to prepare for compliance with the Order, as well as general best-practice tips for adopting a more preemptive approach to cybersecurity. 1. Conduct a Third-Party AssessmentFirst and foremost, organizations must understand their current cybersecurity posture. Given the severity and volume of recent cyberattacks, third-party in-depth or red-team assessments should be done that would include not only the organization’s IT assets, but also include solutions providers, vendors, and suppliers. Red teaming is the process of providing a fact-driven adversary perspective as an input to solving or addressing a problem. In the cybersecurity space, it has become a best practice wherein the cyber resilience of an organization is challenged by an adversary or a threat actor’s perspective.[1] Red-team testing is very useful to test organizational policies, procedures, and reactions against defined, intended standards.A third-party assessment must include a comprehensive remote network scan and a comprehensive internal scan with internal access provided or gained with the intent to detect and expose potential vulnerabilities, exploits, and attack vectors for red-team testing. Internal comprehensive discovery includes scanning and running tools with the intent to detect deeper levels of vulnerabilities and areas of compromise. Physical intrusion tests during red-team testing should be conducted on the facility, networks, and systems to test readiness, defined policies, and procedures.The assessment will evaluate the ability to preserve the confidentiality, integrity, and availability of the information maintained and used by the organization and will test the use of security controls and procedures used to secure sensitive data.2. Integrate Solution Providers and IT Service Companies into Plans to Address Above Executive Order StepsTo accurately assess your organization’s risk, you first have to know who your vendors, partners, and suppliers are with whom you share critical data. Many organizations rely on a complex and interconnected supply chain to provide solutions or share data. As noted above, this is exactly why the Order will eventually broadly impact the private sector. While on its face, the Order only seems to impact federal government and subcontractor entities, those entities’ data infrastructures (like most today) are interconnected environments composed of many different organizations with complex layers of outsourcing partners, diverse distribution routes, and various technologies to provide products and services – all of whom will have to live up to the Order’s cybersecurity standards. In short, the federal government is recognizing that its vendors, partners, and suppliers’ cybersecurity vulnerabilities are also its own. The sooner all organizations realize this the better. According to recent NIST guidance, “Managing cyber supply chain risk requires ensuring the integrity, security, quality, and resilience of the supply chain and its products and services.” NIST recommends focusing on foundational practices, enterprise-wide practices, risk management processes, and critical systems. “Cost-effective supply chain risk mitigation requires organizations to identify systems and components that are most vulnerable and will cause the largest organizational impact if compromised.[2]In the recent attacks, hackers inserted malicious code into Orion software, and around 18,000 SolarWinds customers, including government and corporate entities, installed the tainted update onto their systems. The compromised update has had a sweeping impact, the scale of which keeps growing as new information emerges. Locking down your networks, systems, and data is just the beginning! Inquiring how your supply chain implements a Zero Trust strategy and secures their environment as well as your shared data is vitally important. A cyber-weak or compromised company can lead to exfiltration of data, which a bad actor can exploit or use to compromise your organization.3. Develop Plan to Address Most Critical Vulnerabilities and Threats Right AwayThird-party assessors should deliver a comprehensive report of their findings that includes the descriptions of the vulnerabilities, risks found in the environment, and recommendations to properly secure the data center assets, which will help companies stay ahead of the Order’s mandates. The reports typically include specific data obtained from the network, any information regarding exploitation of exposures, and the attempts to gain access to sensitive data.A superior assessment report will contain documented and detailed findings as a result of performing the service and will convey the assessor’s opinion of how best to remedy vulnerabilities. These will be prioritized for immediate action, depending upon the level of risk. Risks are often prioritized as critical, high, medium, and low risk to the environment, and a plan can be developed based upon these prioritizations for remediation.4. Develop A Zero Trust StrategyAs outlined in Section 3 of the Order, a Zero Trust strategy is critical to addressing the above steps, and must include establishing policy, training the organization, and assigning accountability for updating the policy. Defined by the National Security Agency (NSA)’s “Guidance on the Zero Trust Security Model”: “The Zero Trust model eliminates trust in any one element, node, or service by assuming that a breach is inevitable or has already occurred. The data-centric security model constantly limits access while also looking for anomalous or malicious activity.”[3]Properly implemented Zero Trust is not a set of access controls to be “checked,” but rather an assessment and implementation of security solutions that provide proper network and hardware segmentation as well as platform micro-segmentation and are implemented at all layers of the OSI (Open Systems Interconnection) model. A good position to take is that Zero Trust should be implemented using a design where all of the solutions assume they exist in a hostile environment. The solutions operate as if other layers in a company’s protections have been compromised. This allows isolation of the different layers to improve protection by combining the Zero Trust principles throughout the environment from perimeters to VPNs, remote access to Web Servers, and applications. For a true Zero Trust enabled environment, focus on cybersecurity solution providers that qualify as “Advanced” in the NSA’s Zero Trust Maturity Model; as defined in NSA’s Cybersecurity Paper, “Embracing a Zero Trust Security Model.”[4] This means that these solution providers will be able to deploy advanced protections and controls with robust analytics and orchestration.5. Evaluate Solutions that Pre-emptively Protect Through Defense-In-DepthIn order to further modernize your organization’s cybersecurity protection, consider full integration and/or replacement of some existing cybersecurity systems with ones that understand the complete end-to-end threats across the network. How can an organization implement confidentiality and integrity for breach prevention? Leverage automated, preemptive cybersecurity solutions, as they possess the greatest potential in thwarting attacks and rapidly identifying any security breaches to reduce time and cost. Use a Defense-in-Depth blueprint for cybersecurity to establish outer and inner perimeters, enable a Zero Trust environment, establish proper security boundaries, provide confidentiality for proper access into the data center, and support capabilities that prevent data exfiltration inside sensitive networks. Implement a solution to continuously scan and detect ransomware, malware, and unauthorized encryption that does NOT rely on API calls, file extensions, or signatures for data integrity.Solutions must have built-in protections leveraging multiple automated defense techniques, deep zero-day intelligence, revolutionary honeypot sensors, and revolutionary state technologies working together to preemptively protect the environment. ConclusionAs noted above, Cyemptive recommends the above steps in order to take a preemptive, holistic approach to cybersecurity defense. Cyemptive recommends initiating the above process as soon as possible – not only to comply with potential government mandates brought about due to President Biden’s Executive Order, but also to ensure that organizations are better prepared for the increased cybersecurity threat activity we are seeing throughout the private sector. ‍[1]“Red Teaming for Cybersecurity”. ISACA Journal. October 18, 2018. https://www.isaca.org/resources/isaca-journal/issues/2018/volume-5/red-teaming-for-cybersecurity#1 [2] “NIST Cybersecurity & Privacy Program” May 2021. Cyber Supply Chain Risk Management C-SCRM” https://csrc.nist.gov/CSRC/media/Projects/cyber-supply-chain-risk-management/documents/C-SCRM_Fact_Sheet_Draft_May_10.pdf [3] “NSA Issues Guidance on Zero Trust Security Model”. NSA. February 25, 2021. https://www.nsa.gov/Press-Room/News-Highlights/Article/Article/2515176/nsa-issues-guidance-on-zero-trust-security-model/[4] “Embracing a Zero Trust Security Model.” NSA Cybersecurity Information. February 2021. https://media.defense.gov/2021/Feb/25/2002588479/-1/-1/0/CSI_EMBRACING_ZT_SECURITY_MODEL_UOO115131-21.PDFdata-privacy; information-governancecloud, cybersecurity, blog, corporate, data-privacy, information-governancecloud; cybersecurity; blog; corporatelighthouse

Now more than ever, data security has become priority number one, especially in the context of litigation and eDiscovery. And as the worlds of eDiscovery, information governance, and cybersecurity continue to rapidly converge, cybersecurity incidents are alarmingly on the rise, showcasing all of the weaknesses in an organization’s information governance system. Addressing cybersecurity continues to be a top challenge in eDiscovery. Many are unsure if their own internal processes are safe, not to mention those of the vendors who manage their outsourced eDiscovery.So, how can you protect your ESI all the way from preservation and collection to review and production? In a Law and Candor podcast episode, special guest David Kessler, Head of Data and Information Risk at Norton Rose Fulbright US LLP, discussed with our hosts the diverse set of challenges that arise with data security at each stage of the EDRM. Most understand the right methods start with implementing the fundamentals of cybersecurity, but some have learned the hard way that you can’t fix a house built on a shaky foundation after a cybersecurity disaster strikes. With the protection of client ESI first and foremost top of mind, here are the some of the most pressing cybersecurity challenges in eDiscovery as well as actionable solutions.Cybersecurity Challenges in eDiscoveryThe intersection of information governance, eDiscovery, and data security: The nature of data has evolved such that eDiscovery and information governance naturally intersect with data privacy and security. We’ve learned that issues around data access are very similar to eDiscovery issues and the next challenge is learning how to operate the areas together cohesively. In addition, with the shift to scrutiny on privacy and what can be done with personal data, now we know almost all cases that involve ESI have tremendous privacy concerns.The important role eDiscovery plays in cybersecurity: No longer are the days where confidential data relevant to litigation is primarily found in email and simply on computers. Now, data is created and stored across a wide variety of mediums and the amount of data continues to grow at an exponential rate. For cybersecurity criminals, this is a gold mine of confidential data available to steal and access.The outstanding security gaps throughout the EDRM: Historically, we’ve been focused on the responding parties’ obligations to securely undertake discovery. The business process of eDiscovery is primarily about collecting, copying, and transferring data outside of an organization, which creates concerns about securing that information at every stage of the process. Both the responding and requesting parties need to find a way to collaboratively and cooperatively work together at the beginning of a case to ensure data is protected through the entire EDRM lifecycle.The weakest part of the cybersecurity chain is when you hand over sensitive data: How do we help clients make sure their data isn’t accidentally or intentionally taken from them during the eDiscovery process? Everyone from eDiscovery vendors to law firms has an obligation to shore up their security and organizations have a responsibility to thoroughly vet those partners as they hand over their most sensitive data. In the EDRM, attention has shifted to making sure cybersecurity protections span the entire EDRM and the last step that hasn’t received much attention is making sure the requesting party is taking the appropriate steps to secure the data once they receive it.Cybersecurity Solutions in eDiscoveryShore up cybersecurity contracts and repurpose existing security riders: When an organization engages law firms and eDiscovery vendors to handle discovery, it’s important they work closely with their data security IT team. These teams can help to repurpose some of the standard security riders from other contracts and use it to create new contracts with the appropriate protections in place.Establish comprehensive protective orders at the beginning of cases: With respect to the requesting party, who you will ultimately be producing the data to, ensure that early in the case you’ve negotiated a comprehensive protective order that includes reasonable and proportionate requirements for the protection of data. In that protection order (and a step that’s often forgotten), follow up and confirm the data you produced has been deleted after a case is over.Keep open lines of communication with law firms and eDiscovery vendors: Your discovery partners understand and have a significant stake in their security reputations. They have a strong motivation to work with you to execute risk assessments and other agreements that contain the necessary security provisions to ensure your data is safe at every step of the process. Also, include a breach notification order if data is accidentally lost or there’s an attack.Focus on things you can do to strengthen your productions: Think about the most efficient ways to reduce the number of copies involved in productions where appropriate. For example, use redaction as much as possible and consequently less copies of data. Don’t produce sensitive and irrelevant portions of data – redact it instead.Ultimately, most people have become acutely aware of the vulnerabilities that exist in data security as it travels through the EDRM, and as law firms and eDiscovery vendors become accustomed to deeper vetting, it’s at the production stage where the biggest security vulnerabilities seem to remain. To get ahead of all aspects of potential cybersecurity failures, the use of well-written protective orders will get you a long way. Requirements in protective orders can ensure all parties take reasonable steps to protect data from third-party hackers and unauthorized access, as well as include protections based on encryption, access controls, passwords, etc.data-privacy; information-governance; ediscovery-reviewcybersecurity, cloud-security, ediscovery-process, preservation-and-collection, blog, data-privacy, information-governance, ediscovery-review,cybersecurity; cloud-security; ediscovery-process; preservation-and-collection; bloglighthouse

When it comes to storing organizational data in the Cloud, a few phrases come to mind: the train has left the station; the ship has sailed; the horse is out of the barn, etc. No matter how you phrase it, the meaning is the same – the world is moving to the Cloud, with or without you. It is no longer an oncoming revolution. The revolution is here and your organization needs to prepare for dealing with data in the Cloud, if it hasn’t already. With that in mind, let’s talk cloud logistics – namely, security and cost.First up to the Plate – Cloud Security You might have heard the analogy circulating in technology forums recently that storing your data within the Cloud is akin to storing data on someone else’s hard drive. Unfortunately, from a security perspective, that’s not quite an accurate analogy (although life would be much easier if it were true).Don’t get me wrong - a significant benefit of moving to the Cloud is that it allows an organization to transfer much of the day-to-day security management to a technology company with the resources and expertise to handle that risk. Thus, if you are moving to a private cloud (i.e., renting data center space for your equipment), you can ease security concerns by ensuring that the hosting company maintains widely recognized security attestations/certifications and has a demonstrated commitment to data center security in accordance with strict vendor management risk processes. And of course, there’s always the reassurance when moving to a public cloud (Microsoft’s Azure or Amazon’s AWS) that you’re entrusting your data to companies with seemingly infinite security resources and expertise. That all certainly helps me sleep better at night.However, working within the Cloud still poses unique internal security challenges that will only amplify any of your existing security weaknesses if you’re not prepared for them. To put it another way: ISO certifications from cloud service providers cannot protect you from yourself. Risk, governance, and compliance teams will need to identify, plan for and adapt to internal security challenges. To do so, be sure to have a change management and review approval process in place (ideally before moving to the Cloud, but if not, as soon as possible once you’ve migrated). Also, ensure that your company has someone on hand (either through a vendor or within your IT staff) with the expertise needed to manage your internal cloud security who can stay abreast of all updates and changes.Next up – CostTo plan for a cloud migration, all stakeholders (including Legal Operations, Finance, DevOps, Security, and IT) should have a seat at the table and a plan in place for scaling up in the Cloud. Each team should understand the plan and process, as well as the role their team plays in controlling cost and risk for the company.Cloud Security and Costs Best PracticesTo plan for security risk in the Cloud, companies should ensure that:All cloud service providers are fully vetted, security certified, and have the requisite posture in place to fully protect your data.Company internal processes are evaluated for security risks and gaps. Have a change management and review approval process in place and ensure that you have the experts on hand to manage your cloud security practices and stay abreast of all updates and changes.To plan for costs, companies should ensure that:All stakeholders (including Legal Operations, Finance, DevOps, Security, and IT) collaborate and have a plan in place for scaling up within the Cloud when needed.Each team understands the plan and process, as well as the role their team plays in controlling cost and risk for the company.data-privacy; information-governancecloud-security, cloud-migration, blog, data-privacy, information-governancecloud-security; cloud-migration; blogmarcelino hoyla

On May 12, President Biden issued a landmark Executive Order (“the Order”) aimed at improving the country’s cybersecurity threat defense. This Order is an attempt to create a “whole of government” response to increasingly frequent cybersecurity incidents that have wreaked havoc in the United States in recent months, affecting everything from energy supplies to healthcare systems to IT infrastructure systems. In addition to becoming more frequent, recent cyberattacks have also become increasingly more sophisticated – and even somewhat professional. In response to these attacks, the Biden administration seeks to build a national security framework that aligns the Federal government with private sector businesses in order to “modernize our cyber defenses and enhance the nation’s ability to quickly and effectively respond to significant cybersecurity incidents.” Prior to this Order, there has been no unified system to report or respond to cybersecurity threats and breach incidents. Instead, there is currently a patchwork of state legislation and separate federal government agency protocols, all with differing reporting, notification, and response requirements.In the first of this two-part blog series, I will broadly outline the details of this Order and what it will mean for private sector companies in the coming years. In the second installment, Rob Pike (CEO and Founder of Cyemptive Technologies) will provide guidance on how to set up your organization for compliance with the Order, as well as general best-practice tips for adopting a preemptive cybersecurity approach. What is in President Biden’s Executive Order on Improving the Nation’s CybersecurityThere are nine main sections to the Order, which are summarized below.Section 1: PolicyThis section outlines the overall goal of the Order – namely that, with this Order, the Federal government is intent on making “bold changes and significant investments in order to defend the vital institutions that underpin the American way of life.” To do so, the Order states that the government must improve its efforts to “identify, deter, protect against, detect, and respond to” cybersecurity attacks. While this may sound like a purely governmental task, the Order specifically states that this defense will require partnership with the private sector. Section 2: Removing Barriers to Sharing Threat Information As noted above, prior to this Order, there was no unified system for sharing information regarding threats and data breaches. In fact, separate agency procurement contract terms may actually prevent private companies from sharing that type of information with federal agencies, including the FBI. This section of the Order responds to those challenges by requiring the government to update federal contract language with IT service providers (including cloud service providers) to require the collection and sharing of threat information with the appropriate government agencies. While the Order currently only speaks to federal subcontractors, it is expected that this information-sharing requirement will have a trickle-down effect across the private sector, with purely private companies falling in line to share threat information once federal subcontractors are required to do so. Section 3: Modernizing Federal Government CybersecurityThis section calls for the federal government to adopt security best practices – and is specifically aimed at adopting Zero Trust Architecture and pushing a move to secure cloud services, including “Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).” It requires that each government agency update plans to prioritize the adoption and use of cloud technology and develop a plan to implement Zero Trust Architecture, in part by incorporating the migrations steps outlined by the National Institute of Standards and Technology (NIST).Section 4: Enhancing Software Supply Chain SecurityThis section deals with increasing the cybersecurity standards of software sold to the government. It specifically calls out the fact that the development of commercial software “often lacks transparency, sufficient focus on the ability of the software to resist attack, and adequate controls to prevent tampering by malicious actors.” It, therefore, calls for “more rigorous and predictable mechanisms for ensuring that products function securely.” Thus, this section calls for NIST to issue new security guidelines for software used by the government. These new guidelines will include encryption requirements, multi-factor and risk-based authentication requirements, vulnerability detection and disclosure programs, and trust relationship audits, among others.Section 5: Establishing a Cyber Safety Review BoardThis section establishes a federal Cyber Safety Review Board, which will convene following significant cyber incidents, providing recommendations to the Secretary of Homeland Security for improving cybersecurity and incident response practices. It will be made up of federal officials, as well as representatives from private sector entities.Section 6: Standardizing the Federal Government’s Playbook for Responding to Cybersecurity Vulnerabilities and IncidentsThis section again speaks to the patchwork of differing vulnerability and incident response procedures that currently exists across multiple federal agencies. The goal here is to create a standard set of operational procedures (or a playbook) for cybersecurity vulnerability and incident response activity. The playbook will have to incorporate all appropriate NIST standards, be used by all Federal Civilian Executive Branch (FCEB) Agencies, and spell out all phases of incident response.Sections 7 and 8: Improving Detection, Investigation, and Remediations of Cybersecurity Vulnerabilities and Incidents on Federal Government NetworksThese two sections focus on creating a unified approach to the detection, investigation, and remediation of cybersecurity vulnerabilities and incidents. Section 7 focuses on improving detection – mandating that all FCEB agencies deploy an “Endpoint Detection and Response (EDR)” initiative to support proactive detection of cybersecurity incidents and establishes a procedure for the implementation of threat hunting and detection, as well as inter-agency information sharing around threat detection. Section 8 is focused on improving the government’s investigative and remediation capabilities – namely, by establishing requirements for agencies and their IT service providers to collect, maintain, and share specified information from Federal Information System network logs.Section 9: National Security SystemsThis section requires the Secretary of Defense to adopt National Security System requirements that are at least equivalent to the requirements spelled out by the above sections in the Order.Who Will This Impact?As noted above, while the Executive Order is aimed at shoring up the federal government’s cybersecurity detection and response systems – its impacts will be felt throughout much of the private sector. That isn’t a bad thing! A patchwork cybersecurity system is clearly not the best way to respond to the increasingly sophisticated cybersecurity incidents currently threatening both the United States government and the private sector. Responding to these threats requires a robust, unified national cybersecurity system, which in turn requires updated and unified cybersecurity standards across both government agencies and private sector companies. This Executive Order is a great stepping stone towards that goal.As far as timing for private sector impacts: the first impacts will be felt by software companies and other organizations that directly contract with the federal government, as there are direct requirements and implications for those entities spelled out within the Order. Many of those requirements come into play within 60 days to a year after the date of the Order, so there may be a quick turnaround to comply with any new standards for those organizations. Impacts are then expected to trickle down to other private sector organizations: as government subcontractors update policies and systems to comply with the Order, they will in turn require the companies that they do business with to comply with the new cybersecurity standards. In this way, the Order actually creates an opportunity for the federal government to create a cybersecurity floor above which most companies in the US will eventually have to comply.ConclusionDetecting and defending against cybersecurity threats is an increasingly difficult worldwide challenge – a challenge to which, currently, no perfect defense exists. However, with this Order, the United States is taking a step in the right direction by creating a more unified cybersecurity standard and network that will encourage better detection, investigation, and mitigation.Check out the second installment of this blog series, where Rob Pike, CEO and Founder of Cyemptive Technologies, provides guidance on how to set up your organization for compliance with the Executive Order, as well as general best-practice tips for adopting a preemptive cybersecurity approach. If you would like to discuss this topic further, please reach out to me at erubenstein@lighthouseglobal.com.data-privacy; information-governancecloud, cybersecurity, blog, corporate, data-privacy, information-governancecloud; cybersecurity; blog; corporateerin rubenstein

There is much out there about cloud solutions and how they improve the lives of users, offer flexibility for expansion and contraction of business, and can lighten the lift for IT. There is even a lot of specific commentary about how cloud can help legal teams and enable change management for the department. But what about the day-to-day tasks? How does the cloud change the legal team’s work and what new governance and skills are necessary to handle that change? This blog will tackle these questions so you can be more prepared and agile as cloud technology advances.Why does a shift to the cloud matter for legal teams?From a practical perspective, it means having to be reactive in areas where legal has traditionally been more proactive. Things like data storage timelines and locations, internal access permissions, and document history are now ever-changing with software updates being automatically pushed to corporate software environments. Many organizations that manage on-premises software have historically had an effective software governance structure in place. They can meet, discuss upcoming upgrades and their impacts, and make decisions about when to execute a software upgrade. Now, in an agile cloud approach, upgrades come frequently, without much notice, and sometimes have highly impactful changes. Traditional governance structures are no longer sustainable given the new timing and volume of updates – sometimes hundreds in a week. Legal and IT teams now need to collaborate more often to quickly analyze any impacts updates will have on the organization and what, if anything, needs to be done to mitigate cloud security risks.Given this, how should corporate legal teams adapt?A typical legal department is organized around areas of expertise – you may have employment, litigation, business advice, and contracts, for example. The department may also have a legal operations function, or a member of the team assigned to certain process improvement and/or corporate programs. One of these programs covers technology changes at an organization. It is this latter set of responsibilities that become much more important, and more voluminous, in an agile software environment. Analyzing the potential risks of cloud updates, advising the business on how to mitigate those risks, and changing any associated legal workflows can become a full-time or close to full-time set of responsibilities. In addition, the culture of the department must change to one that embraces frequent change, understands change management, and is consistently updating and improving processes and procedures.Traditionally, in an on-premises environment, an IT organization would typically manage an upgrade governance structure. They would plan for a software upgrade every six months, outline the changes that are due with each upgrade, and analyze what departments it impacts and the risks of those impacts. Finally, they would present this information to a cross-functional committee who would discuss when the upgrade can be made and what kind of work needs to precede the upgrade. Legal was typically part of that committee. Now, in a cloud environment dozens (or even hundreds) of changes get pushed out weekly and, although there may be some advanced warning, the timing isn’t as flexible, it isn’t uniform across users, and there is usually less time to prepare. In addition, changes may be pushed out, rolled back, and potentially reversed. Updates may also occur without any warning, which can contribute to the cloud challenges for corporate legal departments[1]. To minimize risk in this agile environment some specific steps can be helpful: a similar governance committee needs to meet more frequently, the analysis of impact and risk needs to be done very quickly, and changes need to be made almost immediately to ensure you get ahead of any potential impacts. Due to the frequent nature of these changes, and supervising process updates to mitigate risk associated with the changes, managing cloud updates can be more time-consumingWithout structure, these cloud updates can add stress and increase reactive work. However, with some structure and clearly delineated oversight, they can be managed more efficiently. Although many organizations may not have a structure in place, those that do pull together a committee for each enterprise technology. This committee has IT, legal, compliance, and business-focused representation. It may have multiple representatives from some of these groups, depending on the perspectives needed. The goal is for the business representative to advocate for users of the technology, the legal and compliance representatives to mitigate risk and take into account regulatory, litigation and privacy considerations, and the IT team to represent management of the platform and be a voice for the platform provider. The committee should have access to a sandbox-type environment where they can test changes and should be empowered to lead companywide changes – or at least be able to work with a project management office or other resource to make these changes.Most legal departments run pretty lean so creating a new governance structure can be a significant challenge, but there are ways to make the process easier. First, you can hire outside support to handle all, or some, of this work. For example, outsourcing the creation of the governance structure to manage software updates and staffing that group with your own resources or have your external partner staff and manage it until a time when you are ready to take it over. Second, instead of hiring outside support, you can share your risk concerns with IT and rely on them to raise any potential impact that upgrades may have on risk and legal processes. For example, when IT receives an email from a software provider outlining updates, they would analyze them for potential impact to legal workflows, retention policies, or any other issues you have flagged. They would then test the updates and remediate any negative impacts. Finally, you can rotate governance committee membership so that the work is being shared across your team. Whatever approach you choose, keep in mind that changes in the cloud environment are happening frequently and having someone within your company watching from a legal perspective will pay dividends when it comes to accessing data for legal, compliance, investigative, or other reasons down the line.[1] Victoria Hudgins, “Big Adjustment: Legal Departments Struggle with Lack of Control Over Cloud Technology,” Legaltech news, November 29, 2021, law.com information-governance; microsoft-365; lighting-the-path-to-better-information-governancecloud-security, cloud-migration, blog, risk-management, information-governance, microsoft-365cloud-security; cloud-migration; blog; risk-managementlighthouse

Long gone are days when the majority of discovery records were kept in paper format. Documents, invoices, and other related evidence needed to be scanned and printed in the tens (if not hundreds) of thousands. Today, a huge number of discovery efforts (internal or external) revolve around digital content. Ergo, this article will highlight the collection of digital evidence and how to best prepare your case when it comes to preservation and collections as well as processing and filtering.But, before we get into that, one of the core factors to keep in mind here is time, which will always be there irrespective of what we have at hand. It is especially complicated if multiple parties are involved, such as vendors, multiple data locations, outside counsels, reviewers, and more. For the purposes of this blog, I have divided everything into the following actionable groups - preservation and collection as well as processing and filtering.Preservation and CollectionIn an investigation or litigation there could be a number of custodians involved, for example, people who have or had access to data. Whenever there are more than a handful of custodians the location may vary. It is imperative to consider where and what methods to use for data collection. Sometimes an in-person collection is more feasible than a remote collection. Other times, a remote collection is the preferred method for all those concerned. A concise questionnaire along with answers too frequently asked questions is the best approach to educate the custodian. Any consultative service provider must ensure samples are readily available to distribute that will facilitate the collection efforts.Irrespective of how large the collection is, or how many custodians there are, it is best to have a designated coordinator. This will make the communication throughout the project manageable. They can arrange the local technicians for remote collections and ship and track the equipment.The exponential growth in technology presents new challenges in terms of where the data can reside. An average person, in today’s world, can have a plethora of potential devices. Desktops and laptops are not the only media where data can be stored. Mobile devices like phones and tablets, accessories such as smartwatches, the IoT (everything connected to the internet), cars, doorbells, locks, lights…you name it. Each item presents a new challenge and must be considered when scoping the project.User-generated data is routinely stored and shared on the Cloud using a variety of platforms. From something as ancient as email servers to “new” rudimentary storage locations, such as OneDrive, Google Drive, Dropbox, and Box.com. Others include collaborative applications, such as SharePoint, Confluence, and the like.Corporate environments also heavily rely on some sort of common exchange medium like Slack, Microsoft Teams, and email servers. These applications also present their own set of challenges. We have to consider, not just what and how to collect, but equally important is how to present the data collected from these new venues.The amount of data collected for any litigation can be overwhelming. It is imperative to have a scope defined based on the need. Be warned, there are some caveats to setting limitations beforehand, and it will vary based on what the filters are. The most common and widely acceptable limitation is a date range. In most situations, a period is known and it helps to set these parameters ahead of time. In doing so, only the obvious date metadata will be used to filter the contents. For example, in the case of emails, you are limited to either the sent or received date. The attachment's metadata will be ignored completely. Each cloud storage presents its own challenges when it comes to dates.Data can be pre-filtered with keywords that are relevant to the matter at hand. It can greatly reduce the amount of data collected. However, it is solely dependent on indexing capabilities of the host, which could be non-existent. The graphical contents and other non-indexable items could be excluded unintentionally, even if they are relevant.The least favored type of filter among the digital-forensics community is a targeted collection, where the user is allowed to guide where data is stored and only those targeted locations are preserved. This may not be cost effective, however, it can restrict the amount of data being collected. This scope should always be expected to be challenged by other parties and may require a redo.Processing and FilteringOnce the data collected goes through the processing engine the contents get fully exposed. This allows the most thorough, consistent, and repetitive filtering of data. In this stage, filtering relies on the application vetted by the vendor and accompanied by a process that is tested, proven, and updated (when needed).The most common filtering in eDiscovery matters is de-NIST-ing, which excludes the known “system” files from the population. Alternatively, an inclusion filter can be applied, which only pushes forward contents that typically a user would have created, such as office documents, emails, graphic files, etc. In most cases, both de-NIST-ing and inclusion filters are applied.Once the data is sent through the meat grinder (the core processing engine) further culling can be done. At this stage, the content is fully indexed and extensive searches and filters will help limit the data population even further to a more manageable quantity. The processing engine will mark potentially corrupt items, which are likely irrelevant. It will also identify and remove any duplicate items from all collected media from the entire matter data population. Experts can then apply relevant keyword searches on the final product and select the population that will be reviewed and potentially produced.I hope this article has shed some light on how to best prepare your case when it comes to preservation and collections as well as processing and filtering. To discuss this topic further, please feel free to reach out to me at MMir@lighthouseglobal.com.digital-forensics; information-governance; chat-and-collaboration-datacollections, ediscovery-process, preservation-and-collection, processing, blog, digital-forensics, information-governance, chat-and-collaboration-data,collections; ediscovery-process; preservation-and-collection; processing; blogmahmood mir

Below is a copy of a featured article written by Denisa Luchian for The Lawyer.com, where she interviews Lighthouse's Matt Bicknell. Lighthouse business development director EMEA Matt Bicknell talks to The Lawyer about how in today’s remote environment, cloud based collaboration tools are not just desirable but a necessity – but also the challenges they pose for eDiscovery processes.What is the driving force behind the massive migration to cloud-based environments over the last few years?There are a few factors at play here. Prior to the Covid-19 pandemic, companies were already moving their data to the Cloud (both public and private) in droves, in order to take advantage of unlimited data capacities and drastically lower IT overhead. The move to the Cloud is also being driven by a younger workforce that feels at home working with cloud-based chat and collaboration tools, like M365 or G-Suite. However, the worldwide shift to remote work due to the pandemic really broke the dam when it comes to cloud migration. We’ve seen a seismic shift to cloud-based tools and environments since March of 2020. In a completely remote environment, cloud-based collaboration tools are not just desirable, they are necessary to keep workforces productive. Migrating to the Cloud can greatly reduce the need for workers to be physically present in an office building.What are some of the challenges that cloud migration can pose to the eDiscovery process?Unlimited storage capacity at low cost can be a great thing for an organisation’s bottom line, but can definitely cause issues when it comes time to find and collect data that is needed for a litigation or investigation. Search functions built for cloud-based tools are often built for business use, rather than for the functionality that legal and compliance teams require in order to find relevant information. In addition, collecting and producing from collaboration tools like Teams or Slack can be much more complicated than a traditional email collection. Relevant communications that previously would have happened over email now happen over chat, through emoticon reactions, or through collaboratively editing a document. All of this relevant data may be stored in several different places, in a variety of formats within the Cloud. Even attachments are handled differently in cloud-based applications – instead of sending a static document as an attachment via email, Teams defaults to sending a link to the document in Teams. This means that the document could look significantly different at the time of collection than it did when the link was sent. Collecting from those types of sources, producing them in a format that makes sense to a reviewer/opposing counsel, and accounting for all the dynamic variables can be a difficult hurdle to overcome if the organisation hasn’t planned for it.How can companies prepare for eDiscovery challenges in a cloud environment?First, make sure compliance, legal and IT all have a seat at the table and have input into decisions that may affect their workflows and processes. Understand where your data resides and have effective retention, data governance, and compliance policies in place. Your policies should spell out which cloud-based applications employees may use and also have rules in place regarding how they can be used and where work product should be stored. Understand your legal hold policy and what type of data it encompasses. Make sure you have the right talent (either within your organisation or through a vendor) who understands the underlying architecture behind Teams, G-Suite, or any other cloud-based tool your organisation uses and also knows how to collect relevant information when needed. Ensure that your IT team or vendor has a system in place to monitor application and system updates. Cloud-based updates can roll out on a weekly basis; those changes may significantly impact the efficacy of your data retention and collection policies and workflows.As cloud technology continues to evolve, what does the future hold for eDiscovery? Because of the near endless storage capacity of the Cloud, the amount of data companies generate will just continue to exponentially expand. As a result, the technology behind AI and analytics will continue to improve, and those tools will eventually be less of an option to use in certain matters and more of a necessity to use for most matters. I also think as more companies feel comfortable moving their data to the Cloud, we will start to see more and more of these companies bring their eDiscovery programs in house. Vendors are already beginning to offer subscription-based, self-service, spectra eDiscovery programs which hand over the eDiscovery reigns to the organisation, while the vendor stores and manages the data in the Cloud (both public and private). This type of service allows companies to eliminate the middleman, control their own eDiscovery costs, and easily scale up or down to meet their own needs, while leaving the burden of data storage security and maintenance with the vendor. Finally, look for vendors to start offering subscription-based services to help organisations manage the near-constant stream of application and system updates for cloud-based services.microsoft-365; chat-and-collaboration-data; information-governancemicrosoft, cloud, g-suite, blog, microsoft-365, chat-and-collaboration-data, information-governance,microsoft; cloud; g-suite; blogthe lawyer

Key ResultsEarly fact-finding with IQ AnswersAvoided weeks of traditional attorney work, resulting in massive savings and a crucial head start.AI-Powered quality control with IQ IssuesAchieved 90% alignment with IQ Issues and counsel’s coding on initial document sample, eliminating the need for a second sampling round.Custom AI Summarizations for second-level reviewDesigned and deployed a custom solution in one week to accelerate second-level review with comprehensive document summaries and key language excerpts.The Challenge: Anticipating Regulatory Scrutiny and Conquering Complex DataA large, multinational consumer platform received a regulatory information request from the Federal Trade Commission (FTC) consumer-protection concerns involving a core offering. Facing a high-stakes investigation, the company’s outside counsel needed to move quickly to interrogate a large volume of data, be proactive with anticipated follow-up requests, and ensure defensibility from the outset.The matter presented two time-sensitive challenges:Fact-Finding: To meet critical regulatory milestones and get ahead of the FTC, counsel needed to immediately interrogate the data and establish key facts. This urgency was compounded by the desire to identify and vet potential custodians in anticipation of the FTC expanding the scope of the information request. Tailored Solutions: A substantial portion of the relevant data was sourced from proprietary exports from two non-standard enterprise collaboration tools. These non-standard CSV-based exports were incompatible with industry-standard eDiscovery chat processing tools, creating a major roadblock for efficient and defensible review.In total, Lighthouse received roughly 4TB of raw data, which translated to just under 1.4M documents requiring processing.The Solution: A Two-Pronged Approach with AI and Custom EngineeringLighthouse partnered with outside counsel to deploy a strategy that leveraged advanced AI for early fact-finding and custom data engineering to normalize the most challenging data sources.IQ Answers: Accelerating Early Case Assessment and Fact-FindingTo address the volatile custodian list and scope, counsel utilized IQ Answers. This allowed the case team to move beyond the traditional “hunt and peck” method of keyword searching and instead use natural language prompts to interrogate the data early and efficiently.With guidance from the Expert Search team, counsel was able to get at their specific goals for early assessment including:Further targeting key data types crucial to the response.Identify potential custodians who were not yet formally in scope.This proactive, AI-driven exploration eliminated the need for weeks of manual attorney review typically required for initial fact-finding. Based on feedback from counsel, Lighthouse determined that one IQ Answers query and response saved 15-20 hours of review time. Thus, the use of IQ Answers allowed outside counsel to realize a savings of more than $400K in the initial case assessment phase.IQ Issues + Summarization: QC and Second-Level EfficiencyOnce the initial culling processes reduced the document population to 47K documents for review, IQ Issues was used as a Quality Control (QC) measure against first-level reviewers.QC Validation: Lighthouse provided a 200-document sample for counsel’s issue coding and generated AI issue codes for the same set. The results showed a remarkable 90% alignment for Responsive documents, significantly exceeding the typical target of 80% alignment. Because of this high precision, the typical second round of sampling was deemed unnecessary.Custom Enhancement: The case team requested a more robust output for second-level review—a comprehensive document summary and key language excerpts to support the issue codes. Leveraging close client collaboration and responsiveness, the Lighthouse team designed a custom solution on an accelerated timeline that added:A full Document SummaryKey Language Excerpts tied directly to the relevant issues.This customized approach was applied to 38K+ documents in the review corpus, and improved the efficiency of the second-level review by an estimated 38%, resulting in an estimated savings of $300K. On top of this, since alignment between the case team and IQ Issues was so high, it’s reasonable to believe these issue codes could eliminate the need for first-level review entirely, which could result in an additional savings of $45K, if not more depending on review volume.Custom Data Engineering for Modern Collaboration DataReceiving proprietary collaboration data in non-standard CSV exports rendered these data types incompatible with typical processing tools. To overcome this, the Lighthouse Innovation Data Engineering team developed a custom, defensible chat processing workflow to handle proprietary CSV exports.The engineered workflow consolidated, cleaned, and structured the data into 24-hour conversational transcripts while embedding attachments and preserving all necessary metadata. This process allowed the complex, non-standard chat data to be transformed into defensible, review-ready datasets, overcoming a significant roadblock that would have stalled the matter for weeks. As an added benefit, this new workflow is now a reusable framework for future custom conversational exports.The Result: Proactive Defensibility and Accelerated ReviewBy combining an array of LighthouseIQ modules with custom data engineering, the corporate team was delivered proactive, high-confidence results:The strategic use of IQ Answers for early fact-finding allowed counsel to anticipate regulatory needs and prepare for potential scope expansion, resulting in $400K+ in savings and a crucial head start.The deployment of IQ Issues provided a high degree of confidence and quality control over the first-level reviewers, evidenced by the 90% alignment score. Moving forward, based on this high alignment, first-level review could be completely eliminated, resulting in $45K in savings.The quickly developed custom summarization solution reduced second-level review time by over a third, resulting in an estimated savings of $300K.The innovative custom chat processing workflow successfully unlocked previously incompatible data sources, turning a complex data roadblock into a defensible, reusable, and review-ready asset.The partnership ensured both the in-house team and their law firm maintained control over the data investigation, allowing them to approach the FTC with confidence and a clear, defensible response.

The Challenge An attorney reviewing an important Gmail message notices that even though the message was sent two years ago, one of the linked attachments was modified just a couple of months ago. How long after the message was sent did the referenced file change? What exactly was altered, and does it have any bearing on her client’s case? Does the version in hand still have meaningful probative value? The e-discovery industry has grappled with “modern attachments”—items that present only as a reference or link to content stored outside the email system—for quite some time. Some are generally static: photographs, training videos, AI-generated images, PDF files, ZIP containers. Others are purpose-built for collaboration, with multiple users contributing content over time, leaving comments, and resolving tasks. Collection, review, and production of this dynamic information can be a moving target. Our Study We set out to gather empirical evidence to evaluate the true scope of the situation. Although this topic has many layers—each with important and often subjective legal implications—we focused narrowly on two questions: What is the ratio of non-editable modern attachments to those that are inherently dynamic and collaborative? In other words, how many of these linked items actually have the ability to evolve in place over time? Of the editable modern attachments, what is the frequency and prevalence of modification after a communication containing the link has been sent? Helpful Metadata The following data elements can be acquired or computed using output from Google Vault and a variety of other acquisition toolkits. Gmail Sent Date/Time: the UTC timestamp of when the message was delivered to Google’s cloud servers for routing to recipients. GDrive Modified Date/Time: the UTC timestamp of the most recent modification to the hyperlinked Google Drive item at the time of collection. The collection event may have taken place hours, days, or many years after the original communication. A change in the Modified Date of an editable linked item after the communication was transmitted is the marker of post-transmittal modification for the purposes of this study.GDrive Item Type: to separate static GDrive items from editable ones, we built an inventory of document types considered collaborative and editable for the purposes of the study. A JPEG is an image unlikely to be edited over time; a Google Sheets file may remain static but also welcomes in-place edits throughout its life. Gmail Age at Collection (Days): the number of days elapsed between when the Gmail message was sent and when the collection event took place. To allow sufficient time for hyperlinked items to potentially undergo modification, we excluded messages where this figure was less than 180 days (approximately six months). This threshold is adjustable for future studies. Findings Using 19 data sets spanning industries and organization sizes, we examined 271,145 hyperlinks to GDrive items from within Gmail messages. Of those, 150,321 links (55%) pointed to items considered collaborative and editable in place, while the remaining 45% pointed to typically non-editable binary files such as images and video. Of the editable corpus, 90,574—60%—were modified in some manner after the Gmail message was sent and prior to the collection event. Caveat Emptor The primary limiting factor in this study is the reliance on the Modified Date of hyperlinked GDrive items as the barometer for substantive change to document content. In Google Workspace, this metadata field is more volatile than it is on a Windows-centric file system such as NTFS or FAT. Simply opening a Google Doc and pressing the space bar causes the item to auto-save and update the Modified Date. Other triggering actions include making or editing comments, resolving comments, updating permissions, and renaming the file. We recognize this is an imperfect metric for evaluating substantive content changes. Due to the volatility of the Modified Date, our tally of modified items necessarily overstates the true frequency of post-transmittal content modification. A second compounding factor: Google Vault follows links anywhere in a Gmail thread, including replied-to body text and forwarded content buried months or years deep. A link from an old message in a long thread gets re-collected at acquisition time, giving it more calendar time to accumulate Modified Date changes without any actual content alteration. This also causes our post-transmittal modification tally to be overstated. Additional Parameters and Implications At the time of publication, Google Vault does not include hyperlinked GDrive items from other potential sources within the Google ecosystem, such as Calendar, GChat, or other Google Docs files. The source data for this initial study therefore focused only on Gmail. It remains unclear whether the type of communication providing the links has a material effect on the resulting metrics. Improvements for Future Studies Google Drive Audit Log—sample events for a Google DocFuture studies should seek to move beyond reliance on GDrive Modified Dates as indicators of substantive content modification. Hash values offer little additional help: the server-side hash values provided by Vault include the Modified Date in the hash computation, further reducing visibility. The following data points and workflows may prove useful: Number of post-transmittal revisions. Fifty subsequent revisions over three months may suggest substantive change; five revisions very soon after transmission may indicate noise such as comment resolution. Number of different contributors. If ten different accounts made post-transmittal changes, this may indicate meaningful collaborative activity, as opposed to a single actor refining a draft. File size. Generally unreliable except for drastic changes—for example, an item that grew from 24KB to 240KB—and even then the change could be entirely attributable to commenting activity. Acquisition of all versions of each hyperlinked item. This would yield a rich dataset but is impractical for most routine e-discovery collections due to data volume, time, and cost. AI may be able to assist with evaluating content changes across versions if provided a thoughtful prompt. Expansion of source communication types. This study focused on Gmail, but many other sources warrant consideration: Google Calendar and Groups, GChat and in-meeting messaging, Slack channels and direct messages, text messages, WhatsApp, Telegram, Discord, Signal, and others. Google Drive Audit Log. The audit log may provide the clearest window into whether a document’s content—as distinct from its metadata, comments, or permissions—was actually changed. It records events with enough granularity to distinguish views, comments, renames, permission changes, and true edits. Filtering to “edit” events alone would be a meaningful improvement over relying on Modified Date. Key challenges include: Default log retention of only six months, though events can be ported continuously to SIEM systems such as Google Security Operations or Splunk. Potentially tens of thousands of entries per GDrive item, requiring targeted filtering at collection time. High-level tenant access requirements, particularly for pulling data via the Reports API and/or Drive Activity API. Unavailability of equivalent log data for personal Google accounts not part of a Workspace tenant. Final Thoughts The data points leveraged in this initial study are admittedly imperfect, but more precise metrics are coming within reach as our industry’s tools and collective knowledge about collaboration platforms improve. We hope this inaugural research leads to further discoveries that better inform discovery practitioners and the courts. Tools & Further Reading Lighthouse’s Linked Files Solution for Google Workspace Lighthouse’s Modern Data SolutionsCraig Ball, “A Dog and Its Tail: Don’t Let Version Uncertainty Cloud Linked Attachment Production”Metaspike’s Forensic Email Collector‍

ChallengeWhen a whistleblower allegation placed a company’s future in question, outside counsel needed answers immediately. Executives had to determine whether the allegations were credible, whether fraud or criminal exposure existed, and whether the business could continue operating—all within days.The investigation involved more than 126,000 documents spanning email, collaboration platforms, messaging applications, and business records. A traditional review would have required weeks before attorneys could begin developing meaningful legal strategy.With critical business decisions on the line, an Am Law 50 firm partnered with Lighthouse to rapidly identify the evidence that mattered most while maintaining a defensible investigative process.SolutionUsing IQ Case Strategy, Lighthouse and outside counsel replaced the traditional review-first approach with a question-first investigative methodology.Rather than reviewing every document equally, counsel first identified the legal and factual questions that would determine the outcome of the investigation. Lighthouse then transformed those questions into a structured investigative workflow that rapidly surfaced the evidence most relevant to each issue.Approximately 150 targeted investigative questions guided the analysis across more than 126,000 documents, including email, WhatsApp, Signal, Discord, ChatGPT conversations, and other business records.As the investigation progressed, Lighthouse continuously identified, organized, and synthesized the most relevant evidence while attorneys refined investigative priorities and validated findings. Instead of spending weeks reviewing low-value material, counsel could immediately focus on the documents that informed legal strategy and business decisions.IQ Case Strategy delivered a comprehensive merits assessment that included:Executive summary of key findings, risks, and unresolved questionsPrioritized hot documents supporting and challenging each allegationIssue-based evidence summaries with integrated chronologiesStructured evaluation of competing factual theoriesDocument-level investigative coding and supporting data indexThe result was more than a streamlined document review—it was an evidence-based strategic assessment that enabled counsel to quickly evaluate risk, advise leadership, and determine the appropriate path forward.ImpactThe investigation produced meaningful business results in less than three days.Completed the investigation in under 72 hoursReduced 126,000 documents to approximately 1,100 critical recordsGenerated more than $335,000 in estimated cost savings compared to traditional review methodsEnabled counsel to rapidly assess the credibility of the allegations, potential fraud, criminal exposure, and operational riskEquipped executive leadership with evidence-based guidance to make critical business decisions within days rather than weeksThe Lighthouse DifferenceHigh-stakes investigations demand more than faster document review—they demand earlier insight, stronger strategy, and defensible outcomes.IQ Case Strategy combines AI-powered analysis with the expertise of legal strategists, investigators, and technologists to transform complex legal questions into actionable intelligence. By identifying the evidence that matters most at the outset of an investigation, legal teams can assess risk sooner, test legal theories more effectively, and provide business leaders with the confidence to make informed decisions.Whether responding to whistleblower allegations, regulatory inquiries, internal investigations, or complex disputes, Lighthouse helps organizations reduce review time and cost while accelerating the path from information to insight.When every decision matters, IQ Case Strategy empowers legal teams to move beyond document review and deliver what clients need most: actionable intelligence that drives confident, strategic decisions.

The Challenge A national healthcare provider faced 14 related matters across 9 jurisdictions, with 11M documents dispersed across multiple vendors, databases, and case teams.Redundant Review Is a Data Problem, Not a Legal OneWith a traditional eDiscovery model, each matter would have required reprocessing, rehosting, and/or rereviewing large portions of the same data. Data insights and work product would be siloed inside individual matters and within disparate legal teams. This would severely escalate costs and drive inconsistent outcomes and operational drag.The SolutionLighthouse recognized that the problem wasn’t just data volume. It was the absence of a system that could learn across matters and apply that intelligence forward. With LighthouseIQ, counsel could take a fundamentally different approach—using a centralized, AI-backed data system guided by expert judgment, where decisions, insights, and work product flow seamlessly between matters and legal teams.AI-Backed ResultsReduced 11M documents to 90K requiring reviewReused 100K coding decisions across 14 related mattersAvoided duplicate hosting, processing, and review of 1.2M documentsEnabled instant productions from a national database with LighthouseIQ$650K in cost savings delivered with consistency and defensibility built in, not traded offBuilding Human-Guided AI at Multidistrict ScaleStep 1: An AI-Powered Data Repository, Expertly DesignedLighthouse migrated all 11M documents (from both Relativity and non-Relativity sources) into a single LighthouseIQ hosting environment. Lighthouse experts designed the repository architecture upfront to support cross-matter reuse and long-term litigation strategy.Lighthouse eliminated duplicate hosting, processing, and review of 1.2M documents.Step 2: AI Normalization and Cross-Matter MatchingWithin the repository, LighthouseIQ normalized documents and applied proprietary hashing to identify duplicates, near-duplicates, and previously reviewed content across matters. Lighthouse experts validated how matches and inherited decisions were applied, ensuring accuracy, consistency, and defensibility across jurisdictions.Lighthouse reused 100K coding decisions across matters.Step 3: AI-Guided Prioritization, Expert Review StrategyLighthouse review experts designed one strategic review plan for all 14 matters that lowered costs and maximized data reuse and cross-matter insights. Using cross-matter intelligence, IQ Review identified 150K documents (from within the 11M housed in the repository) that were most likely to be responsive across jurisdictions.This dataset was published to the national review database and fully reviewed by an experienced Lighthouse review team (trained by Lighthouse review managers) to categorize each document for both national and jurisdictional responsiveness. After review, Lighthouse copied this strategic production set to each jurisdictional database. This approach kept hosting costs drastically lower for each individual matter, while providing all local case teams with an immediate first production, well ahead of production deadlines.Out of 11M documents, just 90K required human review.Step 4: Continuous Learning Through a Human-in-the-Loop Feedback CycleAfter production, expert-approved coding decisions were fed back into the repository. LighthouseIQ automatically matched those decisions to corresponding documents across matters, creating immediate efficiencies while preserving expert intent. With every matter, the system became: more informed, more consistent, more cost-effective.‍The Results: A System That Gets Smarter Over TimeBy using LighthouseIQ, a sprawling, multidistrict litigation environment was transformed into a reusable intelligence system. The client achieved significant cost savings and faster productions, without sacrificing judgment, consistency, or defensibility.In the process, LighthouseIQ delivered $650K in cost savings.

The ClientThe client operates at the forefront of AI innovation while simultaneously navigating heightened regulatory oversight and increasingly complex civil litigation.The Legal ChallengeOver the past two years, this client has faced a sharp increase in high-profile, high-stakes litigation and regulatory investigations. Matters often involve novel technologies, modern collaboration and messaging platforms, and compressed response timelines.This was creating sustained pressure on traditional eDiscovery models and legacy discovery tools, which proved to be inefficient and difficult to scale at the speed required. Repeated data recollection, redundant review, and inconsistent issue identification also introduced unnecessary costs and risks. The client needed an approach that could apply intelligence across matters, learn from prior work, and deliver defensible results quickly.The Lighthouse SolutionWe implemented a LighthouseIQ-driven eDiscovery program capable of scaling across the client’s litigation and investigative portfolio, prioritizing the client’s need for speed, consistency, and defensibility. Through the rapid design and deployment of this framework, Lighthouse has helped the client:Meet aggressive discovery and regulatory obligationsReduce eDiscovery risk across multiple concurrent mattersSave hundreds of thousands of dollars in just a few monthsMaintain consistency, defensibility, and institutional knowledge across a growing litigation portfolioAs new matters arise, the program continues to scale, leveraging prior AI-driven insights rather than restarting the discovery process with each engagement.Pillars of the LighthouseIQ eDiscovery ProgramIn 2024, Lighthouse launched a programmatic eDiscovery initiative for this client that was grounded in what would become the LighthouseIQ platform and application suite. The objective was to move beyond point solutions and instead create an adaptive framework that continuously improves as new matters arise. The pillars of this framework and the results achieved in just the first year are below.Reusing Work Product at Scale with LLM-Backed TechnologyLighthouse built a centralized data repository designed specifically to support work product reuse across litigation. Each matter is maintained in its own siloed workspace, where LighthouseIQ is used to:Identify when prior work product is relevant to new mattersReuse review decisions, key documents, and privilege determinationsControl reuse across matters while maintaining strict, matter-level silos for privilege and confidentialityThe result:Reduced unnecessary recollection and reprocessing across litigation by over 10 terabytesSaved tens of thousands of dollars by minimizing duplicative attorney review while improving cross-matter consistencyAccelerating Fact Development Under Regulatory DeadlinesThe impact of LighthouseIQ has also been pronounced in matters requiring rapid issue and document identification under regulatory pressure. In a recent regulatory inquiry, outside counsel had only days to identify critical facts from hundreds of thousands of documents. This timeline would have been impossible to achieve using traditional search and review technology.Lighthouse deployed IQ Case Strategy to:Rapidly analyze hundreds of thousands of documentsSurface the key documents tied to three core legal issuesPrioritize results for attorney review within daysThe result:Reduced review costs by more than $100,000Completed the regulatory response within two weeksDelivered the documents attorneys needed within days (vs. the months it would have taken with traditional search tools), giving them more time to work on data-backed legal analysisBuilding a Defensible Forensics FoundationLighthouse also designed and implemented a centralized forensics collection program spanning all of the client’s major data sources, including:Google Vault and Google DriveSlackMobile devicesNon-standard messaging and social applicationsThe forensic program addressed nuanced challenges that arise in modern data environments, including the preservation, collection, and treatment of hyperlinked attachments, particularly where contemporaneous versions are unavailable. Lighthouse’s forensic team improved collection efficiency and defensibility by:Developing a core forensics playbook to standardize data retrieval across mattersDesigning targeted collection workflows that leverage usage and access patterns to prioritize files actually accessed by custodians, significantly reducing over-collectionThe result:Improved collection consistency across matters while minimizing unnecessary data processing and review via a repeatable forensic program

Background Regulators issued a sweeping investigation tied to a global company’s high-profile acquisition. The scope and timeline were demanding: more than 30TB of data required analysis, risk assessment, and production in less than 30 days. A defensible, scalable approach that met regulatory requirements while controlling cost, mitigating risk, and ensuring flawless execution was non-negotiable. The Lighthouse Approach LighthouseIQ eliminated unnecessary human review, decreased scope early, surfaced risk faster, and executed at scale without errors. Key elements included: IQ Review used AI to surface only what truly required human judgement. In parallel, a 300-person managed review team was rapidly ramped to handle the doc volume. IQ Priv accelerated privilege identification and used generative AI for privilege log drafting and names list creation. Key documents identified via modeling in parallel to review. Cross-matter analytics and work-product reuse across a parallel antitrust litigation Custom operational workflows, including M365 cloud attachment linking and secure reuse repositories All of it executed in parallel. No bottlenecks. No rework. Results 10TB, including 20M images were produced with M365 cloud attachments as required by regulators in under 60 days. This delivery boasted an 100% error-free production result and $20M in total cost savings. Cost avoided:

When an engineering partner suddenly pulled out of a major project, a global manufacturer needed answers fast. Was the termination allowed under the contract, or had the partner crossed a line that could lead to litigation? The company’s law firm had to move quickly. A deadline was approaching to file a termination claim, but that was only the first step. Once the partner responded, the firm expected tough follow-up discovery. To be ready, they needed to understand the full story before the dispute escalated. The firm identified and collected more than one million documents across fifteen custodians, most in the United States. While this is a large but not uncommon volume of data for such a complex investigation, the real challenge was determining how to interrogate it quickly without iterating dozens of times on keywords as is the case with traditional keyword search. As one attorney explained, “Most of the time, we don’t know the exact words people used and everyone uses different language anyway.” Every guess costs time, and every missed variation risks overlooking critical evidence. The Lighthouse ApproachLooking for a faster and more reliable approach, the firm used IQ Answers directly inside their Relativity environment, starting with Microsoft 365 data from the U.S. custodians. IQ Answers is not a general-purpose chatbot. It’s an enterprise AI tool that leverages large language models and other AI and ML models to answer questions but is grounded solely in the documents in your case. Instead of building complex keyword searches, attorneys simply asked questions and received clear, document-backed answers. Using this approach, the team conducted an early case assessment without relying on months of manual review. Once all documents were loaded, they used the AI to explore the data directly. Over the course of less than two months, the team asked 182 natural-language questions. That process captured 6,325 documents, of which the team flagged 835 as potentially important. To confirm the results, the firm conducted a second-level manual review of those documents. Attorneys validated 190 documents as key evidence and identified another 130 as potentially key. Notably, 832 of the 835 documents directly related to the 14 issues identified for the case. By combining AI-driven discovery with focused human review, the team turned an overwhelming volume of data into clear, actionable insight—delivering results in a fraction of the time required by traditional methods. Based on the intelligence IQ Answers delivered, the firm made a critical strategic decision: they opted against a full review. What would have been months of traditional document review and significant expense became a targeted, AI-driven investigation that gave them exactly what they needed in pre-litigation.

BackgroundThe client faced a high-stakes Hart Scott Rodino (HSR) Second Request with tight compliance deadlines under FTC oversight:7.5M documents (7.8TB) were collected in 2 phases from 28 custodians collected across email, collaboration platforms, mobile data, and hard copy sources.Differentiated responsiveness standards between groups of custodians, requiring tailored review strategies.The matter was re-opened months later and additional documents requested.The Lighthouse ApproachThe team implemented both IQ Review and IQ Priv, combining AI analysis with disciplined managed review execution. Key elements included: AI-supported relevance review and a team of 30 contract attorneys for documents that required eyes-on review Privilege review, privilege log and names legend automation via AIAI image analysis for visual and scanned contentTwo separate AI models were trained to address differing responsiveness criteria across custodial groups, ensuring precision without sacrificing defensibility.ResultsLighthouse successfully processed 7.5M total documents across both collections. Because our AI models remain largely stable even with new documents, analysis of the second phase of collection was able to start immediately. LighthouseIQ powered analysis meant that only 2,500 contract review hours were needed in total. Using AI insights, our contract review attorneys maintained high review velocity across responsiveness, privilege, and PII review streams. The approach delivered FTC-ready defensibility under close regulatory scrutiny while enabling rapid adaptation to an evolving regulatory scope. Through expert coordination across legal, technical, and review teams, the engagement delivered predictable, consistent performance even under compressed timelines and shifting requirements.

Key Events and OutcomesClient initiated an internal investigation into executive misconduct, requiring high-precision document discovery and behavioral analysis.Multiple search workstreams delivered thematic overviews, interview prep kits, and targeted behavioral evidence.Lighthouse search experts across multiple time zones gave the case team access to support whenever priorities shifted.Lighthouse delivered 160 total key documents over four days in three deliveries to accelerate the time to knowledge and minimize the risk of missing critical evidence.Counsel prepared more strategic witness interviews using behavioral evidence and operational insights surfaced by IQ Answers and Lighthouse search experts.What Was NeededA large retailer launched an internal investigation after receiving whistleblower allegations of misconduct. The project required rapid, high-precision document discovery and behavioral analysis across a substantial volume of internal communications. The client needed thematic overviews of key communications, curated document sets to support interview preparation, and targeted behavioral insights to inform legal and internal review. All work had to be completed within a single week to enable critical witness interviews and support preparation of a summary report for outside counsel.ProcessThe first step in triaging the needs related to the matter involved outside counsel conducting initial research using IQ Answers. This early facts assessment confirmed that the central concerns of the investigation were reflected in the data, and helped refine the goals and targets for a hand-off to the Lighthouse expert search team.Leveraging insights from counsel’s initial use of IQ Answers, the expert search team used advanced techniques developed within Lighthouse’s proprietary systems to support Key Document Identification workflows. These methods, combined with tagging and document filtering workflows for compliance and legal review, targeted queries of linguistic patterns, indicators of tone and behavior, and other expressions of language.In parallel, IQ Answers powered conceptual and semantic queries, surfacing nuanced patterns and sentiment indicators across a voluminous set of 300,000 documents. The combined technology and workflow approach allowed Lighthouse's expert search team to precisely identify the documents of highest importance and potential impact for the investigative team. Volume-reduction methodologies were applied to isolate the most likely relevant, non-duplicative content. Linguistic and behavioral searches focused on topics prioritized by counsel, with results delivered on a rolling basis to support interview preparation and legal review.Throughout the project, Lighthouse's expert search team worked in close coordination with the matter team, leaning on global coverage to provide seamless support and incorporating feedback into iterative search cycles.Expert Search ResultsLighthouse's expert search team delivered three waves of curated document sets totaling approximately 160 records, each tagged with topics and annotation fields to support rapid review. This enabled highly targeted interview preparation by surfacing behavioral indicators, communication patterns, and operational insights relevant to the investigation. The outputs integrated into client workflows, including saved searches and coding layouts within the review platform.By combining multiple information retrieval, analysis, and synthesis technologies and augmenting with human expertise, the team surfaced unique documents responsive to similar lines of inquiry—providing broader and more comprehensive information coverage in a shorter time frame than any single approach could have achieved alone.

A global consumer products company with a distributed workforce needed to strengthen its information security posture. With sensitive intellectual property, regulatory obligations across multiple jurisdictions, and increasing use of Microsoft 365 collaboration tools, the security team sought a more resilient approach to protecting critical data against leakage, misuse, or unauthorized access. Challenge The existing environment lacked unified policies for sensitivity labeling, retention, and data loss prevention, making it difficult to enforce consistent governance across all business units. The client faced significant risks around: Data leakage from collaboration data in Microsoft Teams, SharePoint, and OneDrive. Lack of consistent data classification leading to overexposed sensitive content. Insufficient DLP controls for email and cloud-based sharing, creating regulatory and reputational risks. Growing compliance pressure across global operations, requiring alignment with GDPR, CCPA, and industry-specific regulations. Solution Lighthouse partnered with the client to design a comprehensive Microsoft Purview Information Protection and Data Loss Prevention (DLP) framework pilot that could scale globally. The solution included: This design provided the foundation for both proactive risk reduction and reactive incident handling. Results Through this engagement, the client achieved: Reduced risk of data exposure by applying consistent labeling and DLP rules across collaboration platforms. Improved regulatory compliance by aligning information protection policies with global privacy and industry frameworks. Enhanced incident visibility with reporting dashboards and adaptive policies that alerted security teams to high-risk events. Sustainable governance model enabling scalability as new collaboration tools and AI-driven workflows are adopted. Why It Matters As global enterprises accelerate digital collaboration, data security gaps in Microsoft 365 environments can create regulatory, financial, and reputational risk. By implementing a comprehensive governance and DLP framework, organizations can protect their most valuable assets: intellectual property, customer data, and regulated records, while enabling employees to work securely across borders. This project highlights how a well-designed information protection program, supported by Microsoft Purview, can simultaneously strengthen security and simplify compliance for multinational companies.

The ChallengeA major media company received a Letter of Inquiry (LOI) from the FCC, triggering a high-stakes regulatory investigation. The company was required to produce relevant communications within a month—but two weeks in, the legal team still needed to collect over 2 million documents from 16 custodians. Complicating matters further, the company’s software platform was mid-transition, raising serious concerns about data integrity and reporting reliability. The SolutionRecognizing the urgency and complexity of the matter, the media company and its outside counsel turned to Lighthouse. With an immense volume of documents, looming regulatory deadlines, and a technology transition in progress, they needed more than linear review—they needed a strategic partner with forensic, eDiscovery project management, and AI expertise. Within just four days, Lighthouse’s forensics experts collaborated with the company to collect and process all relevant custodian data, including associated family files. From there, our project management team worked with the company and its counsel to apply targeted filtering—focusing on communications between key senders and recipients. This reduced the original 2 million documents to a refined universe of 94,000. Using advanced email threading and junk file analysis, the team further reduced the review set to 59,000 documents. Given the aggressive timeline, volume of documents, and the dataset’s low privilege risk, Lighthouse consultants recommended deploying Relativity aiR for Review. Working closely with inhouse and outside counsel, Lighthouse developed a defensible AI review prompt using an iterative sampling workflow designed to meet stringent recall standards and maximize precision. Only 300 documents were reviewed during this iterative phase. Relativity aiR identified a predicted responsive universe of 28,000 documents. A first-level review was completed in just five days, followed by a quality control review conducted by outside counsel. Final validation confirmed 88% recall and 96% precision—exceeding regulatory and eDiscovery defensibility standards. The ResultsUltimately, 18,000 documents were successfully produced on time, along with an expert declaration on the defensibility of the process from a Lighthouse Strategic Consultant. When the FCC issued a supplemental request, the teams were able to use the aiR-powered workflow once again to quickly review 2,000 additional documents—resulting in the production of the 300 relevant files.

Client: Global academic medical system Stakeholders: CISO, Information Governance, Legal Tech stack: Microsoft 365 + Microsoft Purview (SharePoint, OneDrive, Exchange, Teams) Objective: Identify, label, and protect high‑value IP across M365 Business Challenge Conventional pattern matching missed nuanced research content; labels were inconsistent. Emerging IP taxonomy lacked consistent, enforceable labels across repositories. Conventional pattern matching couldn’t reliably detect unstructured, nuanced IP. Teams needed clarity on when to use Sensitive Info Types (SITs), Exact Data Match (EDM), and Trainable Classifiers, and how to govern them. Wanted to compare outcomes with prior third‑party classifiers. What Lighthouse Did IP Taxonomy + Purview Labels Mapped proprietary IP categories to a label set Blended Classifier Strategy Combined SIT, EDM, and Trainable Classifiers Operationalize Piloted and tuned models aligned with retention/legal hold/eDiscovery, with auto‑labeling and user prompts. Controls Developed change‑management materials Outcomes Common IP Language: Agreed taxonomy mapped to enforceable labels. High‑Confidence Detection: Trainable classifiers surfaced custom IP Consistent Protection: High‑value content auto‑labeled with policy‑driven controls in M365. Governed Workflows: Clear guidance on SIT vs EDM vs Trainable; fewer false positives/negatives; faster to eDiscovery. Timeline Weeks 0–1 — Kickoff + Plan Weeks 2–4 — Design + Setup Weeks 5–9 — Run Pilots Weeks 10–11 — High Level Design + Training Why Microsoft Purview for Data Protection Enterprise-wide strategy - Unified data security, governance, compliance Integrated governance - DLP, retention, legal hold, eDiscovery Flexible detection models - Sensitive Info Types, Exact Data Match, Trainable Classifiers Persistent, label-based protection - Embedded permissions travel with data

During the first trial of a high-stakes, serialized product liability case, a legal team was stunned when opposing counsel introduced damaging documents that had originated from the client’s own production. Despite months of review by both in-house and outside counsel, these documents had slipped through the cracks—threatening to derail the case and set a dangerous precedent for future litigation.With millions at stake, they needed a solution—and fast. They turned to Lighthouse. In just three days, a Lighthouse expert dug into the 25,000 documents in the production, uncovering 14 crucial rebuttal documents that counsel used at trial to challenge the plaintiffs’ claims.This swift, targeted response set the client up for success and in a position to save the company millions of dollars in judgments and protect them from similar challenges in upcoming cases.In the world of serialized product liability litigation, where one case can impact many others, the power of rapid, focused eDiscovery can be the difference between a costly loss and a decisive win.

SolutionThe Director of Information Security partnered with Lighthouse to conduct a comprehensive scan using Lighthouse’s proprietary environment scan technology and Microsoft Information Protection (MIP). This scan could locate sensitive data across the enterprise and provide the necessary visibility to roll out full MIP policies.1. Lighthouse’s Comprehensive Environment Scan Lighthouse’s scan helped identify and locate sensitive data, helping the security team to understand its exposure and design its protection strategy. An example of findings included:Teams: /LegacyRightAngleData contained 139,000+ instances of sensitive data. SharePoint: /Financial_DMS stored 52,000+ instances of sensitive data. OneDrive: /[single employee] held 18,900+ instances of sensitive data. Most Common Sensitive Data TypesABA Routing NumbersEU Passports NumbersSWIFT CodesU.K. National Health identifiers2. Created Sensitivity Labels in Pilot Mode Following the scan, Lighthouse supported the security team in developing sensitivity labels in pilot phase, including: Testing Auto-Labeling & Classification: Defining initial label rules based on scan results. Evaluating Impact Before Full Rollout: Assessing how sensitivity labels functioned across departments and workflows.Preparing for Future Policy Implementation: Establishing a structured data protection strategy before MIP policies were fully deployed. Key Outcomes The Lighthouse environment scan gave the organization critical visibility into sensitive data locations, laying the groundwork for stronger data governance, protection, and compliance. Critical Visibility for Future Protection: Identified where sensitive data resided to guide security and governance efforts. Pilot Sensitivity Labeling Program: Launched sensitivity labels to test the efficacy of policies and refine data governance practices. Foundation for MIP Rollout: Positioned the team to automate protection and enforce compliance through Microsoft Purview. The Lighthouse environment scan helped the client uncover hidden risks and build a foundation for stronger data governance. With clear visibility and a pilot labelling program, the organization is prepared to advance its Microsoft Purview rollout and reduce exposure.

The ChallengeRecently, the U.S. Department of Justice (DOJ) issued a broad and urgent HSR Second Request in connection with a high-profile merger for a large, highly-regulated corporation. The regulatory inquiry required fast, defensible data collection from a range of custodians, many of whom were senior executives. With just weeks to act, the stakes were clear: respond efficiently and thoroughly or risk delaying the transaction’s approval.The request included nearly 30 custodians spread across the U.S., many with privacy sensitivities around their mobile data.The SolutionLighthouse assembled a cross-functional team of digital forensics experts and client services professionals to lead a high-touch, high-urgency workflow. Coordination between the digital forensics project manager and client services project manager ensured that collections, handoffs, and processing moved forward without bottlenecks—driven by daily alignment and real-time communication.Over six weeks, Lighthouse collected mobile data from all 27 custodians using a mix of remote and on-site methods, all handled in-house to minimize disruption and maintain control. The team leveraged industry-standard tools and proprietary workflows to extract encrypted messaging data from apps like WhatsApp and Signal, even when on-site collection was required. To address privacy concerns, Lighthouse implemented a workflow where custodians approved contact lists before any messages were filtered and prepared for review. This approach ensured rapid turnaround—often within one business day—without compromising data integrity or custodian trust.ResultsBy strategically splitting collections between remote and on-site, the Lighthouse team accelerated the project, completing collection in just 1.5 months and saving an estimated 60 hours of work time. More importantly, the client was able to respond to the DOJ within deadline—and was armed with complete, accurate, and defensible data drawn from even the most sensitive mobile sources.

Challenges The legacy environments included approximately 2,200 repositories with structured data. IT aimed to decommission these systems to reduce costs, while Legal needed confirmation that legal holds were preserved before signing off on each system. The client also had to navigate international data privacy regulations, particularly when data consolidation meant data was moved across borders. Initially, two service providers split the responsibilities: the General Counsel’s office engaged one, and the eDiscovery department turned to Lighthouse because they had a long-term relationship. This fragmented approach introduced inefficiencies and risk.Solutions Lighthouse consultants:Liaised between Legal and IT, validating preservation plans for each repository. Built a detailed playbook, documentation standards, and a quality control process to provide consistency across the project. Conducted regular review calls with IT. Approved or rejected plans based on standards defined by Legal, ensuring retrieval capabilities, immutability, and long-term access. When the client saw our approach, they consolidated the work under Lighthouse, extended the engagement by 24 months, and rescoped the project.Wins The acquiring company: Gained a defensible, repeatable preservation process aligned with legal and regulatory obligations. Decommissioned costly legacy systems while maintaining legal hold compliance. Improved coordination between Legal and IT, expediting approvals. Mitigated regulatory risk by tracking and documenting preservation decisions. Ensured cross-border data preservation aligned with jurisdictional privacy regulations.Reduced long-term operational costs by retiring expensive platforms.Take Aways This project illustrates how cross-departmental cooperation can reduce risk and costs in post-acquisition decommissions and rationalizations. With a well-designed playbook and a team fluent in legal obligations and technical systems, the client adopted a defensible preservation strategy and unlocked long-term savings.

The project included replacing expensive third-party archives with native tools in M365, utilizing an automation solution that Lighthouse had recently prototyped for a large global manufacturer, and other breakthroughs the institution was unable to make before engaging with Lighthouse. Our work with the institution helped unblock their Microsoft 365 deployment and ultimately led to disclosure to regulators for institution’s intent to use M365 as system of record.SIFIs have long wished for a better way to meet their mutability requirement. Historically, they have relied on archiving solutions, which were designed years ago and are poorly suited for the data types and volume we have today. For years, people in the industry have been saying, “Someday we’ll be able to move away from our archives.” It wasn’t until the introduction of M365 native tools for legal and compliance that “someday” became possible.Data Management for SIFIs is Exceptionally ComplexThe financial services industry is one of the most highly regulated and litigious sectors in the world. As a result, companies tend to approach transformation gradually, adopting innovations only after technology has settled and the regulatory and legal landscape has evolved.However, the rate of change in the contemporary world has pushed many financial heavyweights into a corner: They can continue struggling with outdated, clunky, inadequate technologies, or they can embrace change and the disruption and opportunities that come with it.From an eDiscovery perspective, there are three unique challenges: (1) as a broker-dealers, they have a need to retain certain documents in accordance with specific regulatory requirements that govern the duration and manner of storage for certain regulated records, including communications (note that the manner of storage must be “immutable”). This has traditionally required the use of third-party archive solutions that has included basic e-discovery functionality. (2) As a highly regulated company with sizable investigation and litigation matters, they have a need to preserve data in connection with large volumes of matters. Traditionally, preservation was satisfied by long-term retention (coupled by immutable storage) and without deletion. Today, however, companies seek to dispose of legacy data—assuming it is expired and not under legal hold—and are eager to adopt processes and tools to help in this endeavor. (3) They have a need to collect and produce large volumes of data—sometimes in a short timeframe and without the ability to cull-in-place. This means they are challenged by native tooling that might not complete the scale and size of their operations. This particular company’s mission was clear: to use M365 as a native archive and source of data for eDiscovery purposes. To meet this mission, Lighthouse needed to establish that the platform could meet immutability and retrievability requirements—at scale and in the timeframe needed for regulatory and litigation matters. Lighthouse Helps a Large Financial Institution Leverage M365 to Replace Its Legacy Archive SolutionLighthouse is perfectly positioned to partner with financial services and insurance organizations ready to embrace change. Many on our team previously held in-house legal and technology roles at these or related organizations, including former in-house counsel, former regulators, and former heads of eDiscovery and Information Governance. Our team’s unique expertise was a major factor in earning the trust and business of a major global bank (“the Bank”). The Bank first engaged with Lighthouse in 2018, when we conducted an M365 workshop demonstrating what was possible within the platform—most notably, at the time, the potential for native tools to replace their third-party archives. Following the workshop, the Bank attempted, together with Microsoft, to find a viable solution. These efforts stalled, however, due to the complexity of the Bank’s myriad requirements. In 2020, the Bank re-engaged Lighthouse to supports its efforts to fully deploy Exchange and Teams and, in doing so, to utilize the native information governance and e-discovery toolset, paving way for the Bank to abandon its use of third-party archiving tools for M365 data. Our account team had the nuanced understanding of industry regulations, litigation and regulatory landscape, and true technical requirements needed to support a defensible deployment.As a result, we were able to drive three critical outcomes that the bank and Microsoft had not been able to on their own: (1) A solution adequate to meeting regulatory requirements (including immutability and retrievability). (2) A solution adequate to meeting the massive scale required at an institution like this. (3) A realistic implementation timeline and set of requirementsLighthouse Ushers the Bank Through Technical and Industry MilestonesWe spent six months designing and testing an M365-based solution to support recording keeping and e-discovery requirements for Teams and Exchange (including those that could support the massive scalability requirements). The results of these initial tests identified several gaps that Microsoft committed to close. The six month marked a huge milestone for the financial services industry, as the Bank disclosed to regulators their intent to use M365 as system of record. This showed extreme confidence in Lighthouse’s roadmap for the Bank, since a disclosure of this nature is an official notice and cannot be walked back easily. Over the next few months, we continued to design and test, partnering with Microsoft to create a sandbox environment where new M365 features were deployed to the Bank prior to general availability, to ensure we were able to validate adequate performance. During this time, Microsoft made a series of significant updates to extend functionality and close performance gaps to meet the Bank’s requirements. Finally, in February 2021, all the Bank’s requirements had been met and they went live with Teams—the first of their M365 workload deployments. That configuration of M365 met only some of the Bank’s need, however, so Lighthouse had to enable additional orchestration and automation on top. As it happens, we had recently done this for another company, creating a proof of concept for a reusable automation framework designed to scale eDiscovery and compliance operations within M365. Building on this work, we were able to quickly launch development of a custom automation solution for the Bank. This project is currently underway and is slated to complete in June, coinciding with their deployment of Exchange Online.Lighthouse Enables Adoption of Teams and Exchange and Scales M365 Compliance FunctionalityCompliant storage of M365 communications using native tools, rather than a third-party archive. Scaled and efficient use of M365 eDiscovery, including automation to handle preservation and collection tasks rather than manual processes or simple PowerShell scripts.Improved update monitoring, replacing an IT- and message-center-driven process with a cross-functional governance framework based on our CloudCompass M365 update monitoring and impact assessment for legal and compliance teams.Framework for compliant onboarding of new M365 communication sources like Yammer. Framework for compliant implementation of M365 in new jurisdictions, including restricted country solutions for Switzerland and Monaco. Framework to begin expanding to related use cases within M365, such as compliance and insider risk management. Lighthouse Paves the Way for Broader M365 Adoption Across the Financial Services IndustryFollowing the success of this project, we have been engaged by a dozen other large financial institutions interested in pursuing a similar roadmap. The roadblocks we removed for the Bank are shared across the sector, so the project was carefully watched. With the Bank’s goals confidently achieved and even surpassed, its peers are ready to begin their own journey to sunset their archives and embrace the opportunities of native legal and compliance tools in M365.

Firms Needed Fast Analysis of 25M Documents More than a dozen international law firms—including a Joint Defense Group (JDG) of 11 firms and several firms representing defendants outside the JDG—were engaged in a complex cluster of cases spanning over 30 US jurisdictions. The total document tranche included over 25M documents. The firms needed to find and understand the key players, timelines, and nuances involved in each litigation, while also preparing for hundreds of depositions, witness interviews, hearings, and trials scheduled across the litigation universe. However, traditional approaches to fact-finding and litigation (i.e., document review, keyword searches, etc.) were drowning case teams in extraneous and duplicative information. They came to Lighthouse looking for a strategic, unified approach to fact-finding, led by experts who could deliver the key documents, information, and details the case teams needed—and nothing more. Custom Workflows Power Consistency, Speed, and Efficiency Our experts started by creating a topic map across matters, which helped them quickly provide case teams with the core themes in each jurisdiction while reducing redundant search work. From there, as case strategy for each matter developed, the Lighthouse team drilled down into more nuanced fact-finding to help surface the documents case teams needed to learn the key details of each matter, through strategies like: State/Jurisdictional Overview Workflow – We used advanced search technology to target key documents in incoming productions and categorize them by jurisdiction, providing case teams with an immediate thematic overview of key facts and timelines. Re-Deployable Linguistic Model Workflow – Lighthouse linguists developed models based on intimate knowledge of the language used within the datasets, then deployed them within proprietary search technology to sort documents into tiers based on the likelihood that they contained key information. Deposition Kit Bundle Workflow – By bundling deposition kit requests from the same jurisdictions and departments together, we could search across smaller collections of documents and take a deponent-agnostic approach. Previously Delivered Name Hit Workflow – We provided case teams with documents from previously delivered results, giving them an advanced start on deposition preparation while further reducing duplicative searching. These repeatable workflows significantly reduced the volume of searching and coordination required across matters and enabled Lighthouse experts to quickly zero-in on the exact documents needed—without wasting counsels’ time with redundant and unimportant documents. Critical Docs Found and Delivered Across Dozens of Matters and Hundreds of Kits Over the course of two years, Lighthouse experts prepared dozens of case teams for complex litigation and handled a deluge of competing deadlines, priorities, and ad hoc requests (totaling as many as 70 requests at a time). For the Joint Defense Group, this meant: Over 1,150 deposition kits across 24 matters, encompassing 245K unique documents Over 100 state overviews across 21 different jurisdictions, encompassing 80K documents For law firms representing individual defendants, Lighthouse provided an additional:150 deposition kits, encompassing 13K documents 30 defensive overviews across 20 jurisdictions, encompassing 6K documents 1.3K documents in response to ad hoc requests and trial support Each delivery was limited to essential information—including key themes and players in every jurisdiction, potential gaps in productions, lists of hot/sensitive documents and potential deponents, and key strategy documents—and avoided redundant and unimportant documents. The combination of innovative workflows and cutting-edge technology enabled Lighthouse to keep our team small and consistent throughout the engagement, so the entire effort was achieved by a handful of Lighthouse experts with institutional knowledge of every matter. Since this engagement, we have used the same workflows for other clients facing complex Multidistrict Litigation (MDL)—making Lighthouse key document identification one of the most valuable and scalable litigation technology solutions on the market today.

The Lighthouse team of SMEs applied their dedication to exemplary customer experience and unique strategy of marrying compliance, security, IT, and legal needs to help a global chemistry solutions and specialty material producer meet the ever-evolving security and compliance demands and challenges facing international manufacturing and regulations to effectively deploy Microsoft Purview across workstreams while preparing for needs and reducing costs. Global Leader in Chemistry Solutions Transforms Enterprise Data Protection with Microsoft Purview An international producer of commercial chemicals and specialty materials upholds a commitment to people safety and well-being as part of their core tenets. As cyber risks increased along with data volumes, the organization extended their commitment to safety to include the security of data accessed, produced, and stored within their enterprise. Now, the company has implemented a comprehensive data protection program using the entire Microsoft 365 Information Protection suite. After careful design, the team is piloting the solution before a global rollout. A Commitment to Physical and Digital Safety As one of the world’s largest acetyl products manufacturers and a top-tier producer of high-performance engineered polymers, the company supplies chemicals across major industries and for a variety of industrial and consumer applications. Over 10,000 employees in offices, technical centers, and 50+ manufacturing facilities work to realize a vision of improving the world and everyday life through people, chemistry, and innovation—with products that impact the lives of millions. For the organization, an operational approach rooted in well-being has always meant physically safe working environments for employees, and safe solutions for their customers and their communities. However, in this digital age, they have expanded their notion of safety to include data protection for employees, customers, shareholders, and the communities in which they operate. The company’s Chief Information Security Officer (CISO) notes that committing to data protection means a “higher level of assurance—making sure that our security controls keep pace with the threats that surround us every day and seek to exploit vulnerabilities in companies like us every day. You can’t stand still. You always have to evolve—you always have to get better, otherwise you’re devolving, and you’re getting worse, and becoming more vulnerable.” Advancing Data Protection with a Trusted Partner A few years ago, when the company decided to make the move to the cloud, they chose Microsoft 365 E5 and Microsoft Azure, building on their longstanding use of Microsoft technologies. Prior efforts to overhaul their data protection program had been unsatisfactory. However, with access to new Microsoft Purview capabilities, the Information Security team saw an opportunity to try again. They hoped to utilize the full breadth of the Microsoft 365 Information Protection suite including Information Protection Classification and Labeling, Data Loss Prevention (DLP), and Insider Risk Management solutions. Microsoft tapped Security Solutions and Advanced Specialization Designation-Information Protection and Governance Partner Lighthouse Global to lead the engagement for their ability to effectively understand complex compliance needs across IT, security, and legal departments. They hoped that together they could develop a solution to realize the investment they’d made in Microsoft 365, and to support their corporate commitment to safety for both employees and customers. “If you were to interview a bunch of companies, those who have actual, very successful DLP and data labeling programs typically have a hodgepodge of solutions that get melded together,” reflected the CISO, “and that’s where Lighthouse was successful…we’ve been able to leverage the investment…and get it to work, [and not] have to go spend more money to hodgepodge together a solution.” Developing a Comprehensive, Scalable Solution The Lighthouse team started by holding a series of working sessions to align the company’s vision and requirements and design the implementation approach. Using Microsoft Compliance Check, Lighthouse scanned the company’s environment to get an understanding of current state activity and sensitivity intelligence. The team also reviewed existing policies and approaches for the handling of sensitive data and data loss prevention to identify any areas of opportunity or gaps that could exist. From there, the combined teams were able to successfully design and configure a holistic data protection solution leveraging multiple Microsoft Purview products including Data Loss Prevention, Information Protection, and Insider Risk Management. Starting with data classification, the team defined the sensitive information types that needed to be identified. From there, they developed a set of sensitivity labels corresponding to the data protection policy. This set of classification techniques and labels were generated in the course of both Data Loss Protection and Insider Risk Management implementation, ensuring a comprehensive data life cycle protection program from content identification through insider threat analysis. Finally, the Lighthouse team supported the integration of the Microsoft products with the company’s third-party HR software to feed HR data into the Data Theft by Departing Employee Policy, enabling the creation of a truly end-to-end solution. Fulfilling a Mission of Security The company’s dedication to safety, security, and well-being across applications and contexts drove this project’s success. “Because we see security as part of our commitment to people and innovation, we take a uniquely holistic approach and have strong support all the way up to our board of directors,” says the company’s CISO. The CISO also credits Lighthouse’s unwavering commitment to partnership. “They helped us not only implement the technology and guide us through some of the critical points to consider as we implemented the technology, but also the process and decision points with data—which ultimately, in the end, actually worked,” they conclude. Now, with the design and implementation of the Microsoft Purview-based Data Protection program behind them, the organization’s information security team is focused on operationalizing the program through a series of pilots scheduled over the next year. Their ultimate goal is total, global implementation of the solution—and total, global protection for all employee and customer data. Corporate Case Studymicrosoft; big-datamicrosoft-365; data-privacy

Over the course of five months, Lighthouse delivered approximately 4,500 documents for review—out of the 2.3 million document review set—for a Fortune 100 health insurance provider. The Challenge Complex internal False Claims Act investigation 2.3M total documents for review Five-month timeline and tight budget Lighthouse Key Actions Provided curated weekly deliveries of the most important, inclusive documents for review—with no redundant or duplicative versions Compiled summary reports of each delivery (including highlights of high-priority information) to expedite counsel review Out of 2.3M documents, identified and delivered just the 4,500 documents counsel needed to review in order to conduct a comprehensive legal analysis Key Results for Counsel Immediately gained a grasp on the relevant facts and timelines hidden within a massive review set—without wasting time reviewing irrelevant information Quickly developed a deeper understanding of the underlying risks and nuances of the investigation, through consistent and iterative communication with Lighthouse search experts Confidently completed the investigation on time and within budget—even after large volumes of new data were added mid-investigation A Challenging Internal Investigation into False Claims Act Violations A Fortune 100 health insurance provider was pursuing an internal investigation involving potentially improper diagnosis practices undertaken by a wholly-owned provider group. The scope of the investigation included analysis of reimbursements processed across 20+ disease categories, potentially triggering False Claims Act violations. With 2.3M documents to review, it was unclear how the internal investigation would be completed within a constrained budget and timeline. Counsel reached out to Lighthouse for help. Lighthouse Hands Counsel the Keys to a Focused, Efficient Investigation A small team of Lighthouse information retrieval, legal, data science, and linguistic experts immediately began working with counsel to understand the specific allegations at issue, as well as catalogue the various sources of data that needed to be investigated. The team then designed and executed a battery of complex searches tailored to find instances of fraud or wrongdoing related to the allegations at hand. By staying in close communication with counsel, the Lighthouse team ensured that new search requirements and data sources were quickly integrated into the workstream to support fact development. On a weekly basis, Lighthouse delivered a streamlined set of documents responding to counsel’s evolving theory of the case. These deliveries also included a detailed breakdown of the categories of documents identified each week, descriptions of relevant internal processes and policies, and flagging of high-priority documents of particular interest to counsel. Each delivery was distilled down to only the most inclusive, non-redundant versions of relevant documents. In addition to keeping pace with ongoing requests and deliverables, the Lighthouse team also re-executed previous searches to address waves of new data rolling in midway through the engagement. A Faster and More Comprehensive Investigation Resolution Over the course of five months, Lighthouse delivered approximately 4,500 documents for review—out of the 2.3 million document review set. The Lighthouse deliveries encompassed everything counsel needed to know in order to resolve their investigation—and nothing more. The team accomplished this precision through deep subject matter expertise surrounding the allegations and underlying issues at play, consistent and effective communication with counsel, expert topic-based searching, and additional proprietary data analytics to remove unnecessary duplicative content. By the end of their short engagement with Lighthouse, counsel had developed a comprehensive understanding of the pertinent risk areas and confidently completed their investigation—on time and within budget. Corporate Case Studycase-study; corporate; corporation; ediscovery; fact-finding; document-review; investigations; kdi; key-document-identification; keyword-search; insurance-industry; analytics; ai-and-analyticsediscovery-review; ai-and-analytics; client-successCase-Study, client-success, Corporate, Corporation, eDiscovery, fact-finding, document-review, investigations, KDI, key-document-identification, keyword-search, insurance-industry, analytics, ai-and-analytics, ediscovery-review, ai-and-analytics

Lighthouse's proprietary AI technology solves a unique data deduplication challenge while migrating over 25 terabytes for an extensive healthcare system. Key Results In 5 months, Lighthouse migrated four databases—with 25 TBs of data—all while keeping the databases active for review and production for current matters. Leveraging our AI technology, Lighthouse created an innovative solution for a large volume of Lotus Notes files originally processed as HTML files by a legacy processing tool. This solution ensured that any new Lotus Notes files would deduplicate against the migrated data, regardless of the file type or the tool used for processing. A Challenging Data Deduplication Problem A large healthcare system had been hosting its data (over 25 TBs of data across four databases) on another vendor’s platform for nearly a decade. The company knew it was time to modernize its eDiscovery program with Lighthouse. In order to do so, all 25 TBs would need to be migrated over to Lighthouse for hosting and future processing. However, in addition to data migration, the company also had a unique deduplication challenge due to the previous vendor’s original processing tool. The company’s data had originally been processed with the vendor’s legacy processing tool—which processed Lotus Notes data as HTML files, rather than the more modern EML version. The prior processing of these files into an HTML format meant that whenever duplicate Lotus Notes files were added to the database and processed using a more modern processing tool, those EML files would not deduplicate against the older HTML files in the databases. With over half their data consisting of Lotus Note files processed by the older tool in HTML format, the company was concerned that this issue would significantly increase review cost and slow down review time. Thus, in addition to the overall migration process, the company came to Lighthouse with an unfortunate Catch-22: in order to modernize its processing and eDiscovery capabilities, it was losing the ability to deduplicate a majority of its data with each new ingestion. Lighthouse Migration Expertise Because of the volume of new clients moving to Lighthouse for eDiscovery support, Lighthouse has developed an entire practice group dedicated to data migration. This group is adept at creating customized solutions to the unique challenges that often arise when migrating data out of legacy systems. The team works closely with each client to understand the scope, types of data, challenges, and future needs so that the data migration process is seamless and efficient. The Lighthouse migration team quickly got to work gathering information from the healthcare company to start this process, paying particular attention to the Lotus Notes deduplication issue. Once all relevant information was gathered, Lighthouse worked with stakeholders from the organization to form a comprehensive migration plan that minimized workflow disruption and included a detailed schedule and workflow for future data. In the process, Lighthouse also developed a custom solution for the Lotus Notes issue using our proprietary AI technology. An Innovative Solution: Lighthouse AI Lighthouse’s advanced AI technology can create a unique hash value for all data, no matter how it was originally processed. The Lighthouse migration team leveraged this innovative technology to create a unique hash value for the Lotus Notes files that were originally processed as HTML files. That hash value could then be matched against any new Lotus Notes files that were added to the database by the company, even when those files were processed as EML files. With this proprietary workflow, the healthcare company was able to seamlessly move to Lighthouse’s eDiscovery platform, which was better equipped to serve its eDiscovery needs—without losing the ability to deduplicate its data. Set Up for Success In just five months, Lighthouse completed a seamless migration of the healthcare company’s data by creating a custom migration plan that minimized blackouts and kept all databases up and running. Importantly, Lighthouse also leveraged its proprietary AI to create an innovative solution to a complex problem, ensuring continued deduplication capability and reduced discovery costs. ‍ Corporate Case Studycase-study; ai; ai-and-analytics; ai-big-data; corporate; corporation; ediscovery; ediscovery-migration; prism; processing; project-management; healthcareediscovery-review; ai-and-analytics; client-successCase-Study, client-success, AI, ai-and-analytics, AI-Big-Data, Corporate, Corporation, eDiscovery, eDiscovery-Migration, Prism, Processing, Project-Management, Healthcare, ediscovery-review, ai-and-analytics

A prominent law firm leveraged a cloud-based software solution to increase efficiency and scale, resulting in significant costs savings. What They Needed A mid-sized East Coast law firm­—known for its expertise and experience in complex and high-stakes matters—was looking for new software to replace its in-house legacy technology. Their in-house tool did not provide the level of sophistication or throughput the team needed to continue to scale their work for their clients. In assessing their potential new partner, the firm required access to best-in-class technology, in particular Relativity and Nuix, as the firm’s employees were already familiar with these platforms. In addition, they wanted to leverage automation to have repeatable processes that would save both themselves and their clients time and money. ‍ How We Did It Lighthouse Spectra was selected for its simple and intuitive interface that allows users to internally manage client matters across best-in-class technology – including Relativity, Nuix, and even Brainspace. With Spectra, the firm can now start matters immediately, without having to go through the vendor solicitation and/or statement of work processes, creating real time savings. And the monthly subscription price for Spectra gave them more transparency around billing and greater cost control to help them stay within their budget. The onboarding and training processes were quick, due to the experience of the internal team coupled with the ease of use of Spectra’s. After the initial deployment of Spectra, the firm started processing client data through the tool immediately. They were able to get these matters through processing (Nuix) to review (Relativity) within a few hours, rather than an entire day or more, as was typical with their previous in-house solution. We can go from soup to nuts without having to reinvent the wheel each time. It is truly self-service. — Law Firm The Results Soon after onboarding, the firm took on a couple quick-turn and complex matters that they were able to handle more quickly due to the speed and scale of Spectra, as well as the support of Spectra team. In one instance, they received a request late in the work day that needed to be turned around within a short period of time. Prior to deploying Spectra, that would have taken some hands-on experience and a day’s worth of time. With Spectra, they were able to process it as soon as they received it and it was available for review within a few short hours. In another instance, the firm received a request with a pressing deadline where the document set consisted of approximately 95% foreign-language text. Quickly translating the text to English was imperative to firm’s success. To solve this problem, the Spectra team pointed the firm to a machine language translation tool that easily integrates with Spectra. By deploying the integrated translation service on the workspace, documents submitted for translation were loaded back into the workspace as easily as if it was performing a mass edit. This provided an easy solution for the firm for this particular matter, and now that it’s integrated, the feature is available to the firm on demand. By moving to Spectra, the law firm was able to leverage best-in-class technology, gain more transparency and control around the entire eDiscovery process, and create efficiencies and therefore, reduce costs for themselves and their clients. Leveraging Spectra, the law firm can now do more with less and scale their business to support their clients’ growing needs. ‍ Law Firm Case Studycase-study; ediscovery; self-service, spectra; spectra; ai-and-analytics; analytics; processing; tar-predictive-coding; technology-assisted-review; tar; law-firmediscovery-review; client-successCase-Study, client-success, eDiscovery, self-service, spectra, Spectra, ai-and-analytics, analytics, Processing, TAR-Predictive-Coding, technology-assisted-review, TAR, Law-Firm, ediscovery-review,

How They Did ItPenningtons Manches Cooper partnered with Lighthouse to deploy Spectra, which was implemented within three months from initial proof of concept to rollout with live matters. Primary areas of focus during the implementation were training, process design, and internal change management. The project began with roundtable sessions to fully understand the scope and ensure that deployment was customized to fit Penningtons Manches Cooper’s requirements, deliverables, and goals. And because Spectra is a cloud-based solution, there was no capital expenditure or additional IT resourcing required for implementation. This allowed for a flexible approach, fast implementation, and low ongoing maintenance for Penningtons Manches Cooper.Once the tool was initially implemented, the team at Penningtons Manches Cooper identified a suitable matter to be used in a proof of concept. Lighthouse trained key Penningtons Manches Cooper personnel on how to use Spectra, and together the two teams worked to create a scalable and repeatable workflow for particular work types. All items were recorded in a bespoke playbook, which fully documents Spectra’s capabilities and process as well as specific Penningtons Manches Cooper requirements.Next, Lighthouse provided training to the wider Penningtons Manches Cooper team on Spectra's built in analytics and redaction tools. Due to the simplicity and on-demand nature of Spectra, the team at Penningtons Manches Cooper was able to realize a 1 to 4-hour reduction in the time it takes to create a matter and upload data into Relativity. Further, Lighthouse developed a custom Relativity template. to ensure the user experience in Relativity is mirrored across matters and complements the firm’s workflows.Following the successful trial period, Penningtons Manches Cooper has identified and managed many other matters in Spectra with very little external support. Setup of each new matter has been reduced significantly, in some circumstances by up to 2-3 days, as there has been a significant reduction in the number of steps required to instruct external eDiscovery vendors, including no need to gather price proposals, no delay while vendors run conflict checks, and no need for any additional contract negotiation. As a consequence, each legal team was typically able to begin reviewing documents on the same day the data was received by the firm.In conjunction with the above, predictable and recurring billing practices were implemented and custom reports were developed around the firm’s matters and metrics. This, in turn, will allow Penningtons Manches Cooper to manage cost recovery and integrate billing for a more seamless and efficient process.The ResultsPenningtons Manches Cooper partnered with Lighthouse to roll out Spectra, which enabled their team to control the process from the very start and create efficiency and predictability of cost and process. By using Spectra, the team at Penningtons Manches Cooper was able to create matters and upload and process data quickly, all within a simplified and intuitive interface. The use of best-in-class technology, combined with repeatable process and in-house expertise, created a tangible benefit, ensuring eDiscovery and document review are completed with minimal cost, a savings which can be passed on directly to the client.

Lighthouse Spectra helps a considerable healthcare organization gain control, pricing transparency, and efficiency gains in the eDiscovery process. What They Needed A large healthcare organization was looking to solve their eDiscovery challenges around speed and cost. Specifically, they needed to increase their overall efficiency, and have more control over their matters with truly transparent and lower ediscovery-related costs. How We Did It Lighthouse Spectra was chosen to help achieve these key goals. Spectra is a self-service, on-demand eDiscovery tool with a transparent subscription-based pricing model. Spectra users can also access a full-time project management team at Lighthouse, whenever needed – all for one predictable price. Spectra onboarding was tailored to the users’ needs and focused on teaching users how to use Spectra itself, as well as when and how to use Brainspace, an analytics engine available inside the platform. Since Spectra is built with an intuitive interface, it only took a few short trainings over the course of a few weeks for the users to become comfortable using it. The Lighthouse team also ensured that Relativity and Spectra were customized to the organization’s specific needs. Our teams ensured that all customized permissions and views were set up within Relativity and worked with the organization to create custom Relativity templates to apply their standard coding pallets, rule-based coding propagations, pre-baked saved searches, standard views/layouts, imaging profiles, and more. Additionally, the Lighthouse team also assisted in building a continuous multi-model learning (CMML) workflow for their team to leverage within Spectra. Once set up was complete, the organization immediately started leveraging Spectra to process their data and run search terms as needed on a variety of diverse case types, including labor and employment cases, internal investigations, and OIG requests. The Results By moving to Spectra, the healthcare organization gained more control over their eDiscovery processes, created more efficient workflows, and achieved significant cost savings with transparent and predictable pricing. Since deploying the tool, the organization found that using the search and analytics capabilities of Spectra reduced the volume of natives to just 4.5% of the total hosted volume, minimizing the count of documents being reviewed by 95%. The custom Relativity template prevents the need to reinvent the wheel with each new matter and drive consistency across their portfolio. Further, the CMML workflow allows the organization to prioritize review of documents that are most likely to be responsive, as well as minimize the number of documents that go to review. Both of these enhancements allowed the organization to increase their overall speed from collection to production while lowering their overall eDiscovery-related costs. Through these new workflows and processes, the healthcare organization has achieved both defensibility and affordability and reduced review time from days to hours. This has resulted in an overall savings of $500K in their first year with Spectra.\ Corporate Case Studycase-study; corporate; corporation; ediscovery; self-service, spectra; spectra; ai-and-analytics; analytics; processing; tar-predictive-coding; technology-assisted-review; tar; healthcareediscovery-review; client-successCase-Study, Corporate, Corporation, eDiscovery, self-service, spectra, Spectra, ai-and-analytics, analytics, Processing, TAR-Predictive-Coding, technology-assisted-review, TAR, Healthcare, ediscovery-review

Cleary Gottlieb and Lighthouse save millions of dollars and thousands of hours in HSRs Second Request for Fortune 500 company. What They Needed A global Fortune 500 electronics company received an HSR Second Request from the Department of Justice (DOJ), with an extremely aggressive timeline to reach substantial compliance. They engaged Cleary Gottlieb (“Cleary”), a global technology-savvy and innovative law firm with extensive experience handling challenging Second Requests. After Cleary led negotiations with the DOJ to reduce the scope of the investigation, the client was faced with 3.3M documents to review—a significant subset of which included CJK language documents that would require expensive and time-consuming translation. To further complicate matters, the DOJ and Cleary remained engaged in ongoing scope negotiations, resulting in additional data being added throughout the project. Cleary knew that conventional TAR technology was not capable of evaluating a dataset with ever-changing review parameters. How Cleary and Lighthouse Did It CJ Mahoney, counsel and head of the eDiscovery and litigation technology group at Cleary, has extensive experience working on complex HSR Second Requests and has pioneered a number of different analytics-driven methods to reach substantial compliance in the past. Based on prior joint success in innovating new ways to use this technology to improve privilege analytics, CJ immediately saw the potential of Lighthouse’s proprietary AI technology for this challenge. Together, CJ and the Lighthouse data scientists developed a unique training workflow to achieve highly precise responsive prediction results on this challenging dataset. CJ secured the DOJ’s first-ever approval of this workflow with Lighthouse’s proprietary AI technology. Immediately after approval, responsive and privilege analysis and review began simultaneously, enabled by AI technology. For responsiveness, the teams utilized an active learning TAR workflow wherein subject matter experts reviewed a control set of randomly selected documents. After only a few training rounds, the system reached stability and began scoring the remaining dataset for responsiveness. A privilege classifier was built based on 20K previously confirmed privilege calls and applied to score all documents in the privilege workspace. The teams used a combination of the analytic results and privilege terms to identify potential privileged documents. All documents within this set that were scored as “highly likely to be privileged” were immediately routed to reviewers for review and privilege logging. Conversely, documents scored as “unlikely to be privileged” were removed from privilege review after Cleary’s attorneys verified the accuracy of the results using a random sample. Further, the teams used the privilege classifier to identify additional privilege documents that had not hit on privilege terms. As the timeline for substantial compliance approached, negotiations with DOJ regarding relevant timeframes and custodians continued, resulting in the near-constant addition and removal of documents from the dataset. The Lighthouse and Cleary teams managed the ever-changing dataset with ease using the Lighthouse technology and workflow developed by the teams. The Results Using a specialized TAR workflow leveraging advanced AI, the teams delivered highly accurate responsive classification, resulting in more than 500K (or more than 40%) fewer documents requiring further review and production to the DOJ, when compared to legacy TAR tools. By creating a smaller volume of documents requiring production, the amount of privilege and foreign language review was also lessened. For example, 120K fewer foreign language documents were included in the final responsive set compared to legacy TAR tool results. This reduction of review and translation saved approximately $1M alone. For the client, the smaller responsive set meant faster production turnaround times, lower overall costs, and risk mitigation through the decreased chance for inadvertent production of non-responsive documents. The Lighthouse and Cleary partnership resulted in the removal of 200K documents from privilege review beyond what could have been possible through conventional methods, leading to cost savings of $1.2M and time savings of 8K review hours. The team further mitigated risk to the client by identifying privilege documents that did not hit on standard privilege terms. The Cleary and Lighthouse partnership resulted in substantial compliance with the HSR Second Request, increased risk mitigation, faster document review, and remarkable savings for the client. Law Firm Case Studycase-study; antitrust; ediscovery; tar; tar-predictive-coding; law-firm; hsr-second-requests; investigations; mergers; ai-and-analytics; ai-big-data; artificial-intelligence; ai; acquisitions; analytics; predictive-coding; prism; privilege; privilege-review; tech-industryediscovery-review; antitrust; ai-and-analytics; client-success; lighting-the-path-to-better-ediscoveryCase-Study, client-success, Antitrust, eDiscovery, TAR, TAR-Predictive-Coding, Law-Firm, HSR-Second-Requests, investigations, Mergers, ai-and-analytics, AI-Big-Data, artificial-intelligence, AI, Acquisitions, analytics, predictive-coding, Prism, privilege, privilege-review, tech-industry, ediscovery-review, antitrust, ai-and-analytics

Lighthouse saves insurance giant millions of dollars during major technology upgrade. Key Actions Microsoft referred the Company to Lighthouse to resolve existing concerns from the Company’s IT and legal departments that were stifling their automation and transition process to Microsoft 365 (M365). Lighthouse held educational workshops on eDiscovery tools within M365, and devised a comprehensive plan for the compliance. Key Results Unblocked the M365 transition effort and enhanced the partnership between legal and IT. Compliance concerns were answered within M365, saving the company millions of dollars in retaining or updating legacy data management systems. What They Needed Legal Concerns Churn 11th Hour Nightmare for IT Department In 2017, a nationwide insurance giant initiated a transition from an on-premises Microsoft solution to a cloud-based M365 solution fueled by gain from cost, performance, and security improvements. Years later, and well past the intended launch date, the Company’s legal team suddenly halted the transition entirely due to concerns of M365’s eDiscovery capabilities, specifically, how M365 would handle the identification, preservation, and collection of email, instant messages, and files for the Company. The legal department insisted the company retain its custom-built archival solution until all compliance concerns were allayed. These demands put the IT department in an extremely tough spot after having already invested several years into the transition to M365. If forced to extend their aging, on-premises solution, the team would face substantial costs. To help unstick the implementation project, Microsoft suggested the Company engage Lighthouse to assist. Lighthouse immediately understood the legal team’s concerns and acted swiftly to address the Company’s insistence on exercising the transition to M365 with great caution, all while remaining vigilant of the Company’s receipt of hundreds of new legal matters monthly. The sensitive nature of data in this industry and the complex regulatory environment made the potential risk related to mismanagement very high. The process was intricate and complex, and required high-level integration to mitigate the significant risks that were specific to individual privacy regulations, such as the California Consumer Privacy Act (CCPA) and the European Union’s General Data Protection Regulation (GDPR). Hands-on Experience and High-touch Service Bridge the Gaps Lighthouse fielded a team of experts with direct experience in the same or similar roles as the various client stakeholders, ranging from IT to records management, corporate legal, and public affairs. This hand-selected team led a three-part process with their counterparts from the Company: Providing education on the eDiscovery aspects of M365 Analyzing current workflows and performance, and expressing their desired future state Devising a high-level design document for how relevant parties could conduct eDiscovery tasks in compliance with the requirements while using M365 The first two processes helped restore unity among stakeholders, while the design document delivered on the legal team’s concerns, including specified settings for a range of M365 applications and components, such as Exchange Online, SharePoint Online, OneDrive for Business, and Teams. The design document made room for process automation and/or custom workflows, as well as for third-party system integration (for compliance archive, legal hold, matter management, etc.). The initial project success led to a continuing relationship between the Company and Lighthouse, and over time Lighthouse has become a critical element in the Company’s ongoing M365 implementation and adoption journey helping them in charting a path forward. Corporate Case Studycase-study; big-data; cloud-migration; cloud; cloud-services; ccpa; corporate; corporation; data-privacy; data-protection; emerging-data-sources; information-governance; ediscovery; microsoft; gdpr; legacy-data-remediation; legal-holds; risk-management; insurance-industry; record-managementmicrosoft-365; data-privacy; information-governance; client-success; lighting-the-path-to-better-information-governanceCase-Study, Big-Data, Cloud-Migration, cloud, Cloud-Services, ccpa, Corporate, Corporation, Data-Privacy, data-protection, Emerging-Data-Sources, Information-Governance, eDiscovery, microsoft, gdpr, Legacy-Data-Remediation, Legal-Holds, microsoft, risk-management, insurance-industry, Record-Management, microsoft-365, data-privacy, information-governance

Lighthouse bridges internal gaps during technology overhaul and solves longstanding compliance issues for a German multinational healthcare manufacturer. Key Actions Lighthouse engaged company stakeholders in operational planning and received funding from Microsoft to devise and integrate a premium Microsoft 365 (M365) add-on to existing Purview Premium eDiscovery, which resolved an outstanding compliance need. Key Results The proof-of-concept achieved a zero-trust security model integrated with third-party software, and satisfied the barring of critical needs for the Company that centralized IT and legal departments after years of dysfunction. What They Needed Automating a transition to M365 commonly yields a clash between IT, legal, and compliance stakeholders if the decision to convert was spearheaded by IT and made without consulting legal and compliance teams. Typically, during planning or implementation of converting to M365, legal teams ask IT how the new platform will manage compliant and defensible processes, and if IT doesn’t have the answers, the project stalls. This was the situation facing a multinational manufacturing Company that engaged Lighthouse for help during the spring of 2020. At that time, the Company was several years into its M365 transition, and the legal teams’ requirements for adoption of native M365 compliance tools barred a complete transition. Pressure to adopt the tools escalated as M365 workloads for content creation, collaboration, and communication were already rolled out, creating an increasingly large and complex volume of data with significant degrees of risk. Lighthouse Responds to Need and Launches New Technology In partnership with Microsoft Consulting Services, Lighthouse organized a companywide M365 “reset,” hosting a three-day workshop to revamp the transition process and generate an official statement of work. The strategic goal was to streamline the stakeholders from litigation, technical infrastructure, cybersecurity, and forensics teams that previously failed to align. The workshop fielded critical topics geared to encourage constructive discussions between stakeholders and to strengthen departmental trust. The outcome of these discussions eventually enabled the company to move forward with critical compliance updates, including the collection and parsing of Microsoft Teams data, and the management of myriad files and email attachments. Lighthouse took stock of the current state, testing potential solutions, and arrived at a proof-of-concept for an eDiscovery Automation Solution (EAS) that augmented existing M365 capabilities to meet the legal team’s security requirements and remediate any performance gaps. Microsoft recognized the potential value of the EAS for the wider market, ultimately leading to Microsoft funding for the proof-of-concept. Inside the eDiscovery Automation Solution (EAS) Technology Azure-native web application designed to orchestrate the eDiscovery operations of an M365 subscriber through Purview Premium eDiscovery automation Maximized Microsoft Graph API “/Compliance/eDiscovery/” functions and other Microsoft API Simplified to Azure AD trust boundary, targeting the M365 tenant hosted within, and enabling full governance of identity and entitlement throughout Azure and M365 security features Benefits Achieved a zero-trust security model Authorized high-velocity, high-volume eDiscovery tasks without outside technology through automation and orchestration of existing M365 eDiscovery premium capabilities native to M365 Mobilized integration with third-party software included in the Company’s eDiscovery workflows Amplified workload visibility by automatically surfacing relevant Mailboxes, OneDrives, and other M365 group-based technologies dependent upon selected Custodians’ access Corporate Case Studybig-data; case-study; cloud-migration; cloud; cloud-services; cloud-security; corporate; corporation; data-privacy; emerging-data-sources; information-governance; ediscovery; microsoft; manufacturing-industry; risk-managementchat-and-collaboration-data; ediscovery-review; microsoft-365; data-privacy; information-governance; client-success; lighting-the-path-to-better-information-governanceBig-Data, Case-Study, Cloud-Migration, cloud, Cloud-Services, Cloud-Security, Corporate, Corporation, Data-Privacy, Emerging-Data-Sources, Information-Governance, eDiscovery, microsoft, manufacturing-industry, risk-management, chat-and-collaboration-data, ediscovery-review, microsoft-365, data-privacy, information-governance

Lighthouse's forensics experts found hidden clues missed during an internal investigation, proving a departing employee was stealing company data. Lighthouse Key Results By quickly engaging Lighthouse forensics experts: The company stopped proprietary and sensitive information from being disseminated and used by competitors. The company’s law firm was able to quickly take action against the employee, preventing any further malfeasance or damage. Investigation Overview Week 1 Day 1 – 4 — Employee uploads company data onto a personal Google Drive account over the span of four days. ‍ Day 4 – 5 — An internal investigation concludes that all company data has been deleted from the employee’s personal data sources and no further action is needed. However, the company’s outside counsel calls in Lighthouse forensics experts to perform a separate investigation for affirmation. ‍ Day 6 — Lighthouse forensics experts find evidence missed during the company’s internal investigation, indicating that the laptop provided to internal investigators was a “decoy,” and that the employee had actually transferred the proprietary company data onto an as-of-yet undisclosed laptop. Week 2–4 Outside counsel uses Lighthouse’s findings to file a restraining order against the employee and elicit a confession wherein the employee admitted they had downloaded the proprietary data onto a secret laptop—owned by another business. Week 6 Lighthouse forensics team is provided access to the additional laptop and the employee’s private Google Drive account. Although there is no company data stored on the drive, the Lighthouse team dives deeper and immediately finds that the employee had restored the previously deleted company data back to their Google Drive account, transferred it the secret laptop, and then deleted it again from the Google Drive account. These findings enable outside counsel to take additional remediating actions. Suspicious Activity by a Departing Employee Raises Alarm Bells During routine internal departing employee analysis, a global company was alerted to the fact that an employee had uploaded more than 10K files containing sensitive proprietary data to a personal Google Drive account. The company immediately launched an internal investigation and engaged their outside counsel. Over the course of the internal investigation, the employee admitted they had uploaded company data to their Google Drive, and then used an external hard drive to transfer that data onto a personal laptop. However, the employee avowed that all company data had since been deleted—which the company’s IT team confirmed by examining all three data sources. However, due to the sensitivity of the data, outside counsel wanted additional reassurance that the employee was no longer concealing proprietary company data. The law firm had previously relied on Lighthouse forensics experts for similar investigations and knew that they could count on Lighthouse expertise to find any hidden clues that would point to additional hidden data. Finding the Forensic Breadcrumbs Week 1 The Lighthouse forensics team received access to forensic images of the employee’s personal laptop and external hard drive within one week of the first suspicious upload. The team immediately noticed that the employee’s data tracks conflicted with the timelines and statements provided by the employee during the company’s internal investigation. Key Evidence Found by Lighthouse Forensics Experts The external hard drive used to transfer company data had not been plugged in to the personal laptop during the relevant time frame. File paths identified on the external hard drive (which show the file locations where data was downloaded upon connection) did not match those on the personal laptop provided to internal investigators. This evidence led the Lighthouse team to conclude that the laptop provided by the employee was not the laptop used to download company data—and that a different laptop with the stored proprietary company data existed but had not been disclosed by the employee. Week 2–4 A Lighthouse forensics expert provided a sworn declaration explaining the evidence found during the examination of the employee’s personal devices. The company’s law firm used this declaration to file a restraining order to stop the employee from continuing to steal or disseminate proprietary data. The law firm also used Lighthouse’s findings to elicit a confession from the employee, admitting that they had been secretly working part-time for another business, and had transferred the company’s proprietary data onto a laptop provided to the employee by that business. Week 6 Within two weeks of the Lighthouse forensics expert’s sworn declaration, the Lighthouse team was provided access to the laptop owned by the other business, as well as the employee’s personal Google Drive account. Lighthouse’s inspection of the Google Drive did show that all company data had been deleted, as had been confirmed by internal investigators. However, Lighthouse immediately went deeper into the Google Drive and found conclusive evidence that the employee had subsequently “restored” the deleted proprietary data just a few days after the internal investigation ended, in an attempt to continue with the data theft. Key Evidence Found by Lighthouse Forensics Experts Despite the fact that no company data was stored on the employee’s personal Google Drive account at the time Lighthouse received access to it, Lighthouse forensics experts went above and beyond to do a deeper forensic dive into the user activity log, email account, and internet searches stored on the Google Drive. That deeper analysis showed that: Two days after the internal investigation ended, the employee began conducting numerous internet searches for ways to “restore” deleted files on Google Drive. Two weeks later, the employee emailed a private IT company asking for help restoring deleted Google Drive files. One day after sending that email, thousands of files were restored to the employee’s Google Drive. Those restored files were once again deleted a few days later. Before the restored files were re-deleted, the employee downloaded some of the files containing company data to the “secret” laptop owned by another business. Keeping a Lid on Pandora’s Box The evidence found by Lighthouse forensics experts after their initial examination of the employee’s personal devices enabled the company’s law firm to take legal action against the employee less than one month after the first suspicious data upload. Within one day of being provided access to the employee’s personal Google Drive account, Lighthouse forensics experts were able to find exactly how and where the stolen proprietary and sensitive data was hidden. This enabled the company to permanently prevent any dissemination of that proprietary and sensitive data to competitors. ‍ ‍ Corporate Case Studycase-study; corporate; corporation; g-suite; forensics; investigations; collections; fraud-detection; red-flag-reporting; departing-onboarding-employeedigital forensics; client-successCase-Study, client-success, Corporate, Corporation, -G-Suite, digital forensics, investigations, collections, fraud-detection, Red-Flag-Reporting, Departing-Onboarding-Employee, digital forensics

Lighthouse experts distilled crucial information from millions of produced documents for a client's legal strategy during a Department of Justice investigation. Key Actions Lighthouse created 35 deposition kits by conducting two large-scale data investigations—and addressing multiple ad-hoc emergency investigations in the process—on an initial production set of six million documents, identifying the 4,100 most relevant items. Lighthouse adhered to a complex delivery schedule so the case team had time to prepare for each deposition. ‍ Key Results Counsel was well-prepared for 35 depositions using the deposition kits delivered by Lighthouse. Instead of spending time and review cycles finding they evidence, they used the bandwidth they saved to hone their legal strategy. ‍ Responding to a Fast-Moving Government Investigation, with a Merger on the Line When two of the largest publishing companies in the country entered a merger deal, the Department of Justice (DOJ) reacted with a large anti-trust investigation. Pursuant to an HSR Second Request, the companies produced a combined six million documents to the DOJ. In response, the DOJ sought to depose 35 individuals within a few months’ time. This left outside counsel with just two months to prepare for the defense of a massive potential merger, including intensive preparation for all 35 depositions. To do so, they knew they would need to find every shred of relevant information hidden within those six million documents—as quickly as possible. Executing a Plan for Better Legal Strategy When the law firm reached out to Lighthouse for help, our agile search team of analytic, legal, and linguistic experts immediately got to work, consulting with counsel to understand the specifics of the investigation, as well as the case team’s initial strategy for response. Using this background, the Lighthouse team mapped out a information search plan leveraging advanced volume reduction technologies and linguistic search models, delivering: Comprehensive deposition kits for all 35 deponents. Each kit was scheduled to be delivered well ahead of the corresponding deposition date, and included summaries of Lighthouse experts’ findings and highlights of notable documents and facts, in order to give counsel adequate time to prepare for each deposition. Key and relevant documents related to the DOJ’s anti-trust concerns and outside counsel’s defense strategies. These documents, provided on a rolling timeline, were uncovered by conducting two large scale data investigations: one to find all documents related to determining which publishers participated in or won the auctions, and another to find all documents necessary to facilitate the creation of an all-encompassing book auction timeline. Given the legal and analytic expertise of our specialists, Lighthouse search results often uncovered new areas of importance for the case team. When the case team responded to this new information with urgent follow-up search requests (with results sometimes needed in 24 – 48 hours), our team also boosted efforts to provide the requested information. Powering Counsel with Knowledge—and Time By partnering with Lighthouse, the case team stayed focused on preparing for depositions and crafting a response to the DOJ’s concerns to the merger, instead of conducting database searches and reviewing irrelevant or redundant documents. In just two months, Lighthouse found and delivered the 4,100 documents the case team needed, out of an initial population of six million documents. This included creation and delivery of 35 deposition preparation kits, all documents related to the case team’s strategy for responding to the DOJ’s antitrust concerns (delivered on a rolling basis), and results of six ad hoc case team investigation requests. All deposition kit and derivative search deliveries met or exceeded counsel’s delivery deadline expectations. Law Firm Case Studycase-study; document-review; ediscovery; fact-finding; kdi; key-document-identification; law-firm; hsr-second-requests; investigations; mergers; acquisitionsediscovery-review; ai-and-analytics; antitrust; client-successCase-Study, client-success, document-review, eDiscovery, fact-finding, KDI, key-document-identification, Law-Firm, HSR-Second-Requests, investigations, Mergers, Acquisitions, ediscovery-review, ai-and-analytics, antitrust

Lighthouse proprietary, technology-enabled strategy for finding key documents gives counsel a strategic advantage in a challenging HSR Second Request. Key Results In just three weeks, the Lighthouse team found the 1K most important documents out of an initial data population of 19M documents. Lighthouse experts began flowing key documents to the case team just three days after the initial kickoff meeting. Lighthouse saved counsel at least a month’s worth of preparation time for witness interviews and defense planning by efficiently finding the most important documents. A Mountain of Data and a Short Timeline A global technology company and their two outside counsel teams needed to quickly prepare a winning defense in a high-stakes, time-sensitive, Department of Justice (DOJ) Hart-Scott-Rodino (HSR) Second Request. To do so, they would have to identify and review all potentially damaging (or alternatively, helpful) documents within an initial data population of 19M documents. Finding the most important documents within that massive data volume—in less than one month—presented a Herculean task. A Proprietary Solution for Finding the Most Important Documents Lighthouse’s technology-enabled search strategy is led by information retrieval experts with decades of industry experience, who utilize robust search technologies that support large data volumes beyond industry-standard tools. Together, this combination of cutting-edge technology and data expertise quickly surfaces critical documents, streamlining legal analysis and case preparation for case teams. Handing Over the Keys to a Strategic Defense With no time to lose, Lighthouse TAR and review experts were able to whittle down the 19M documents to just over 990K responsive documents for production to meet substantial compliance. Simultaneously, Lighthouse experts quickly got to work finding the most important documents for the case team. Rather than relying on keyword culling, the Lighthouse team analyzed the data population and leveraged proprietary algorithms to safely reduce the universe to documents that contained the unique content the case team needed. From there, a team of six data retrieval experts leveraged proprietary search technology and institutional knowledge of the client’s data, gleaned from working with the company in a managed services capacity, to find key documents that were critical to the case team. Our experts used an iterative process and had weekly meetings with the case team so that they could instantly integrate counsel and witness feedback throughout the project, which helped yield more accurate search results. With this process, the Lighthouse team began flowing key documents to the case team just three days after the initial kickoff meeting. Over the course of the next three weeks, the Lighthouse team provided a total 1K key documents (out of a 990K responsive documents) in eight rolling deliveries. By gaining immediate access to these documents and eliminating the need for time-consuming and costly manual review, Lighthouse saved the team at least a month’s worth of preparation time for witness interviews and defense preparation. Law Firm Case Studyantitrust; case-study; document-review; ediscovery; fact-finding; kdi; key-document-identification; tar; tar-predictive-coding; law-firm; hsr-second-requests; investigations; mergers; acquisitionsediscovery-review; ai-and-analytics; antitrust; client-successAntitrust, Case-Study, document-review, eDiscovery, fact-finding, KDI, key-document-identification, TAR, TAR-Predictive-Coding, Law-Firm, HSR-Second-Requests, investigations, Mergers, Acquisitions, ediscovery-review, ai-and-analytics, antitrust

Lighthouse red flag report prevents proprietary data from being taken by departing employee. Key Actions A global company partnered with Lighthouse to create a proactive departing employee program to prevent data loss and theft. Lighthouse forensics experts prepared Red Flag Reports for every departing employee that fell within a specific category of employees. Each report outlined the risks associated with the departing employee based on a skilled forensic examination of their activity and data. Soon after implementing the program, a Lighthouse Red Flag Report alerted the company to suspicious activity by a departing employee indicating a high risk for data loss. Key Results Because of Lighthouse’s analysis and quick response, the company was able to: Prevent sensitive data from being disseminated outside the company. Avoid costly litigation associated with proprietary data loss. Reevaluate the departing employee’s severance package due to breach of contract, resulting in additional cost savings. ‍ What They Needed A global company was dealing with an increased risk of data loss and theft from departing employees. The company retains large volumes of proprietary data spread across their entire data landscape. Much of that data is also highly sensitive and would create a competitive disadvantage for the company if it were to end up in competitors’ hands. The company was also facing a higher volume of employee turnover—especially within roles that had access to the company’s most sensitive data (e.g., company executive and management roles). The company was concerned that these factors were creating a perfect storm for data theft and loss. They realized they needed a better system to catch instances of proprietary data loss before any data left the company. Company stakeholders reached out to Lighthouse because they knew our forensics team could help them build a proactive, repeatable solution for analyzing and reporting on departing employee activity. How We Did It Lighthouse forensics experts worked with the company to create a custom departing employee program for data loss prevention. With this program, Lighthouse experts prepared a Red Flag Report for every departing employee that fell within specified high-risk categories (e.g., employees above a specific seniority level, or employees that had access to highly sensitive company data, etc.). Each Red Flag Report was prepared by a Lighthouse forensics expert and summarized the data theft risk associated with the underlying employee. Every report contained: A high-level summary of the risk of data theft presented by the employee. A collection of attachments with highlights and comments by the Lighthouse forensics examiner (for example, a list of files stored in an employee’s personal cloud storage account, with an explanation of why that activity may indicate a higher risk of data theft). A forensic artifact categorization with associated risk ratings (e.g., if there were no suspicious search terms found during a scan of the employee’s Google search history, the examiner assigned that category a lower risk rating of “1”). Recommended next steps, with options for substantiating high-risk employee behavior. Reports were delivered to a cross-functional group of company stakeholders, including IT, human resources, and legal groups. The Results The Lighthouse program very quickly paid off for the company. Soon after initiation, Lighthouse escalated a Red Flag Report for a departing employee that showed a high risk of data loss. Specifically, the Lighthouse forensics examiner flagged that the employee had connected two different external thumb drives containing sensitive company data to their laptop. This activity was flagged by the Lighthouse forensics examiner as high risk because: The employee had already been directed by the company to return any device that had corporate data saved on it; and The employee had previously indicated that they didn’t have any devices to return. As soon as Lighthouse escalated the Red Flag Report, company stakeholders scheduled an interview with the employee. This interview resulted in the employee admitting that they had taken corporate data with them, via the two thumb drives. Because Lighthouse was able to quickly flag the employee’s suspicious activity, the company was able to retrieve the thumb drives before the proprietary data was disseminated to a competitor. The company was also able to reevaluate the employee’s severance package due to the breach of company policy, resulting in a significant cost saving. Even more importantly, the company now has a proven, proactive, and customized solution for preventing data loss and theft by departing employees—implemented by Lighthouse’s highly skilled forensics team. ‍ Corporate Case Studycase-study; corporate; corporation; forensics; investigations; collections; fraud-detection; red-flag-reporting; departing-onboarding-employeedigital forensics; client-successCase-Study, client-success, Corporate, Corporation, digital forensics, investigations, collections, fraud-detection, Red-Flag-Reporting, Departing-Onboarding-Employee, digital forensics

Imagine you are an attorney general suing a pharmaceutical company that manufactures a synthetic opioid spray and you're alleging racketeering. You've received 1.5 million documents in production and your team has three weeks before the next case management conference. Traditional review would have meant that you would spend months and likely millions of dollars to interrogate your data. Let's see what IQ Answers can do in the next several minutes. First off, I'm gonna just ask general questions within my dataset to get a sense of what was going on with this product and who it was prescribed for and what was happening with those prescriptions. So I'm typing a question about that generally to see what that returns for me. You'll notice here at the end of the query that you get an overall answer, but you also get topics surfaced for you along with citations that match each of these topics that highlight the particularly important parts of the document that can help lead you to the conclusions that are surfaced for you with IQ Answers. So here we see that this was a spray that was approved for breakthrough cancer pain and that that was the FDA intent of the approval. But what I'm also seeing in these topics that is being surfaced for me is that a lot of off-label prescription for non-cancer pain is apparently going on with this product. And I can tell that from these particular documents that I've clicked on here along with the citations where I'm seeing a hundred plus prescriptions a month that are off label. Well that's interesting. Now I'm also seeing that the salesforce has been explicitly instructed to prioritize high volume opioid prescription writers regardless of their specialty and regardless of what's happening with that prescription. And I can click into the documents and see that the volume is what is driving here. And then I also can look and see that there's been awareness internally that the approved indication from the FDA is not actually matching the patient population. So that's very interesting. It seems like we definitely have some use here that it was not intended, and I could figure that out in about 30 seconds in IQ Answers. I have the foundation. So, if the drug is approved for cancer pain, but the company is deliberately targeting non-cancer patients, that's definitely a gap from the FDA approval. And so, let's understand how they're going about making this happen. How are they getting doctors to keep writing these prescriptions? I'm going to go ahead and ask an additional question of IQ Answers to figure out what they're doing to get this volume of prescriptions written. And in particular, I noticed that there was something about speaker engagements that they were doing with doctors. So I'm going to ask about those speaker engagements. And you'll see here that basically the speaker engagement program was a way for them to pay doctors for prescriptions. I can see that they were tracking the ROI of those speaker payments as compared to the amount of prescriptions a doctor was writing. And I can also see from the documents and the citations that if they did not feel that a doctor was writing enough prescriptions, they were no longer part of these speaking events and, and thus paid through these speaking events. I also see these speaking events are not really genuine educational activity and it looks like the company was aware of this and was terminating doctors when they were not writing enough prescriptions to satisfy the amount of money that they were giving the doctors. So this all does not look very great for them in terms of how these programs were essentially bribery of these doctors. So if they're bribing the doctors, that still doesn't answer for me what's happening with the insurance companies. The product costs thousands of dollars a month and insurance companies wouldn't just approve that without any questions. So Vantage clearly needed a way to get these insurers to pay. Let me ask about that. I'm gonna type in a question about their programs to deal with the insurance companies and the way in which they instructed their employees. All right, so now I see in my answer that they had created what was called a Vantage Reimbursement Center. That was essentially their way of tracking the approvals from the insurance companies. And it looks like from the topics that's being surfaced here, that they were also using it as a vehicle to instruct their staff on how to deceive the insurance companies. In particular, here you can see in this document where they talk about using particular types of language, lingo, or diagnoses to get the insurance companies to approve the use of these drugs for the written prescriptions. But it also looks like they know that these are false statements that are being made when they are talking with the insurance companies. You can see here they're tracking and they want a 100% authorization success rate. So they're essentially giving all of their employees the way to beat the system, to cheat the insurance company, and to get them to approve something under false pretenses. So I now have two parallel fraud streams that are emerging here. One to bribe doctors to write prescriptions, one to deceive insurance companies to pay. For a RICO case, I also need to know that this was coming directly from management and from the top. So let's see if I can find that out in the dataset and ask a question about that to help me win my conviction. Alright, so now I'm gonna ask in particular, what evidence do we have that the CEO knew about this speaker program and this insurance program? Now that I'm asking this of the documents, what I can see here that is surfacing is that in fact the CEO did have direct knowledge and there's multiple documents that substantiate this. And in particular you can see this one here where he personally directs a speaker fee increase that is tied to prescription volume. In this document, you would have him talking about different tiers of speaker programs and that someone is no longer going to be invited to be a part of these speaker programs if they are not writing a certain amount of prescriptions. There's one here that surfaces a document where a hundred percent of the authorization success rate is something that he is directing and he's also calling for in the data. You also see here that I have additional follow up questions that I can be asked that are being surfaced by IQ Answers that will help me investigate and interrogate each one of these particular questions and the information I found up in these questions. But overall, it looks like I, in a matter of minutes, have been able to find key documents and important fact timelines that help me substantiate my case and know that I have a good chance of success moving forward and make me feel set up really well for my next case management conference.

Hi, Karl. Hi Stacy. How are you doing today? Good. It's good to see you. Good to see you too. Thanks for spending a little time with us today. Why don't you start out by telling us a little bit more about your role at Kirkland & Ellis and the types of matters that you handle? I'm a partner at Kirkland. My practice really involves the intersection of traditional discovery, preparing documents for production, meeting discovery obligations, and the like, and preparing case strategy, digging into the facts, understanding what those documents all show largely in the mass tort context. So large, very high-value litigation where facts and understanding the facts is really important. Well, so you just talked a little bit about case strategy, so I'd love to hear more about how you've used IQ Case Strategy, As part of litigation, it's really important that we understand what's in the materials, especially early on in the case. It's important to develop case strategy that's based on the actual evidence, based on the actual facts. And then we've, for a long time, been partnering with the Lighthouse team and members of the Lighthouse team to help us weed through, cull through the vast amount of material that often gets collected and produced in a case to really focus on what matters. It's important to be able to cull through those and really develop case themes, understand how particular issues are addressed in the documents, and then really leverage that information to be able to build out case themes, case arguments, develop our strategy for the case. And I think you've used IQ Case Strategy for depo prep in the past. We've actually, in a number of our cases, have really been able to leverage the deposition preparation to have our team focus on the substance of the case. Not spending time reading through a hundred thousand documents produced for custodian, but, focusing on the 100, 200, 300 that really matter the most for that person. That allows our team to focus on the substance as opposed to trying to figure out where in the vast universe of documents out there, that information is. That's great. So maybe touch a little bit on how AI is changing how you handle your client work at Kirkland. Yeah, it's a really exciting time, I think, for the entire field. I literally started in 2010 working on deposition prep, where I had partners who printed off tens of thousands of documents on hard paper and we would sift through them, flipping through them, and putting sticky notes on them. Since then, we've come a long way. The technology we have, especially with the evolving AI technologies, allows us to do more. More work and more effectively. Right by, early on in a case, understanding what the materials are, what the issues are, what the evidence shows, what the document shows, we're able to build out better case strategies that help our clients achieve their goals in litigation. So now that we've rolled out the full suite of applications under LighthouseIQ, I'm curious, beyond IQ Case Strategy, do you see yourself using some of the other tools that we've rolled out? We really do. We've really appreciated the Lighthouse IQ Case Strategy system and method for allowing us to do our work most efficiently and effectively for our clients. That said, I think with the advent of all the AI technologies and the implementation of those into the Lighthouse suite of tools that we've been talking about, we're really, really excited to leverage those materials and do more with them. In particular, the IQ Answers. We're really excited to, to try out on our next case to really help our teams and allow our teams to leverage the information that we're able to glean most quickly from, again, a large set of documents. That's great. Karl, thank you so much for spending time with us today. We really appreciate your partnership. Absolutely. Thank you, Stacy.

Hear how Eric Wieder and his team at Baker Botts uses LighthouseIQ get more control over when and how we review data.

Hear how Bryan Marra of Arnold & Porter uses IQ Case Strategy to get to insight faster. Hi Bryan. Hey Stacy. Good To see you. Why don't we start out by just sharing a little bit about your role at Arnold & Porter and the, the types of matters that you handle? So my practice focuses on merger investigations, the second requests, antitrust conduct investigations from the government and also merger litigation and other antitrust litigation. My specialty is really driving the eDiscovery process, um, helping clients use technology to drive more efficient outcomes for them in eDiscovery and complying with these government requests.Why don't You share a little bit about your use of LighthouseIQ, how it's helped you with your clients? Sure. So I used IQ Case Strategy. It was an antitrust litigation and we were facing trial in federal and state court in a matter of months. It was a very aggressive deposition schedule. We had over 30 depositions coming up in a matter of weeks, and we had a production population of over 23 million documents to look through.So how are we gonna tackle that? We could have done this the old fashioned way, hired an army of contract attorneys or used firm attorneys to basically sift through millions of documents, maybe use search terms to winnow it down, but then look at the results. It would've taken a long time, but instead we used IQ Case Strategy. So we worked with a small team of experts, linguists technologists, and we trained them on basically what they were looking for in terms of documents, what the case themes were about the witnesses. And they started delivering documents to us in a week. They kept up a weekly schedule basically to keep up with the depositions.They ultimately did depo prep kits for over 30 depositions and it worked well. I mean, out of 23 million documents, they surfaced thousands of the key documents and they surfaced them early enough for us to get insights and use them for prep in advance before the depositions. You mentioned using linguists and our Lighthouse team. How did pairing Lighthouse expertise with our LighthouseIQ technology help have a better outcome for you? The team we worked with, they basically developed classifiers and linguistic models, uh, using your technology to essentially identify key documents and it ended up being a really a seamless process. I mean, we thought the documents they came up with were relevant and were key documents and we thought it was an excellent use case.Maybe share a little bit what was the biggest impact of using LighthouseIQ? I mean, it was definitely the cost and time saving that was involved. I mean, we basically avoided having to do a massive document review effort, which would've cost the client a lot of money. And so by using this technology, we were able to short circuit having to do that and do things in a more efficient and focused way to get actionable intelligence that we could use, um, right away with our depositions and for the litigation strategy. So now that we've rolled out other applications, I know you've used some of them, but what are your overall thoughts of like using LighthouseIQ more broadly in the future? Yeah, I definitely see use cases to use more of LighthouseIQ technology.I mean, how I use AI is really to make eDiscovery more efficient for my clients to save money, to do things in a more focused way. And I can see use cases for IQ Answers. I'm, I'm looking forward to using that application for early case assessment to help clients find out what's in their documents at an early point to help focus the case strategy ahead of time. Maybe share a little bit more about how early insights really helps you and your teams. Definitely. So in merger investigations, finding out what's in your documents at an early point can be crucial.Oftentimes you produce like a million documents to the government and you don't really know what's in them ahead of time. But if you can know what's in your documents at an early point, it can really help you drive case strategy ahead of time. I Know you've used it on some large matters, but think about how, how would you use it on small matters or how you're thinking about the use of AI in the future. So I think size isn't really the main factor. I mean, clients are always looking to save money and they're always looking to find out more intelligence about their documents at an early point. And I think even in smaller matters, smaller investigations, this could be a way to see what's in your documents at an early point to drive case strategy.I look forward to using IQ Answers to do that, what I've seen of it that looks great and, and I think will help me in my practice for my clients. That's Great. Why don't you share a little bit about how you think about the use of AI in your practice? Really, AI helps you move from broad-based review solutions towards more focused actionable intelligence. And that's what we're trying to do in my practice to help clients use technology to find out more about their documents ahead of time to get through, you know, what would've been a massive costly undertaking much faster and more efficiently by using ai. And that's how I see my role is sort of being someone that uses this technology to drive these outcomes for my clients.Thank you so much for your time, Bryan. Really a pleasure to have this conversation with you. It was great speaking with you.

In every matter, there's a moment that changes everything. The moment information turns into understanding the moment, every decision becomes clearer, faster. The moment you can act with confidence, get to that moment quicker with LighthouseIQ, where intelligence meets performance. Hello and welcome. I'm Stacy Ybarra, Chief Marketing Officer at Lighthouse. Earlier this year we introduced LighthouseIQ, our eDiscovery platform, designed to bring earlier insight and greater control to the discovery lifecycle. Today you'll hear directly from clients putting that approach into practice. You'll also see how it helps legal teams stay flexible, whether they're managing complex matters today, or planning for how review platforms will evolve. To ground in how LighthouseIQ was built to support that flexibility, I'll turn it over to Iram Arras, our head of product and engineering. Iram. Thanks, Stacy. I'm Iram Arras, Senior Vice President of Product and Engineering at Lighthouse. My role is to make sure what we build actually works in the real world - not just in a controlled demo, but on live matters at scale when timelines are tight and consequences are real. Before joining Lighthouse, I spent time at Microsoft where the teams I worked with built Purview eDiscovery, which is used by many of the largest organizations in the world. That experience shaped how I think about this space. Legal technology has to be scalable, dependable, and defensible, and designed for pressure. Otherwise it doesn't matter how impressive it sounds. Since LighthouseIQ launched, a lot of questions I've been hearing are less about what it is and more about how it's different and why it was built the way it was. Lighthouse has been working with large language models and applied AI well before this technology became a headline. That gave us time to focus on the work behind the scenes, tuning models to handle real world scale, dialing in precision through continuous refinement, and building the safeguards that make them trustworthy in practice. The result is a platform teams can rely on day in and day out. From a product perspective, LighthouseIQ is a purpose-built eDiscovery intelligence platform with two core parts: IQ Applications that address specific high value workflows and IQ fabric, which is the foundation that weaves everything together. The goal is straightforward, help legal teams understand their data faster, make better decisions and control costs without compromising quality or defensibility. Today LighthouseIQ includes four core production grade applications designed for scale, accuracy, and consistency. Each built specifically for real eDiscovery workflows and already in use on complex matters. They are: IQ Answers, which allows teams to ask direct questions of their data and get immediate reliable answers; IQ Case Strategy helps translate insight into action; IQ Review delivers high quality relevance and classification across large data sets with speed and repeatability; IQ Priv provides precise privilege identification and logging, giving teams confidence in their outcomes. Underneath all of this is IQ Fabric, which brings together three core capabilities: Processing that standardizes data at massive scale while preserving fidelity; Cognition that helps interpret content and surface meaningful insights; Orchestration that connects workflows, tools and teams so work moves forward smoothly. Together these capabilities turn raw data into real action at scale and speed modern eDiscovery demands. That's the thinking behind LighthouseIQ and how we're seeing it used today. To illustrate how this works practice, Stacy sat down with Bryan Marra from Arnold & Porter to talk about how they use LighthouseIQ. Hi Bryan. Hey Stacy. Good to see you. Why don't we start out by just sharing a little bit about your role at Arnold & Porter and the types of matters that you handle? So my practice focuses on merger investigations and second requests, antitrust conduct investigations from the government and also merger litigation and other antitrust litigation. My specialty is really driving the eDiscovery process - helping clients use technology to drive more efficient outcomes for them in eDiscovery in complying with these government requests. Why don't you share a little bit about your use of LighthouseIQ and how it's helped you with your clients. Sure. So I used IQ Case Strategy. It was an antitrust litigation and we were facing trial in federal and state court in a matter of months. It was a very aggressive deposition schedule. We had over 30 depositions coming up in a matter of weeks and we had a production population of over 23 million documents to look through. So how are we going to tackle that? We could have done this the old fashioned way - hired an army of contract attorneys or used firm attorneys to basically sift through millions of documents, maybe used search terms to winnow it down, but then look at the results. It would've taken a long time. But instead, we used IQ Case Strategy. So we worked with a small team of experts, linguists, technologists, and we trained them on basically what they were looking for in terms of documents, what the case themes were about the witnesses, and they started delivering documents to us in a week. They kept up a weekly schedule, basically, to keep up with the depositions. They ultimately did depo prep kits for over 30 depositions and it worked well. Out of 23 million documents, they surfaced thousands of the key documents and they surfaced them early enough for us to get insights and use them for prep in advance before the depositions. You mentioned using linguists and our Lighthouse team. How did pairing Lighthouse expertise with our LighthouseIQ technology help have a better outcome for you? The team we worked with, they basically developed classifiers and linguistic models using your technology to essentially identify key documents and it ended up being a really a seamless process. We thought the documents they came up with were relevant and were key documents and we thought it was an excellent use case. Maybe share a little bit, what was the biggest impact of using LighthouseIQ? It was definitely the cost and time saving that was involved. I mean, we basically avoided having to do a massive document review effort, which would've cost the client a lot of money. And so by using this technology, we were able to short circuit having to do that and do things in a more efficient and focused way to get actionable intelligence that we could use right away with our depositions and for the litigation strategy. So now that we've rolled out other applications, I know you've used some of them, but what are your overall thoughts of using LighthouseIQ more broadly in the future? I definitely see use cases to use more of LighthouseIQ technology. I mean, how I use AI is really to make eDiscovery more efficient for my clients - to save money, to do things in a more focused way. I can see use cases for IQ Answers. I'm looking forward to using that application for early case assessment to help clients find out what's in their documents at an early point and to help focus the case strategy ahead of time. Maybe share a little bit more about how early insights really help you and your teams. Definitely. So in merger investigations, finding out what's in your documents at an early point can be crucial. Oftentimes you produce like a million documents to the government and you don't really know what's in them ahead of time, but if you can know what's in your documents at an early point, it can really help you drive case strategy ahead of time. I know you've used it on some large matters, but think about how would you use it on small matters or how you're thinking about the use of AI in the future. So I think size isn't really the main factor. Clients are always looking to save money and they're always looking to find out more intelligence about their documents at an early point. And I think even in smaller matters, smaller investigations, this could be a way to see what's in your documents at an early point to drive case strategy. I look forward to using IQ Answers to do that. What I've seen of it, it looks great and I think will help me in my practice for my clients. That's great. Why don't you share a little bit about how you think about the use of AI in your practice? Really, AI helps you move from broad-based review solutions towards more focused actionable intelligence and that's what we're trying to do in my practice - to help clients use technology to find out more about their documents ahead of time to get through what would've been a massive costly undertaking much faster and more efficiently by using AI. And that's how I see my role, is sort of being someone that uses this technology to drive these outcomes for my clients. Thank you so much for your time, Bryan. Really a pleasure to have this conversation with you. It was great speaking with you. Wow, that was a great conversation. What Bryan described is a model where intelligence comes first, giving your team flexibility before committing to full review. Iram, help us understand how LighthouseIQ was designed to support that approach as platforms continue to evolve. Customers are rightly asking two related questions: What happens with the retirement of Relativity Server in 2028? How will they reduce risk when changing something as central as a review platform? Our answer is straightforward. We reduce this risk by moving intelligence earlier in the lifecycle. So the choice of review platform matters far less than it does today. LighthouseIQ is designed to manage this transition seamlessly. It does not force workflow changes and it does not require customers to retool how they operate. Matters continue to move through LighthouseIQ without a dependency on Relativity Server because the platform is not tied to any single review tool or even to the assumption that documents must be reviewed in a traditional system at all. That flexibility is deliberate. Customers can choose how and where they review documents, if they choose to review them. LighthouseIQ sits above those decisions, providing consistent intelligence regardless of the tools underneath. And to be clear, we remain fully committed to Relativity and will continue to offer RelativityOne as a review option when it's the right fit for a matter. What fundamentally changes is where value is created. That shift is what gives customers more control, more optionality, and far less risk as the ecosystem evolves. With that context, it's more meaningful to hear how this plays out in practice. So next you'll hear directly from Eric Wieder at Baker Botts about how LighthouseIQ is helping their teams navigate these changes and deliver better outcomes on real matters. Hi Eric. Thank you so much for joining us today. I'd love to just hear a little bit about your role at Baker Botts and the type of matters that you oversee. Absolutely. So I am Senior eDiscovery Council at Baker Botts. I've been working in the eDiscovery industry for over 20 years and my role is across the spectrum of the EDRM from collection through production with a focus on review and I've managed many large second requests, multi-district litigation, both civil and criminal cases. I wanted to start out talking about Relativity and the announcement of Server going away in January, 2028 and curious, how does that operationally affect your team and how you think about eDiscovery? So in terms to the transition from Server to RelOne, we're not looking to replace Relativity. We're looking for an AI platform that will extract intelligent data from our clients and seamlessly integrate into Relativity for the benefit of our matter teams. This is what LighthouseIQ does. So tell me a little bit more, expand on that, on how LighthouseIQ will help you with that transition. LighthouseIQ gives us more control over when and how we're going to review the data. It used to be you collect the data and you review it linearly. LighthouseIQ gives us the chance to break it up into parts and review in a prioritized way to the benefit of the case. You've used IQ Priv for some of your cases. Can you share a little about that experience and how it's helped you? Yeah, so we have used the GenAI component of IQ Priv to assist us with our privilege log. As you know, the burden of preparing a privilege log is costly and expensive for our clients. We've been able to use the GenAI tool to more efficiently review documents and then perform a heavy QC so that we could submit a log that is less likely to be contested by the regulators. I understand you've used IQ Answers for some of your matters. Can you just elaborate a little bit more on how you've used it and how it's helped support your team? We have used IQ Answers on two different matters. One a second request, a second one a criminal litigation. In both instances, IQ Answers was very helpful in getting to the question of particular issues quicker than you would normally do just searching a Relativity database. Using an iterative process, we were able to get to the answer for the matter team in a short amount of time. Eric, it's been great spending time with you today. Thank you so much for sharing your experiences with us. Really appreciate you and appreciate the partnership with Lighthouse and Baker Botts. My pleasure, thank you. Wow, another insightful conversation. What Eric just described reinforces that this isn't about swapping platforms, it's about moving intelligence earlier so your teams are much less dependent on the review tools, or norms, at any one point in time. Iram, as you look ahead to 2028 and beyond, bring this all together for us. What does this shift really mean for legal teams as we look ahead to the future? Thanks, Stacy. What it comes down to is when legal teams get clarity. What you heard from Eric around IQ Answers is about getting meaningful insight earlier, while there's still time to shape strategy and make better decisions. When teams understand their data sooner, they can narrow scope, focus on what actually matters, and move forward with a far more confidence. That early clarity changes everything that follows. Decisions are more deliberate, costs are easier to control, and teams spend their time acting on insight instead of searching for it. That's the value of early intelligence and that's the direction we're building toward with LighthouseIQ. Hi Karl. Hi Stacy. How are you doing today? Good. It's good to see you. Good to see you too. Thanks for spending a little time with us today. Why don't you start out by telling us a little bit more about your role at Kirkland & Ellis, and the types of matters that you handle? Yeah, I'm a partner at Kirkland. My practice really involves the intersection of traditional discovery, preparing documents for production, meeting discovery obligations and the like, and preparing case strategy, digging into the facts, understanding what those documents all show largely in the mass court context. So large, very high-value litigation where facts and understanding the facts is really important. So you just talked a little bit about case strategy, I'd love to hear more about how you've used IQ Case Strategy. In litigation, it's really important that we understand what's in the materials, especially early on in the case. It's important to develop case strategy that's based on the actual evidence, based on the actual facts. We've, for a long time, been partnering with the Lighthouse team and members of the Lighthouse team to help us weed through, cull through, the vast amount of material that often gets collected and produced in a case to really focus on what matters. It's important to be able to cull through those and really develop case themes, understand how particular issues are addressed in the documents, and then really leverage that information to be able to build out case themes, case arguments, develop our strategy for the case. And I think you've used IQ Case Strategy for depo prep in the past. Yeah, and we've actually in a number of our cases, really been able to leverage the deposition preparation to have our team focus on the substance of the case. Not spending time weaving through a hundred thousand documents produced for a custodian, but, focusing on the 100, 200, 300 that really matter the most for that person. It allows our team to focus on the substance as opposed to trying to figure out where in the vast universe of documents out there that information is. That's great. So maybe touch a little bit on how AI is changing how you handle your client work at Kirkland. Yeah, it's a really exciting time, I think for the entire field. I literally started in 2010 working on deposition prep where I had partners who printed off tens of thousands of documents on hard paper and we would sift through them, flipping through them and putting sticky notes on them. Since then, we've come a long way. The technology we have, especially with the evolving AI technologies, allows us to do more, more work and more effectively. Early on a case understanding what the materials are, what the issues are, what the evidence shows, what the document shows. We're able to build out better case strategies that help our clients, achieve their goals in litigation. So now that we've rolled out the full suite of applications under LighthouseIQ, I'm curious, beyond IQ Case Strategy, do you see yourself using some of the other tools that we've rolled out? We really do. We've really appreciated the IQ Case Strategy system and method for allowing us to do our work most efficiently and effectively for our clients. That said, I think with the advent of all the AI technologies and the implementation of those into the Lighthouse suite of tools that we've been talking about, we're really, really excited to leverage those materials and do more with them. In particular, IQ Answers, we're really excited to try out on our next case to really help our teams and allow our teams to leverage the information that we're able to glean most quickly from, again, a large set of documents. That's great. Karl, thank you so much for spending time with us today. We really appreciate your partnership. Absolutely. Thank you, Stacy. As we shared in January, we made IQ Answers available as a risk-free trial. IQ Answers is built on a simple promise: ask anything, get accurate answers. It allows teams to extract insight immediately before committing to a full review. In just the past few weeks, dozens of customers have already applied it to millions of their own documents. To show you how that works in practice, I'd like to bring in Cassie Blum, our Senior Director of AI and Analytics. She'll walk through a brief demonstration. Imagine you are an attorney general suing a pharmaceutical company that manufactures a synthetic opioid spray and you're alleging racketeering. You've received 1.5 million documents in production and your team has three weeks before the next case management conference. Traditional review would've meant that you would spend months and likely millions of dollars to interrogate your data. Let's see what IQ Answers can do in the next several minutes. First off, I'm gonna just ask general questions within my dataset, to get a sense of what was going on with this product, who it was prescribed for, and what was happening with those prescriptions. So I'm typing a question about that generally to see what that returns for me. You'll notice here at the end of the query that you get an overall answer, but you also get topics surfaced for you along with citations that match each of these topics that highlight the particularly important parts of the document that can help lead you to the conclusions that are surfaced for you with IQ Answers. So here we see that this was a spray that was approved for breakthrough cancer pain and that that was the FDA intent of the approval. But what I'm also seeing in these topics that is being surfaced for me is that a lot of off-label prescription for non-cancer pain is apparently going on with this product. And I can tell that from these particular documents that I've clicked on here along with the citations where I'm seeing a hundred plus prescriptions a month that are off-label. Well that's interesting. Now I'm also seeing that the salesforce has been explicitly instructed to prioritize high volume opioid prescription writers, regardless of their specialty and regardless of what's happening with that prescription. And I can click into the documents and see that the volume is what is driving here. And then I also can look and see that there's been awareness internally that the approved indication from the FDA is not actually matching the patient population. So that's very interesting. It seems like we definitely have some use here that it was not intended and I could figure that out in about 30 seconds in IQ Answers; I have the foundation. So if the drug is approved for cancer pain, but the company is deliberately targeting non-cancer patients, that's definitely a gap from the FDA approval. And so let's understand how they're going about making this happen. How are they getting doctors to keep writing these prescriptions? I'm gonna go ahead and ask an additional question of IQ Answers to figure out what they're doing to get this volume of prescriptions written. In particular, I noticed that there was something about speaker engagements that they were doing with doctors. So I'm gonna ask about those speaker engagements. You'll see here that basically the speaker engagement program was a way for them to pay doctors for prescriptions. I can see that they were tracking the ROI of those speaker payments as compared to the amount of prescriptions a doctor was writing. And I can also see from the documents and the citations that if they did not feel that a doctor was writing enough prescriptions, they were no longer part of these speaking events, and thus paid through these speaking events. I also see these speaking events are not really genuine educational activity and it looks like the company was aware of this and was terminating doctors when they were not writing enough prescriptions to satisfy the amount of money that they were giving the doctors. So this all does not look very great for them in terms of how these programs were essentially bribery of these doctors. So, if they're bribing the doctors, that still doesn't answer for me what's happening with the insurance companies. The product costs thousands of dollars a month and insurance companies wouldn't just approve that without any questions. So Vantage clearly needed a way to get these insurers to pay. Let me ask about that. I'm gonna type in a question about their programs to deal with the insurance companies and the way in which they instructed their employees. All right, so now I see in my answer that they had created what was called a Vantage Reimbursement Center that was essentially their way of tracking the approvals from the insurance companies. And it looks like from the topics that's being surfaced here, that they were also using it as a vehicle to instruct their staff on how to deceive the insurance companies. In particular here, you can see in this document where they talk about using particular types of language, lingo, or diagnoses to get the insurance companies to approve the use of these drugs for the written prescriptions. But it also looks like they know that these are false statements that are being made when they are talking with the insurance companies. You can see here they're tracking and they want a 100% authorization success rate. So they're essentially giving all of their employees the way to beat the system and to cheat the insurance company and to get them to approve something under false pretenses. So, I now have two parallel fraud streams that are emerging here. One to bribe doctors to write prescriptions, one to deceive insurance companies to pay. For a RICO case I also need to know that this was coming directly from management and from the top. So let's see if I can find that out in the dataset and ask a question about that to help me win my conviction. Alright, so now I'm gonna ask in particular, what evidence do we have that the CEO knew about this speaker program and this insurance program? Now that I'm asking this of the documents, what I can see here that is surfacing is that in fact the CEO did have direct knowledge and there's multiple documents that substantiate this. And in particular you can see this one here where he personally directs a speaker fee increase that is tied to prescription volume. In this document, you would have him talking about different tiers of speaker programs and that someone is no longer going to be invited to be a part of these speaker programs if they are not writing a certain amount of prescriptions. There's one here that surfaces a document where a hundred percent of the authorization success rate is something that he is directing and he's also calling for in the data. You also see here that I have additional follow-up questions that I can be asked that are being surfaced by IQ Answers that will help me investigate and interrogate each one of these particular questions and the information I found up in these questions. But overall, it looks like I, in a matter of minutes, have been able to find key documents and important fact timelines that help me substantiate my case and know that I have a good chance of success moving forward and make me feel set up really well for my next case management conference. Stacy, I'm gonna send it back over to you. Thank you, Cassie. Given the strong response we've seen, we are extending the IQ Answers risk-free trial. If you'd like to get started, visit iq-answers.com and explore how it can help your team surface insight earlier, narrow scope faster, and make more confident decisions. And if you'll be at Legalweek, we'd welcome the opportunity to connect in person and talk through how LighthouseIQ can support your matters and your priorities. And if not, we're also happy to set up time to meet with you at your convenience. Thank you again for spending time with us today, and we look forward to continuing the conversation.

Join Lighthouse Senior Director of AI & Analytics, Cassie Blum, for a quick demo of IQ Answers inside of LighthouseIQ. Today, I'll show you how LighthouseIQ transforms your entire workflow. For this time together, we'll focus on trial and deposition prep from high level research to comprehensive interview kits. I wish I had time to show you all of LighthouseIQ, but today we're going to focus on IQ Answers and IQ Case Strategy. Let's just dive right on into Lighthouse IQ Answers. I am trying to get an early assessment of what's in my data. Specifically, how did one of my custodians interact with the subject matter at dispute? So I have custodian Jane Hopper that I would like to know what her involvement was with that campaign. So I'm going to type in this question. What was Jane Hopper's involvement with JUUL's youth marketing strategy and appeal to minors? And when we talk about how it analyzes your data, IQ Fabric is doing something proprietary that's a little different from other tools on the market that helps with both its accuracy and its scale. The way in which specifically that we chunk the data for analysis is unique to us in that we make sure with our proprietary chunker, that we are not cutting through sentences or themes. That we are leaving those intact for when we are doing the underlying query. The other thing that it's doing for you is it's surfacing follow up questions for you. So you'll see here I have additional lines of inquiry I can undertake now as a result of what has surfaced in this original question that I queried. So now if I click ask in these, it will run that question for me. And similarly, I now have those results returning to me with document IDs, with highlighting and with citations in the particular record. Now let's switch to IQ Case Strategy. This is the stage of your case where mistakes and miss data cannot happen. It's critical for your frontline litigators to be armed with all the proper data and insights for your matter. So continuing to inquiry Jane Hopper's data set, I'm now inside of the deposition summary for this particular custodian. You'll see here that I not only have a summary, but I have several other important artifacts that are going to help me navigate my trial prep. I have topics that have also been surfaced, and so if I look at these topics, I can click into them and I can see a chronological summary of the key events in this topic. I can also see who is communicating about it. And, if I want to learn even more about those communicants, I can click into our communications widget where I see not only who these folks are and what the particular discourse was, but we see sentiment in here as well. I also have the ability to add a note or a transcript here if I'm collaborating with others in my case or just for my own purposes of preparation. And as with all things in LighthouseIQ, we also have the ability to use AI with natural language query to ask a question of the dataset. It is really a whole ecosystem that will let you interact with your data. And there you'll see, and I've typed in, did Jane Hopper express concern about JUUL's compliance with youth prevention playbook for international marketing? And again, I will see that an answer is returned for me that helps me get additional insight into that from this deposition. This is just a little bit of what you can see in LighthouseIQ. Hopefully you get a flavor of what's possible with IQ Answers and IQ Case Strategy.

Introducing LighthouseIQ: A next-generation intelligence platform and AI application suite designed to provide legal and compliance teams with earlier insights, regulatory defensibility, and significant cost savings.Learn more about LighthouseIQ.Transcript:In every matter, there's a moment that changes everything. The moment information turns into understanding the moment, every decision becomes clearer, faster, the moment you connect with confidence. At Lighthouse, that moment is what we build for.We innovate with purpose to empower legal teams to act with clarity and confidence.We deliver value today while shaping what comes next, and now we take the next step together. Hello and welcome. Thank you for joining us today.I'm Stacy Ibarra, chief Marketing Officer at Lighthouse. We are thrilled to have you join us for the announcement of our battle tested platform that is truly groundbreaking, one that will drive significant new business value for you. A true game changer.Lighthouse has taken advantage of advancements in AI and large language models to provide you with a solution that gives you continuous innovation insight the moment you need it, with no limits to speed or scale, it is secure, trusted, and already regulator approved. Here's what you can expect in today's webcast.First, you'll hear from Lighthouse CEO Ron Markit, Ron Mul unveil how Lighthouse is bringing the power of AI to you in a way that is grounded in real workflows and real results. We'll share a demo that shows how we deliver insight the moment you need it. I'll also speak with two of our clients who are already putting this into practice on complex matters, under real deadlines and real scrutiny.And we'll close by sharing how you can experience this firsthand through an opportunity to trial one of our applications. And with that, I'll turn it over to Lighthouse, CEO, Ron Marcus. Thank you Stacy, and thank you all for joining us.I'm Ron Markezich, CEO of Lighthouse. Before joining Lighthouse three years ago, I spent 27 years at Microsoft.The bulk of my time at Microsoft was helping build and scale Microsoft 365. I joined Lighthouse because I saw a huge opportunity to create more value for the eDiscovery industry. Through both great expertise at Lighthouse and an awesome AI based technology platform that existed.Lighthouse is a pioneer with large language models and ai. Before AI became headlines everywhere. Over the last three years, we've been putting that AI foundation to work, refining it, pressure testing on real matters, and deliberately building towards this moment.Today we're announcing availability of LighthouseIQ. LighthouseIQ is where intelligence meets performance.It's a purpose-built eDiscovery intelligence solution made up of two core layers IQ applications designed to address your specific business needs and IQ fabric as the foundation that weaves everything together. LighthouseIQ is built to accept data from any source system because you always own your data. In LighthouseIQ, we're committed to meeting you exactly where your business needs require.LighthouseIQ is designed to help legal teams understand their data faster, act smarter and save money. LighthouseIQ embeds intelligence and all you do to make new opportunities possible Today, LighthouseIQ includes four applications designed specifically for eDiscovery workflows. These applications work seamlessly together and are already proven on some of the world's largest and most complex matters.These are not chatbots. They're production grade AI powered applications.IQ Answers allows you to ask anything of your data set and receive immediate accurate answers. IQ Case Strategy helps you create sharper strategies and smarter actions because we know inside alone doesn't win cases Action does. IQ Review delivers reliable relevance and high quality classification at scale and speed across your entire data.Corpus IQ Priv generates precise privilege identification and logging given you confidence in your outcomes. This is intelligence that works at the moments you need it. IQ Fabric is the foundational element of LighthouseIQ that weaves everything together into one solution.The power of IQ Fabric comes from three innovative capabilities. Processing standardizes at massive scale preserves fidelity and handles every data format cognition so you can quickly and accurately interpret content.Surface key insights and deepen understanding of your data. Orchestration connects workflows and coordinates tools and teams to power seamless execution. Together these capabilities turn raw data into real actions at any scale and speed your business demands.Enough of me talking. Let's show you. I want to introduce Cassie Blum, a senior director at Lighthouse who has been bringing LighthouseIQ to life for clients.Thanks, Ron. Today I'll show you how LighthouseIQ transforms your entire workflow. For this time together we'll focus on trial and deposition prep from high level research to comprehensive interview kits.I wish I had time to show you all of LighthouseIQ, but today we're gonna focus on IQ Answers and IQ Case Strategy. Let's just dive right on into LighthouseIQ answers. I am trying to get an early assessment of what's in my data.Specifically how did one of my custodians interact with the subject matter at dispute? So I have custodian Jane Hopper that I would like to know what her involvement was with that campaign. So I'm gonna type in this question.What was Jane Hopper's involvement with Jules Youth marketing strategy and appeal to miners? And when we talk about how it analyzes your data, LighthouseIQ Fabric is doing something proprietary that's a little different from other tools on the market that helps with both its accuracy and its scale. The way in which specifically that we chunk the data for analysis is unique to us in that we make sure with our proprietary chunker that we are not cutting through sentences or themes that we are leaving those intact for when we are doing the underlying query.The other thing that it's doing for you is it's surfacing follow up questions for you. So you'll see here I have additional lines of inquiry I can undertake now as a result of what has surfaced in this original question that I queried. So now if I click ask in these, it will run that question for me.And similarly, I now have those results returning to me with document IDs, with highlighting and with citations in the particular record. Now let's switch to IQ Case Strategy. This is the stage of your case where mistakes and miss data cannot happen.It's critical for your frontline litigators to be armed with all the proper data and insights for your matter. So continuing to inquiry Jane Hopper's data set, I'm now inside of the deposition summary for this particular custodian. You'll see here that I not only have a summary, but I have several other important artifacts that are gonna help me navigate my trial prep.I have topics that have also been surfaced, and so if I look at these topics, I can click into them and I can see a chronological summary of the key events in this topic. I can also see who is communicating about it. And if I want to learn even more about those communicants, I can click into our communications widget where I see not only who these folks are and what the particular discourse was, but we see sentiment in here as well.I also have the ability to add a note or a transcript here if I'm collaborating with others in my case or just for my own purposes of preparation. And as with all things in LighthouseIQ, we also have the ability to use AI with natural language query to ask a question of the dataset. It is really a whole ecosystem that will let you interact with your data.And there you'll see, and I've typed in did Jane Hopper express concern about JUULs compliance with Youth Prevention Playbook for international marketing? And again, I will see that an answer is returned for me. That helps me get additional insight into that from this deposition.This is just a little bit of what you can see in LighthouseIQ. Hopefully you get a flavor of what's possible with IQ Answers and IQ K strategy, iq, priv, and IQ Review are incredibly powerful as well. We'll have clients here in a bit that have used all four applications who will share more.We'd also love to follow up to show you the full set of LighthouseIQ capabilities when you have time. But for now, I'll send it back to Ron. Thank you Cassie.I always love seeing how LighthouseIQ can empower our clients. What makes LighthouseIQ different is not just the technology, it's the expertise behind it. We have a seasoned team of eDiscovery professionals.Lighthouse averages under 8% annual attrition, which is excellent for any industry, but that also means our teams remain consistent and committed to your business to serve your needs. That expertise shows up for clients every single day because we know technology alone does not deliver successful outcomes. Lighthouse also remains committed to Relativity as a core part of our platform, relativity is a common review platform for the clients we serve.Our strategy is not to disrupt what already works. It is to enhance it. We will continue our strong partnerships in tight integration with Relativity.Ensuring LighthouseIQ delivers intelligence fully integrated with Relativity. We built LighthouseIQ to support the most complex client needs while also scaling seamlessly to small matters so you can trust one platform for all of your eDiscovery work to earn that trust. LighthouseIQ is modern by design as we keep innovating, incorporating both Lighthouse technology and leading innovation from across the industry.So the platform is always improving and you are not locked in to any one single software provider. It's built for early intelligence so you don't have to wait for documents to move through an entire workflow before gaining insight. You can get intelligence immediately because we serve some of the world's largest and most complicated matters.It was important to ensure LighthouseIQ has unlimited speed and scale. There are absolutely no limits on the number of documents in your matters or meeting your aggressive deadlines. We also know how important it is for LighthouseIQ to be secure, trusted, and accepted by regulators.So we made this solution defensible by design from the beginning. As I mentioned earlier, LighthouseIQ has been battle tested on some of the world's largest and most complex eDiscovery matters. To date, we've analyzed over 1.4 billion documents with LighthouseIQ, including multiple matters exceeding 25 million documents.In fact, we have had a recent matter with 33 million documents analyzed by LighthouseIQ in hours not days. There are no limits to our scale and we will help you meet the most aggressive of your deadlines. And yes, LighthouseIQ has been accepted by the FTC and DOJ, but don't just take it from us.Stacy will come back and speak with a couple of our clients about their experience with LighthouseIQ. Welcome back Stacy. Thanks Ron.We've been fortunate to have industry leaders involved in the development of these products. They've helped guide and shape LighthouseIQ. They've been generous enough to share their time to tell us how they've used LighthouseIQ.I had a chance to sit down with Robert Keeling at Redgrave. He's been in the industry for over 20 years and brings a lot of experience. Hi Robert.I know you're a super busy guy. You've got lots going on at Redgrave. I really appreciate you taking the time to come talk about LighthouseIQ with us today.Oh, thank you. Happy to do so. We have, several matters ongoing with you guys where we're using the LighthouseIQ tool in real time, so I'm excited to talk about it.I know, I think you were coming in earlier with your phone already talking about a matter with one of our, our team members. Yes. I happen to be, on a call with one of your colleagues right before this about about a matter that I'm working with you guys on.so yes, look, looking forward to our discussion. Tell us a little bit about your role at Redgrave. Yes, I'm co-managing partner at Redgrave.and in my practice I work with clients across a range of industries, on their litigations and white collar matters. specifically I partner with Merits counsel and we handle the discovery, both the document review, the privilege review process, and more technical aspects of discovery, for our clients, to try and make the discovery process as efficient and as effective as possible. Great.Congratulations on your new title, by the Way. Thank you. I appreciate it.Why don't you tell me a little bit about your experience using IQ proof? Obviously using the tool to identify privileged communications is really effective and we've had a lot of success. But equally effective is using the tool to help identify what documents are not privilege.And that can really make a review much more efficient, much more effective. For example, we can take documents that they may hit on common privileged generic terms like, like privilege or, or, or legal, but we then look to see, well, what does the Priv IQ tool say about these documents?And if the tool is saying these documents are are not privileged or unlikely to be privileged, we don't review those documents. and instead we'll just have them go out the door without human review, which significantly decreases the overall cost of the radio. Why don't you tell me a little bit about using the tool for priv logging?Yes, we've been working with the Lighthouse team, for IQ for logging now for over two years. and at present, the the technology I would say is rather remarkable. It is, at least as comparable to human review, for creating log entries.I personally think it's superior to human review when that review is set up to have a dropdown or so-called pick list for all options of the prologue in including after the reline. And so what we've done is we worked with the Lighthouse team to have the IQ footprint tool create log entries, for real matters, that have gone out after QC from us, but otherwise without the involvement of a large contract attorney team, which has really replaced a substantial pain point for the discovery process, privilege logging is oftentimes one of the most expensive and tedious parts of discovery. And having a tool like IQ for PRIV replaced that, at least on the human side has, is really I think a significant game changer for us and has led to a lot of efficiencies for our clients.Love to hear your experience with IQ Review and also what difference it made in knowing that this approach has been approved by the FTC and DOJ. I have deep experience with the IQ four review tool. It is the tool of choice when we're working with Lighthouse on second requests, both before the DOJ and the FTC.the FTC and DOJ routinely approve use of IQ four review on second request matters, and we've had good success employing them across very large billion dollar. Second request matters that have been very complex and detailed where we've had to comply on tight timelines. I know you've used IQ Answers in the past.I'd love to hear your experience with that and outcomes that you've been able to achieve. So IQ Answers has been really helpful for us in several matters. For example, we had a matter where we had to respond to very detailed interrogatory requests, and we did, I had very detailed responses.after submitting them though, the receiving party threatened to go to the court on us because they said that we had not cited any documents in our responses. So very quickly we worked with the Lighthouse team and the IQ Answers tool and used the IQ Answers tool, to essentially identify documents relating to each of our interrogatory responses. We basically fed the interrogatory into the tool and our answer, and it provided numerous documents that would support our answer.We then, supplemented our interrogatory responses with the documents identified by IQ Answers and avoided any, court involvement or a motion to compel. So it was a very successful, use of the tool. That's great.It's so great to hear how our clients are using and benefiting from LighthouseIQ. CJ Mahoney, a partner at Cleary Gotlieb has also been using the LighthouseIQ tools. Hi cj.Hey Stacy. It's good to see you. Well, you've had a good year this year with the bills in the playoffs and Miami and the national championship.It's been pretty good. just made partner this year too. But, Miami's probably the most important one of those three things Partner's pretty important to you.So why don't you introduce yourself and tell us a little bit more about your role and the matters you handle at Cleary. Sure. I have been the head of Cleary's eDiscovery Group for a number of years now.I have been at Cleary for about 20 years leading a team of over a hundred attorneys. We handle very large antitrust matters, litigations, other types of government investigations. We are dealing with really large data sets.And so our partnership with Lighthouse is incredibly important to us. Together, we've built a lot of great, tools and especially AI tools to help us, manage a lot of the challenges of these matters. So tell me a little bit of how you've used IQK strategy.Yeah, so, case strategy is really important for us at the start of matters. Prior to, a tool like this, we didn't really have an efficient way to get to key documents early that might make a difference in how we approach the case From a strategic perspective. With case strategy, we now have a much more efficient solution than manual review and boole and search terms to arrive at a really precise, useful population of key documents that helps us understand how to proceed in the case.A big example for me from the past few months is a contract dispute. our client had a dispute with one of their customers regarding cancellation of a contract. Our client felt that they had damages under the contract for the cancellation, but they wanted us to test their theories of damages.They also wanted us to use information from their dataset to help substantiate their damages claimed and arrive at a calculation using, case strategy. We were able to ask a number of prompts, arrive at some really good reporting and a population of around 6,000 documents to, review to substantiate that claim and to arrive at a damages calculation that's backed up by data. We actually benchmarked that against older standard processes and what a review would've looked like without case strategy and found that we would've had to review at least five times the amount of documents.So the savings are huge, but it's not just about the savings. We are actually able to find information that we probably would not have found without search terms. And, today's a huge day for us because just today, this matter settled, thanks to the work we did in case strategy.Our client was able to obtain really favorable monetary settlement. and as importantly, they were able to avoid, the court process in order to get that settlement. What a fantastic outcome.Yeah, it was really great. Would love to hear your experience with IQ Answers and how it's helped you solve big problems. We used IQ Review to arrive at a really precise production set.we were able to achieve nearly 90% precision. so much better than you would expect from traditional human review. But it does leave the issue of, okay, I've got this corpus of responsive documents.I now need to know what's in there as I'm making productions. We were getting pressure from the government regulator to make productions very quickly. So we were trying to identify portions of that responsive set, that could go out without any worry that we are producing concerning documents without fully understanding them.We ran these prompts over potential productions and we're able to identify many documents that were potentially concerning and hold them back from production. While we considered their importance, this was extremely meaningful to the client because although we eventually have to produce those documents, we really want to be able to understand and tell their story to the opposing party at the time of production. Thank you so much for your time, cj, thank you for the partnership.Well, thank you for the partnership. always happy to speak about our great experiences with Lighthouse. Thank you Robert and CJ for sharing your experience with us.As you heard, LighthouseIQ has already been battle tested on some of the largest and most complex matters in the world. The perspectives you just heard bring that proof to life and show what is possible when intelligence is brought forward and paired with experience. To understand the value of LighthouseIQ, we want you to experience it firsthand.The best way to do that is through IQ Answers, which we are making available through a risk-free trial for qualified clients. This allows you to see how quickly you can surface insight, gain clarity, and move forward with confidence on your next matter. There is no risk and immediate value.You can begin uncovering meaningful insights in minutes to get started. Visit IQ Answers.com. Well again, thank you for spending time with us today.We are excited about the benefit you'll receive from LighthouseIQ and we look forward to partnering with you.

Hear what Robert Keeling, Partner at Redgrave, has to say about LighthouseIQ in this interview with Lighthouse CMO, Stacy Ybarra. We have, several matters ongoing with you guys where we're using the LighthouseIQ tool in real time, so I'm excited to talk about it. Yes, I'm co-managing partner at Redgrave in my practice, I work with clients across a range of industries, on their litigations and white collar matters. specifically I partner with merits counsel and we handle the discovery, both the document review, the privilege review process, and more technical aspects of discovery, for our clients, to try and make the discovery process as efficient and as effective as possible. Obviously, using the tool to identify privileged communications is really effective and we've had a lot of success. But equally effective is using the tool to help identify what documents are not privileged. -. And that can really make a review much more efficient, much more effective. IQ Answers has been really helpful for us in several matters. For example, we had a matter where we had to respond to very detailed interrogatory requests, and we did, had very detailed responses. after submitting them though, the receiving party threatened to go to the court on us because they said that we had not cited any documents in our responses. So very quickly we worked with the Lighthouse team and the IQ Answers tool, and used the IQ Answers tool, to essentially identify documents relating to each of our interrogatory responses. We basically fed the interrogatory into the tool and our answer, and it provided numerous documents that would support our answer. We then, supplemented our interrogatory responses with the documents identified by IQ Answers and avoided any, court involvement or a motion to compel. So it was a very successful, use of the tool.

Hear what Christian J Mahoney, Partner at Cleary Gottlieb, has to say about LighthouseIQ in this interview with Lighthouse CMO, Stacy Ybarra. I have been the head of Cleary's eDiscovery Group for a number of years now. I have been at Cleary for about 20 years leading a team of over a hundred attorneys. We handle very large antitrust matters, litigations, other types of government investigations. We are dealing with really large data sets and so our partnership with Lighthouse is incredibly important to us. Together, we've built a lot of great, tools and especially AI tools to help us, manage a lot of the challenges of these matters. Case strategy is really important for us at the start of matters.Prior to, a tool like this, we didn't really have an efficient way to get to key documents early that might make a difference in how we approach the case. From a strategic perspective with case strategy, we now have a much more efficient solution than manual review and boole and search terms to arrive at a really precise, useful population of key documents that helps us understand how to proceed in the case. A big example for me from the past few months is a contract dispute. our client had a dispute with one of their customers regarding cancellation of a contract. Our client felt that they had damages under the contract for the cancellation, but they wanted us to test their theories of damages. They also wanted us to use information from their dataset to help substantiate their damages claimed and arrive at a calculation using, case strategy.We were able to ask a number of prompts, arrive at some really good reporting and a population of around 6, 000 documents to, review to substantiate that claim and to arrive at a damages calculation that's backed up by data. We actually benchmarked that against older standard processes and what a review would've looked like without case strategy and found that we would've had to review at least five times the amount of documents. So the savings are huge, but it's not just about the savings. We are actually able to find information that we probably would not have found without search terms. And, today's a huge day for us because just today, this matter settled. thanks to the work we did in case strategy.Our client was able To obtain really favorable monetary settlement, and as importantly, they were able to avoid, the court process in order to get that settlement. We were getting pressure from the government regulator to make productions very quickly, so we were trying to identify portions of that responsive set, that could go out without any worry that we are producing concerning documents without fully understanding them. We ran these prompts over potential productions and were able to identify many documents that were potentially concerning and hold them back from production. While we considered their importance, this was extremely meaningful to the client because although we eventually have to produce those documents, we really want to be able to understand and tell their story to the opposing party at the time of production.

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