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Like most cloud-based productivity platforms, Google offers solutions for both home and business environments. Free for personal use applications such as Gmail, Google Docs, and Google Drive deliver a rich set of communication and Office-like functionality that have near feature parity with their commercial corporate-focused G Suite counterparts. From the perspective of evidence acquisition in the civil arena, we find a significant number of organizations bypassing the conventional Microsoft stack in favor of G Suite. These organizations tend to operate in the technology space including biotech, electronics, engineering, and all flavors of “garage” startups.While cloud platforms enable a limitless world of collaboration and information storage, they also introduce an alternative set of metadata that can trip up seasoned examiners and eDiscovery practitioners. This can be particularly problematic for metadata dates. Historically, determining the date of a file that moved between computers is quite simple; however, arriving at the “best” date for any given piece of cloud evidence can be a subjective exercise and is limited to metadata exposed and potentially altered by the cloud platform. In the following post, I’ll dive into how this issue arises so that practitioners and analysts can use the most accurate evidence date for their eDiscovery needs. A “document” in Google Docs is simply a set of records and field values stored in a database. This departs from the traditional concept of a document being contained in a stand-alone file on your computer’s desktop. Currently, to be reviewed alongside traditional ESI, a Google Doc (ie, a spreadsheet or presentation) must be pulled from Google’s database, converted into a traditional document file, and downloaded for processing and review.Thus, the handling of dates can become an issue for documents within G Suite. If a Microsoft (MS) Excel document is created by a user on their laptop, uploaded to Google Drive, edited in place, and then later downloaded for eDiscovery purposes, what is the document’s date? A typical MS Office (Excel, Word, PowerPoint, etc) document has three dates assigned by the file system (think: my laptop’s hard drive): Created, Modified, and Accessed. It also has up to three dates “embedded” inside the file itself: Created, Modified, and Last Printed. What happens when the Excel file makes a round trip to Google and back? With so many dates to choose from, it’s tough to pick just one!Before the upload to Google Drive, here are the file system dates for our MS Excel document. Notice that the file system is telling us the document was created on June 30, 2020, at 11:33 AM.And here are the embedded “application” dates. Note that “Date last saved” is essentially a “modified” date, and this document has not yet been printed. By looking at the application-level dates, we can also tell that the file was actually created at 11:04 AM, and then copied to its present location at 11:33 AM.After uploading to Google Drive, Google will assign its own Created and Modified dates to the item. You’ll notice in the graphic below that Google’s displayed Modified date of June 30 at 1:36 PM matches the Modified date of the original file. So far so good! But, take a look at Google’s recording of the Created Date: it’s been set by Google to simply “11:23 AM” on the date of the upload action (July 10, 2020.) Notice also that Google indicates the document was created “with Google Drive Web.”Now, let’s make an edit to the Excel file. There are two ways to accomplish this in Google Drive: 1) you can edit the document “in place” using Google Docs without abandoning the original MS Excel format, or 2) you can do a “Save As” and convert the document into Google Sheets format. In this example, we are going to use method #1 and make a couple of edits to our MS Excel file. Google Docs immediately auto saves the file for us. Let’s look at the dates.After editing in Google Drive, but leaving as Excel format, you’ll notice in the graphic below that Google’s Modified date has been changed to the time of the edit. This makes sense. The Created date, which Google previously set to the time of upload, remains the same.Let’s assume that this record is needed for e discovery purposes, and it is downloaded from Google Drive to a forensic examiner’s machine to pass along to the case team. When the file reaches the machine, the creation of the new file results in the following file system date values. Notice that they’ve all been changed to the date/time of the download action!However, if we take a look inside the Excel file at the embedded “application” dates, we notice that we have a creation date of 6/30/2020 at 11:04 AM that has remained unaltered throughout this entire process. However, the “Date last saved” is reflective of the time of the download action. We may have expected this date to be set to 11:27 AM, which was the time at which the document was edited in Google Drive, but it is unfortunately altered by the download action. The image on the right shows the “Info” tab from MS Excel itself, which indicates a blank value for “Last Modified.”Using the same Excel file, I will now choose to “Save as Google Sheets”.You’ll notice that the creation and modification timestamps in the graphic below have been set to the time at which the MS Excel file was converted to a Google Sheet. Google also indicates the application that created the document was “Google Sheets.”I made a couple of edits to the file in Google Sheets and then right clicked to download it to my workstation. First, Google converts the file from Google Sheets format into MS Excel format.chat-and-collaboration-data; information-governancecloud, g-suite, blog, chat-and-collaboration-data, information-governancecloud; g-suite; blogjosh headley

However you view a DSAR, for any entity who receives one, they are time consuming to complete and disproportionately expensive to fulfill. Combined with the increasing manner in which they are being weaponized, companies are often missing opportunities to mitigate the negative effects of DSARs by not migrating data to the Cloud.Existing cloud solutions, such as M365 and Google Workplace (formerly known as G-Suite) allow administrators to,for example, set data retention policies, ensuring that data cannot routinely be deleted before a certain date, or that a decision is made as to when data should be deleted. Equally, legal hold functionality can ensure that data cannot be deleted at all. It is not uncommon for companies to discover that when they migrate to the Cloud all data is by default set to be on permanent legal hold. Whilst this may be required for some market sectors, it is worth re-assessing any existing legal hold policy regularly to prevent data volumes from ballooning out of control.Such functionality is invaluable in retaining data, but can have adverse effects in responding to DSARs, as it allows legacy or stale data to be included in any search of documents and inevitably inflates costs. Using built-in eDiscovery tools to search and filter data in place in combination with a data retention policy managed by multiple stakeholders (such as Legal, HR, IT, and Compliance) can mitigate the volumes of potentially responsive data, having a significant impact on downstream costs of fulfilling a DSAR.Typically, many key internal stakeholders are frequently unaware of the functionality available to their organization. This can help to mitigate costs, such as Advanced eDiscovery (AED) in Microsoft 365, or Google Vault in Google Workspace. Using AED, a user can quickly identify relevant data sources, from mailboxes, OneDrive, Teams, Skype, and other online data sources, apply filters such as date range and keywords, and establish the potential number of documents for review within in minutes. Compare this to those who have on-premise solutions, where they are wholly dependent on an internal IT resource, or even the individual data custodians, to identify all of the data sources, confirm with HR / Legal that they should be collected, and then either apply search criteria or export the data in its entirety to an external provider to be processed. This process can take days, if not weeks, when the clock is ticking to provide a response in 30 days. By leveraging cloud technology, it is possible to identify data sources and search in place in a fraction of the time it takes for on-premise data.Many cloud platforms include functionality, which means that when data is required for a DSAR, it can now be searched, filtered, and, crucially, reviewed in place. If required, redactions can be performed prior to any data being exported externally. Subject to the level of license held, additional functionality, such as advanced indexing or conceptual searching, can also be deployed, allowing for further filtering of data and thus reducing data volumes for review or export.The technology also allows for rapid identification of multiple data types including:Stale dataSensitive data types (financial information/ PII)Customer-specific dataSuspicious / unusual activitiesBy using the inbuilt functionality to minimize the impact of such data types as part of an Information Governance / Records Management program, there can be significant changes and improvements made elsewhere, including data retention policies, data loss prevention, and improved understanding of how data is routinely used and managed in general day-to-day business. This, in turn, has significant time and cost benefits when required to search for data, whether for a DSAR, investigation, or a litigation exercise. Subject to the agreement with the cloud service provider, this may also have benefits in reducing the overall volume and cost of data hosted.With a sufficiently robust internal protocol in place, likely data sources can be identified and mapped. Now, when a DSAR request is received, an established process exists to rapidly search and cull potential cloud-based data sources, including using tools such as Labels or Sensitivity Type to exclude data from the review pool, and efficiently respond to any such request.Migrating to the Cloud may seem daunting, but the benefits are there and can be best maximized when all stakeholders work together, across multiple teams and departments. DSARs do not have to be the burden they are today. Using tools readily available in the Cloud might also significantly reduce the burdens and costs of DSARs.To discuss this topic further, please feel free to reach out to me at MBicknell@lighthouseglobal.com.data-privacy; ediscovery-review; information-governance; microsoft-365cloud, dsars, cloud-services, blog, data-privacy, ediscovery-review, information-governance, microsoft-365cloud; dsars; cloud-services; blogmatt bicknell

Few things are more ominous to a company’s in-house counsel than the prospect of facing thousands of individual lawsuits across 30-40 jurisdictions, alongside various other companies in a multi-district litigation (MDL) proceeding. In-house teams can, of course, lean on the expertise of external law firms that have strong backgrounds in MDLs. However, even for experienced law firms, coordinating an individual company’s legal defense with other law firms and in-house counsel within a joint defense group (JDG) can be a Sisyphean task. But this coordination is integral to achieving the best possible outcome for each company, especially when it comes to identifying and sharing the documents that will drive the JDG’s litigation strategies. An MDL can involve millions of documents, emanating from multiple companies and their subsidiaries. Buried somewhere within that complicated web of data is a small number of key documents that tell the story of what actually happened—the documents that explain the “who, what, where, and when” of the litigation. Identifying those documents is critical so that JDG counsel can understand the role each company played (or didn’t play) in the plaintiffs’ allegations, and then craft and prepare their defense accordingly. And the faster those documents are identified and shared across a JDG, the better and more effective that defense strategy and preparation will be. In short: A strong and coordinated key document search strategy that is specific to the unique ecosystem of an MDL is crucial for an effective defense. Ineffective search strategies leave litigators out at sea Unfortunately, outdated or ineffective search methodologies are often still the norm rather than the exception. The two most common strategies were created to find key documents in smaller, insular litigation proceedings involving one company. They are also relics of a time when average data volumes involved in litigation were much smaller. Those two strategies are: one, relying on linear document review teams to surface key documents as they review documents one by one in preparation for production, and, two, relying on attorneys from the JDG’s counsel teams to arbitrarily search datasets using whatever search terms they think may be effective. Let’s take a deeper look at each of these methodologies and why they are both ineffective and expensive: Relying on linear review teams to find key documents. Traditional linear review teams are often made up of dozens or even hundreds of contract attorneys with no coordination around key document searches and little or no day-to-day communication with JDG counsel. Each attorney reviewer may also only see a tiny fraction of the entire dataset and have a skewed view of what documents are truly important to the JDG’s strategy. The results are often both overinclusive (with thousands of routine documents labeled “key” or “hot” that JDG counsel must wade through) and underinclusive (with truly important documents left unflagged and unnoticed by review teams). This search method is also painfully slow. Key documents are only incidentally surfaced by the review team if they notice them while performing their primary responsibility—responsive review. Relying on attorneys from JDG counsel teams. Relying on individual attorneys from the JDG’s outside counsel to perform keyword searches to find key documents is also ineffective and wastefully expensive. Without a very specific, coordinated search plan, attorneys are left running whatever searches each thinks might be effective. This strategy inevitably will risk plaintiffs finding critical documents first, leaving defense deposition witnesses unprepared and susceptible to ambush. This search methodology is also a dysfunctional use of attorney time and legal spend. Merits counsel’s value is their legal analytic skillset—i.e., their ability to craft the best litigation strategy with the evidence at hand. Most attorneys are not technologists or linguistic experts. Asking highly skilled attorneys to craft the most effective technological and linguistic data search is a bit like asking an award-winning sushi chef to jump onboard a fishing vessel, navigate to the best fishing spot, select the best bait, and reel in the fish the chef will ultimately serve. Both jobs require a highly specialized skillset and are essential to the end goal of delighting a client with an excellent meal. But paying the chef to perform the fisherman’s job would be ineffective and a waste of the chef’s skillset and time. Both of these search strategies are also reactive rather than proactive, which drives up legal costs, wastes valuable resources, and worsens outcomes for each company in a JDG. A better approach to MDL preparation and strategy Fortunately, there is a more proactive, cost-efficient, holistic, and effective way to identify the key documents in an MDL environment. It involves engaging a small team of highly trained linguists and technology search experts, who can leverage purpose-built technology to find the best documents to prepare effective litigation strategies across the entire MDL data landscape. A specialized team with this makeup provides a number of key advantages: Precise searches and results—Linguistic experts can carefully craft narrow searches that consider the nuance of human language to more effectively find key documents. A specialized search team can also employ thematic search strategies across every jurisdiction. This provides counsel with a critical high-level overview of the evidence that lies within the data for each litigation, enabling each company to make better, more informed decisions much earlier in the process.Quick access to key documents—Technology experts leveraging advanced AI and analytics can ensure potentially damaging documents bubble up to the surface—even in the absence of specific requests from JDG counsel. Compare this to waiting for those documents to be found by contract attorneys as they review an endless stream of documents, one by one, during the linear review process. A flexible offensive and defensive litigation strategy—A team of this size and composition can react more nimbly, circulate information faster, and respond quicker to changes in litigation strategy. For example, once counsel has an overview of the important facts, the search team can begin to narrow their focus to arm counsel with the data needed for both offensive and defensive litigation strategies. The team will be incredibly adept at analyzing incoming data provided by opposing counsel—flagging any gaps and raising potential deposition targets. Defensively, they can be used by counsel to get ahead of any potentially damaging evidence and identify every document that bolsters potential defense arguments. An expert partner throughout the process—A centralized search team is able to act as a coordinated “search desk” for all involved counsel, as well as a repository and “source of truth” for institutional knowledge across every jurisdiction. As litigation progresses, the search team becomes the right hand of counsel—using their knowledge and expertise to prepare deposition and witness preparation binders and performing ad-hoc searches for counsel. Once a matter goes to trial in one jurisdiction, the search team can use the information gleaned from that proceeding to inform their searches and strategy for the next case. Conclusion Facing a complex MDL is an undoubtedly daunting process for any company. But successfully navigating this challenge will be downright impossible if counsel is unable to quickly find and understand the key facts and issues that lie buried within massive volumes of data. Traditional key document search methodologies are no longer effective at providing that information to counsel. For a better outcome, companies should look for small, specialized search teams, made up of linguistic and technology experts. These teams will be able to build a scalable and effective search strategy tailormade for the unique data ecosystem of a large MDL—thereby proactively providing counsel with the evidence needed to achieve the best possible outcome for each company. lighting-the-way-for-review; ai-and-analytics; ediscovery-review; lighting-the-path-to-better-review; lighting-the-path-to-better-ediscoveryreview, blog, ai, ai-and-analytics, ediscovery-reviewreview; blog; aikdisarah moran

It was a tumultuous summer in the world of data privacy, so I wanted to keep legal and compliance teams updated on changes that may affect your business in the coming months. Below is a recap of important data privacy changes across multiple jurisdictions, as well as where to go to dive into these updates a little deeper. Keep in mind that some of these changes may mean heightened responsibilities for companies related to breach requirements and/or data subject rights.U.S. On September 17th, four U.S. Republican senators introduced the “Setting an American Framework to Ensure Data Access, Transparency, and Accountability Act” (SAFE DATA). The Act is intended to provide Americans “with more choice and control over their data and direct businesses to be more transparent and accountable for their data practices.” The Act contains data privacy elements that are reminiscent of the GDPR and California Consumer Privacy Act (CCPA) of 2018, including requiring tech companies to provide users with notice of privacy policies, giving consumers the ability to opt in and out of the collection of personal information, and requiring businesses to allow consumers the ability to access, correct, or delete their personal data. See the press release issued by the U.S. Senate Committee on Commerce, Science and Transportation here: https://www.commerce.senate.gov/2020/9/wicker-thune-fischer-blackburn-introduce-consumer-data-privacy-legislationCalifornia’s Proposition 24 (the “California Privacy Rights Act of 2020”) will be on the state ballot this November. In some ways, the Act expands upon the CCPA by creating a California Privacy Protection Agency and tripling fines for collecting and selling children’s private information. Proponents say it will enhance data privacy rights for California citizens and give them more control over their own data. Opponents are concerned that it will result in a “pay for privacy” scheme, where large corporations can downgrade services unless consumers pay a fee to protect their own personal data. See: https://www.sos.ca.gov/elections/ballot-measures/qualified-ballot-measures for access to the proposed Act.In mid-August, the Virginia Legislative Commission initiated study commissions to begin evaluating elements of the proposed Virginia Privacy Act, which would impose similar data privacy responsibilities on companies operating within Virginia as the GDPR does for those in Europe and the CCPA does for those in California. To access the proposed Act, see: https://lis.virginia.gov/cgi-bin/legp604.exe?201+sum+HB473.EuropeOn September 8, Switzerland’s Federal Data Protection and Information Commissioner (FDPIC) concluded that the Swiss-US Privacy Shield does not provide an adequate level of protection for data transfers from Switzerland to the US. The statement came via a position paper issued after the Commissioner’s annual assessment of the Swiss-US Privacy shield regime, and was based on the Court of Justice of the European Union (CJEU) invalidation of the EU-US Privacy Shield. You can find more about the FDPIC position paper here: https://www.edoeb.admin.ch/edoeb/de/home/kurzmeldungen/nsb_mm.msg-id-80318.htmlSimilarly, Ireland’s data protection commissioner issued a preliminary order to Facebook to stop sending data transfers from EU users to the U.S., based on the CJEU’s language in the Schrems II decision which invalidated the EU-US Privacy Shield. In response, Facebook has threatened to halt Facebook and Instagram services in the EU. Check out the Wall Street Journal’s reporting on the preliminary order issued by the Ireland Data Protection Commission here: https://www.wsj.com/articles/ireland-to-order-facebook-to-stop-sending-user-data-to-u-s-11599671980. For Facebook’s response filing in Ireland, see: https://www.dropbox.com/s/yngcdv99irbm5sr/Facebook%20DPC%20filing%20Sept%202020-rotated.pdf?dl=0Relatedly, in wake of the Schrems II judgment, the European Data Protection Board has also created a task force to look into 101 complaints filed with several data controllers in EEA member states related to Google/Facebook transfers of personal data into the United States. See the EDPB’s statement here: https://edpb.europa.eu/news/news/2020/european-data-protection-board-thirty-seventh-plenary-session-guidelines-controller_enBrazilIn September, the new Brazilian General Data Protection Law (Lei Geral de Proteção de Dados Pessoais or LGPD) became retroactively effective after the end of a 15-business-day period imposed by the Brazilian Constitution. This was a surprising turn of events after the Brazilian Senate rejected a temporary provisional measure on August 26th that would have delayed the effective date to the summer of 2021. Companies should be aware that the law is similar to the GDPR in that it is extra territorial and bestows enhanced privacy rights to individuals (including right to access and right to know). Be aware too, although administrative enforcement will not begin until August of 2021, Brazilian citizens now have a private right of action against organizations that violate data subjects’ privacy rights under the new law. For more information, check out the LGPD site (that can be translated via Google Chrome) with helpful guides and tips, as well as links to the original law: https://www.lgpdbrasil.com.br/. The National Law Review also has a good overview of the sequence of events that led up to this change here: https://www.natlawreview.com/article/brazil-s-data-protection-law-will-be-effective-after-all-enforcement-provisions.EgyptIn June, Egypt passed the Egyptian Data Protection Law (DPL), which is the first law of its kind in that country and aims to protect the personal data of Egyptian citizens and EU citizens in Egypt. The law prohibits businesses from collecting, processing, or disclosing personal information without permission from the data subject. It also prohibits the transfer of personal data to a foreign country without a license from Egypt. See the International Association of Privacy Professional’s reporting on the law here: https://iapp.org/news/a/egypt-passes-first-data-protection-law/To discuss this topic further, please feel free to reach out to me at SMoran@lighthouseglobal.com.data-privacyccpa, gdpr, data-privacy, blog, data-privacy,ccpa; gdpr; data-privacy; blogsarah moran

The theme at the last CLOC conference was all about how the legal function is going through a tremendous evolution. Businesses are changing rapidly through digital transformation and remote or hybrid work environments while trying to capture the attention of technology saturated consumers. To remain competitive, legal departments must evolve to handle new types of work and constantly advancing processes and technologies, and consider how the legal function impacts the broader organization. They need to do this while also showing that their own department is embracing change, staying up on technology, and becoming more efficient. To do this well, legal department heads and the lawyers and professionals in the department will have to learn, and practice, some new skills: embracing technology, project management, change management, and adaptability. Some good news—recent trends in the legal space are helping departments and professionals facilitate and adapt to these changes. The first is an uptick in legal technologies available to legal departments. Instead of adapting to whatever technology the business makes available to the department, there are technologies built by lawyers for running a legal department. This trend means that lawyers have already started down the path of being more technology-forward. Second, the advent of the legal operations role—putting business discipline and rigor around the functioning of the legal department— has brought more robust project management and change management into many law departments. With these foundational blocks in place, lawyers must evolve their skills to take their department to the next level.The first, and likely most obvious, skill an attorney needs in a rapidly evolving business environment is a firm grasp on existing and emerging technology. There are two important categories of technology to consider—the first is legal technology and the second is broader technology trends. Legal technology not only facilitates the day-to-day functioning of the legal department—with e-billing, contract management, and project intake and workflow software—but also includes more complex categories such as eDiscovery and data management. To learn more about these technologies you can attend CLEs about relevant technologies in your area of practice or attend a legal technology conference. Outside of the legal space, there are also many general technology trends that are important for lawyers to be immersed in, including digital transformation, artificial intelligence, and digital payments and cryptocurrency. Digital transformation is all about changing from a brick and mortar, paper-based business to one that strategically leverages technology, digital tools, and the cloud to do the work. This is important for lawyers because it impacts the way their organizations contract and manage these technologies. Migrating to the cloud also benefits lawyers because it provides new technologies to manage legal departments.[1] Like cloud, AI has the ability to transform how lawyers work (e.g., check out our recent blog post on utilizing chatbots) as well as how their companies work. For both AI and digital transformation, reading and watching videos for IT leaders can help—although made for a different audience, there are lots of resources out there and they can provide the information relevant to lawyers. Finally, the plethora of digital payment methods and the volatility of cryptocurrency will have legal impacts in the future and lawyers should learn to understand the differences.The next set of skills is about project execution and management. As businesses change through digital transformation, it is equally important to transform the way legal departments work. To do that, learning effective business case presentation, project management, and change management are incredibly valuable talents. While diving into a full 30-page business case can sometimes be necessary, focusing time on learning to create an executive summary business case is time better spent for lawyers. You can find resources and templates in many places, including SmartSheet and Asana.There is a whole discipline around project management as well as multiple ways to drive results most effectively. Whether you take an agile approach or a more traditional method, the following skills are necessary: Cross-functional collaboration, including understanding and empathy for other departments, and influencing othersCommunication, including how to communicate effectively with a remote team – a reality that is often the norm in today’s worldTime management and prioritizationLeadership – leading a team and inspiring a team, and keeping team members engaged and focused both in the same office or working remotelyFacilitating a learning mindset across the project and team – ensuring that people are looking out for ways to continuously improve, learning from each step of the project, and iterating on each phase of the projectA couple of good resources for developing these skills include PMI.org, and LinkedIn Learning courses such as Project Leadership, Project Management Foundations: Communication, and Project Management Tips. Note that this is a discipline that can take years to perfect so focus on getting familiar with the concepts and then look for ways to get real life experience in your business. The best way to master these skills is through practice.While project management focuses on the process where you create a change, change management is a separate set of skills focused on moving people through that change. There are two components of change management lawyers need to know. The first is how to manage their own reaction to change—being adaptable can bring a lot of value to a volatile world.[2] Professor Anne Converse Willkom of Drexel University provides some great ways to work on becoming more adaptable here. The second part of change management is helping others through change. This may be your team or it could be a team impacted by a project you are leading. Harvard Business Review has a whole category of writing dedicated to this area, highlighting the importance of leading through change.There is a lot of information and resources to move through so it’s important to prioritize the areas and skills that will impact your role now and as you move through your career. From there, identify the list of resources you want to access to master those areas then work it in to your schedule. It’s important to budget 2-4 hours a week, at minimum, building your skills in one of these areas. If that seems like a lot, keep in mind that it is only 5-10% of a standard work week.‍[1] You can find more information on what this change is in this article by CIO.[2] It is sometimes hard to judge adaptability because we tend to be surrounded by like-minded thinkers. As such, relying on a third party resource can help. There is a great Forbes article that shares the signs of an adaptable person. Evaluate yourself versus this list and work on areas where you may not be adaptable.ediscovery-review; legal-operationsediscovery-process, blog, project-management, ediscovery-review, legal-operationsediscovery-process; blog; project-managementlighthouse

Since the dawn of modern litigation, attorneys have grappled with finding the most efficient and strategic method of producing discovery. However, the shift to computers and electronically stored information (ESI) within organizations since the 1990s exponentially complicated that process. Rather than sifting through filing cabinets and boxes, litigation teams suddenly found themselves looking to technology to help them review and produce large volumes of ESI pulled from email accounts, hard drives, and more recently, cloud storage. In effect, because technology changed the way people communicated, the legal industry was forced to change its discovery process.The Rise of TARDue to growing data volumes in the mid-2000s, the process of large teams of attorneys looking at electronic documents one-by-one was becoming infeasible. Forward-thinking attorneys again looked to technology to help make the process more practical and efficient – specifically, to a subset of artificial intelligence (AI) technology called “machine learning” that could help predict the responsiveness of documents. This process of using machine learning to score a dataset according to the likelihood of responsiveness to minimize the amount of human review became known as technology assisted review (TAR).TAR proved invaluable because machine learning algorithms’ classification of documents enabled attorneys to prioritize important documents for human review and, in some cases, avoid reviewing large portions of documents. With the original form of TAR, a small number of highly trained subject matter experts review and code a randomly selected group of documents, which are then used to train the computer. Once trained, the computer can score all the documents in the dataset according to the likelihood of responsiveness. Using statistical measures, a cutoff point is determined, below which the remaining documents do not require human review because they are deemed statistically non-responsive to the discovery request.Eventually, a second iteration of TAR was developed. Known as TAR 2.0, this second iteration is based on the same supervised machine learning technology as the riginal TAR (now known as TAR 1.0) – but rather than the simple learning of TAR 1.0, TAR 2.0 utilizes a process to continuously learn from reviewer decisions. This eliminates the need for highly trained subject matter experts to train the system with a control set of documents at the outset of the matter. TAR 2.0 workflows can help sort and prioritize documents as reviewers code, constantly funneling the most responsive to the top for review.Modern Data ChallengesBut while both TAR 1.0 and TAR 2.0 are still widely used in eDiscovery today – the data landscape looks drastically different than it did when TAR first made its debut. Smartphones, social media applications, ephemeral messaging systems, and cloud-based collaboration platforms, for example, did not exist twenty years ago but are all commonly used within organizations for communication today. This new technology generates vast amounts of complicated data that, in turn, must be collected and analyzed during litigations and investigations.Aside from the new variety of data, the volume and velocity of modern data is also significantly different than it was twenty years ago. For instance, the amount of data generated, captured, copied, and consumed worldwide in 2010 was just two zettabytes. By 2020, that volume had grown to 64.2 zettabytes.[1]Despite this modern data revolution, litigation teams are still using the same machine learning technology to perform TAR as they did when it was first introduced over a decade ago – and that technology was already more than a decade old back then. TAR as it currently stands is not built for big data – the extremely large, varied, and complex modern datasets that attorneys must increasingly deal with when handling discovery requests. These simple AI systems cannot scale the way more advanced forms of AI can in order to tackle large datasets. They also lack the ability to take context, metadata, and modern language into account when making coding predictions. The snail pace of the evolution of TAR technology in the face of the lightning-fast evolution of modern data is quickly becoming a problem.The Future of TARThe solution to the challenge of modern data lies in updating TAR workflows to include a variety of more advanced AI technology, together with bringing on technology experts and linguistics to help wield them. To begin with, for TAR to remain effective in a modern data environment, it is necessary to incorporate tools that leverage more advanced subsets of AI, such as deep learning and natural language processing (NLP), into the TAR process. In contrast to simple machine learning (which can only analyze the text of a document), newer tools leveraging more advanced AI can analyze metadata, context, and even the sentiment of the language used within a document. Additionally, bringing in linguists and experienced technologists to expertly handle massive data volumes allows attorneys to focus on the actual substantive legal issues at hand, rather than attempting to become an eDiscovery Frankenstein (i.e., a lawyer + a data scientist + a technology expert + and a linguistic expert all rolled into one).This combination of advanced AI technology and expert service will enable litigation teams to reinvent data review to make it more feasible, effective, and manageable in a modern era. For example, because more advanced AI is capable of handling large data volumes and looking at documents from multiple dimensions, technology experts and attorneys can start working together to put a system in place to recycle data and past attorney work product from previous eDiscovery reviews. This type of “data reuse” can be especially helpful in tackling the traditionally more expensive and time-consuming aspects of eDiscovery reviews, like privilege and sensitive information identification and can also help remove large swaths of ROT (redundant, obsolete, or trivial data). When technology experts can leverage past data to train a more advanced AI tool, legal teams can immediately reduce the need for human review in the current case. In this way, this combination of advanced AI and expert service can reduce the endless “reinventing the wheel” that historically happens on each new matter.ConclusionThe same cycle that brought technology into the discovery process is again prompting a new change in eDiscovery. The way people communicate and the systems used to facilitate that communication at work are changing, and current TAR technology is not equipped to handle that change effectively. It’s time to start incorporating more modern AI technology and expert services into TAR workflows to make eDiscovery feasible in a modern era.To learn more about the advantages of leveraging advanced AI within TAR workflows, please download our white paper, entitled “TAR + Advanced AI: The Future is Now.” And to discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com. [1] “Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2025” https://www.statista.com/statistics/871513/worldwide-data-created/practical-applications-of-ai-in-ediscovery; ai-and-analytics; ediscovery-reviewai-big-data, tar-predictive-coding, ediscovery-process, prism, blog, data-reuse, ai-and-analytics, ediscovery-reviewai-big-data; tar-predictive-coding; ediscovery-process; prism; blog; data-reusesarah moran

Since Judge Andrew Peck’s ruling over nine years ago in Da Silva Moore v. Publicis Groupe & MSL Group, the use of Technology-Assisted Review (TAR) for managing review in eDiscovery has been court approved. Yet many lawyers and legal professionals still don’t use machine learning (which, for many, is synonymous with TAR) in litigation. In the eDiscovery Today 2021 State of the Industry report, only 31.1% of respondents said they use TAR in all or most of their cases; 32.8% of respondents said they use it in very few or none of their cases. So, why don’t more lawyers use TAR?Transparency and TAROne possible reason that lawyers avoid the use of TAR is that requesting parties often demand more transparency with a TAR process than they do with a process involving keyword search and manual review. Judge Peck (retired magistrate judge and now Senior Counsel with DLA Piper) stated in the eDiscovery Today State of the Industry report: “Part of the problem remains requesting parties that seek such extensive involvement in the process and overly complex verification that responding parties are discouraged from using TAR.”In the article Predictive Coding: Can It Get A Break?, author Gareth Evans, a partner at Redgrave, states: “Probably the greatest impediment to the use of predictive coding has been the argument that the party seeking to use it should agree to share its coding decisions on the documents used to train the predictive coding model, including providing to the opposing party the irrelevant documents in the training sets.”Lawyer training vs. “black box” technologyWhy do lawyers expect that they are entitled to more transparency with TAR? Perhaps a better question might be: why do they demand less transparency for keyword search and manual review? One reason might lie in the education and training that they receive to become lawyers. Many lawyers cut their teeth on the keyword search used for resources like Westlaw and Lexis. Consequently, keyword search is part of their experience and they feel comfortable using it.Those same lawyers see keyword search and manual review for discovery as an extension of what they learned in law school. But it’s not. Search (aka “information retrieval”) is an expertise. Effective keyword search for discovery purposes is an iterative process that requires testing and verification of the search result set and the discard pile to confirm that the scope of the search wasn’t too narrowly focused. The end goal is to construct a search with both high recall and high precision; to identify those documents potentially responsive to a production request without also capturing non-responsive information, which can significantly increase review costs. This is very different from the goal of identifying a handful of documents that can assist in a case precedents argument.With regard to TAR, many lawyers still see the technology as a “black box” that they don’t understand. So, when the other side proposes using TAR, they want a lot more transparency about the particular TAR process to be used. It’s simply human nature to ask more questions about things we don’t understand. But, truth be told, lawyers should probably be just as vigilant in seeking information about the opposing’s use of keyword search as they are when TAR is the approach being proposed.TAR technology in daily livesWhat many lawyers may not realize is that they’re already using the type of technology associated with TAR elsewhere in their lives — albeit with a different goal and lower stakes than in a legal case. TAR is based on a supervised machine learning algorithm, where the algorithm learns to deliver similar content based on human feedback. Choices we make in Amazon, Spotify, and Netflix influence what those platforms deliver to us as other choices we might want to see in terms of items to buy, songs to listen to or movies to watch. The process of “training” the algorithms that drive these platforms makes them more useful to us — just as the feedback we provide during a predictive coding process helps train the algorithm to identify documents most likely to be responsive to the case.ConclusionWhat should lawyers do when opposing counsel makes transparency demands regarding TAR processes to be used? Certainly, cooperation and discussion of the protocol as soon as possible — such as the Rule 26(f) “meet and confer” between the parties — can help everyone get “on the same page” about what information can or should be shared, no matter what approach is proposed.However, if the parties can’t reach an accord regarding TAR transparency, perhaps another case ruling by Judge Peck — Hyles v. New York City — can be instructive here, where Judge Peck cited Sedona Principle 6. This principle states: “Responding parties are best situated to evaluate the procedures, methodologies, and technologies appropriate for preserving and producing their own electronically stored information.” Ironically, in Hyles, the requesting party was trying to force the responding party to use TAR, but Judge Peck, despite being an acknowledged “judicial advocate for the use of TAR in appropriate cases” denied the requesting party’s motion in that case. Transparency demands from requesting parties shouldn’t deter you from realizing the potential efficiency gains and cost savings resulting from an effective TAR process.For more information on H5 Litigation Services, including review for production with the H5 unique TAR as a Service, click here.ediscovery-reviewediscovery-reviewblog; tar; litigation; technology-assisted-review; predictive-coding; ediscovery; machine-learningmitch montoya

“The world’s most valuable resource is no longer oil, but data.” That’s what The Economist said in a fascinating opinion piece in 2017 that really stuck with me. This bold statement now seems more prescient than ever, as digital data continues to explode in volume and the advent of the cloud is significantly expanding where that valuable data, or electronically stored information (ESI), lives. So how has the legal world, and particularly all of us in the eDiscovery realm, fared?While this data revolution developed, lawyers, as per usual, have been a bit slow to adapt. As we’ve grappled with how to manage the explosion of data and cloud storage has gone mainstream, new and advanced SaaS solutions tied to cloud-based technology have taken the rest of the world by storm. It was only a matter of time before corporate clients would get on board and make the move to the cloud as is evident with the large majority of corporations who have transitioned to Office 365.So as clients focus more and more on controlling their budgets and demanding more eDiscovery efficiency, shifting to modernized, cloud-based SaaS technology seems like a no-brainer for law firms. What’s not to love about immediately eliminating the inefficiencies and manual tasks that accompany traditional eDiscovery workflows and creating satisfied clients in the process?In my previous two blogs, I discussed the top reasons why SaaS, self-service, spectra eDiscovery is exactly the right solution and the way of the future for law firms, and also best practices for embracing the data revolution. In this blog, I wrap up my SaaS exploration and present the top things to consider when choosing the best and most versatile SaaS solution for your eDiscovery program.1. Quick to Onboard - Software in the eDiscovery space has had a notoriously rocky road as far as simplicity and user friendliness. Many iterations of self-service, spectra, on-prem software are too complicated and require training fit for advanced users only. Another missing piece of the puzzle has often been the lack of clear and consumable metrics on areas like billing, usage, ingestion, and processing stats which are the key to helping inform users to make better decisions. With the new generation of eDiscovery technology, lawyers and litigation support professionals would most benefit from choosing a SaaS, self-service, spectra tool that’s quick and easy to understand. Look for a tool where cases with multiple users can be easily managed across matters and locations, and where you can create, upload, and process matters quickly, all with a customizable reporting dashboard.2. Access to Industry Leading Tools - One of the biggest issues we’ve seen as eDiscovery software has evolved is the need for users of on-prem software to purchase, install, and maintain multiple tools and systems in order to have a comprehensive internal workflow that spans the EDRM. This is not only expensive, but time consuming and risky considering the security implications that come with holding client data on your own servers. With SaaS, it’s critical to choose a platform that will provide access to all of the industry leading tools from processing to analytics to production in one comprehensive tool that is purchased, maintained, and upgraded by the solution provider. Users will immediately see direct cost savings from not having to manage multiple systems themselves when they adopt this type of end-to-end SaaS solution.3. Full-Service Support - Another important consideration when selecting a self-service, spectra, SaaS tool is to choose a flexible solution provider who can scale up if your matter changes and you end up needing full-service support. While having a self-service, spectra tool allows for complete independence in key areas like processing and production, what happens when your matter gets much bigger than anticipated and the data is too unwieldy to handle in-house, or if your internal team simply needs to shift their focus to something else? In this case, it’s critical to partner with a solution provider who has solid and experienced client support teams that can jump in any time you need help in your self-service, spectra journey.4. Secure Infrastructure - Last but not least, in this age of data breaches and cybersecurity on the top of the list of concerns for law firms and corporate clients alike, make sure you fully vet any SaaS tool you’re considering by thoroughly researching the solution provider’s back-end infrastructure. Look for vendors who have a scalable architecture for data processing and automation that you’ll be able to take full advantage of while eliminating the overhead that comes with infrastructure development and management on your end. That infrastructure should come with the peace of mind of security certifications such as SOC 2 and ISO 27001. You can also eliminate the concern that often comes with the security of a public cloud by choosing a solution provider that hosts data within their own private cloud or within their own data centers.Ultimately, as the global economy continues to shift from traditional commodities and lands squarely on data as its main driver, there’s a world of opportunity ahead for the legal world and eDiscovery. With data already moved to the cloud for most companies and their focus shifted to reducing expenses and risk, eDiscovery and SaaS for law firms is a perfect fit.ediscovery-review; ai-and-analyticscloud, self-service, spectra, blog, ediscovery-review, ai-and-analyticscloud; self-service, spectra; bloglighthouse

What does Artificial Intelligence (AI) mean to you? In the non-legal space, AI has taken a prominent role, influencing almost every facet of our day-to-day life – from how we socialize, to our medical care, to how we eat, to what we wear, and even how we choose our partners.In the eDiscovery space, AI has played a much more discreet but nonetheless important role. Its limited adoption so far is due, in part, to the fact that the legal industry tends to be much more risk averse than other industries. The innate trust we have placed in more advanced forms of AI technology in the non-legal world to help guide our decision making has not carried over to eDiscovery – partly because attorneys often feel that they don’t have the requisite technological expertise to explain the results to opposing counsel or judges. The result: most attorneys performing eDiscovery tasks are either not using AI technology at all or are using AI technology that is generations older than the technology currently being used in other industries. All this despite the fact that attorneys facing discovery requests today must regularly analyze mountains of complicated data under tight deadlines.One of the most prominent roles AI currently plays in eDiscovery is within technology assisted review (TAR). TAR uses “supervised” machine learning algorithms to classify documents for responsiveness based on human input. This classification allows attorneys to prioritize the most important documents for human review and, often, reduce the number of documents that need to be reviewed by humans. TAR has proven to be especially helpful in HSR Second Requests and other matters with demanding deadlines. However, the simple machine learning technology behind TAR is already decades old and has not been updated, even as AI technology has significantly advanced. This older AI technology is quickly becoming incapable of handing modern datasets, which are infinitely more voluminous and complicated than they were even five years ago.Because the legal industry is slower to adopt more advanced AI technology, many attorneys have a muddled view of what advanced AI technology exists, how it works, and how that technology can assist attorneys in eDiscovery today. That confusion becomes a significant detriment to modern attorneys, who must start being more comfortable with adopting and utilizing the more advanced AI tools available today if they stand a chance overcoming the increasingly complicated data challenges in eDiscovery. This confusion behind AI can also lead to a vicious cycle that further slows down technology adoption in the legal space: attorneys who lack confidence in their ability to understand available AI technology subsequently resist adoption of that technology; that lack of adoption then puts them even further behind the technology learning curve as technology continues to evolve. This is where legal technology companies with dedicated technology services can help. A good legal technology company will have staff on hand whose entire job it is to evaluate new technology and test its application and accuracy within modern datasets. Thus, an attorney who has no interest in becoming a technology expert just needs to be proficient enough to know the type of tools that might fit their needs – the right technology vendor can do the rest. Technology experts can also step in to help provide detailed explanations of how the technology works to stakeholders, as well as verify the outcome to skeptical opposing counsel and judges. Moreover, a good technology provider can also supply expert resources to perform much of the day-to-day utilization of the tool. In essence, a good legal technology vendor can become a trusted part of any attorney team – allowing attorneys to remain focused on the substantive legal issues they are facing. With that in mind, it’s important to “demystify” some common AI concepts used within the eDiscovery space and explain the benefits more advanced forms of AI technology can provide within eDiscovery. Once comfortable with the information provided here, readers can take a deeper dive into the advantages of leveraging advanced AI within TAR workflows in our full white paper – “TAR + Advanced AI: The Future is Now.” Armed with this information, attorneys can begin a more thoughtful conversation with stakeholders and legal technology companies regarding how to move forward with more advanced AI technology within their own practice.Demystifying AI Jargon in eDiscoveryAt its most basic, AI refers to the science of making intelligent machines – ones that can perform tasks traditionally performed by human beings. Therefore, AI is a broad field that encompasses many subfields and branches. The most relevant to eDiscovery are machine learning, deep learning, and natural language processing (NLP). As noted above, the technology behind legacy TAR workflows is supervised machine learning. Supervised machine learning uses human input to mimic the way humans learn through algorithms that are trained to make classifications and predictions. In contrast, deep learning eliminates some of that human training by automating the feature extraction process, which enables it to tackle larger datasets. NLP is a separate branch of machine learning that can understand text in context (in effect, it can better understand language the way humans understand it).The difference between the AI technology in legacy TAR workflows and more advanced AI tools lies in the fact that advanced AI tools use a combination of AI subsets and branches (machine learning, deep learning, and NLP) rather than just the supervised machine learning used in TAR. Understanding the Benefits of Advanced AIThis combination of AI subsets and branches used in advanced AI tools provides additional capabilities that are increasingly necessary to tackle modern datasets. These tools not only utilize the statistical prediction that supervised machine learning produces (which enables traditional TAR workflows), but also include the language and contextual understanding that deep learning and NLP provide. Deep learning and NLP technology also enable more advanced tools to look at all angles of a document (including metadata, data source, recipients, etc.) when making a prediction, rather than relying solely on text. Taking all context into consideration is increasingly important, especially when making privilege predictions that lead to expensive attorney review if a document is flagged for privilege. For example, with traditional TAR, the word “judge” in the phrases, “I don’t think the judge will like this!” on an email thread between two attorneys and, “Don’t judge me!” on a chat thread with 60 people regarding a fantasy football league will be classified the same way – because statistically, there is not much difference between how the word “judge” is placed within both sentences. However, newer tools that combine supervised machine learning with deep learning and NLP can learn the context of when the word “judge” is used as a noun (i.e., an adjudicator in a court of law) within an email thread with a small number of recipients versus when the word is being used as a verb on an informal chat thread with many recipients. The context of the data source and how words are used matters, and an advanced AI tool that leverages a combination of technologies can better understand that context.Using Advanced AI with TAROne common misconception regarding using newer, more advanced AI tools is that old workflows and models must go out the window. This is simply not true. While there may be some changes to review workflows due to the added efficiency generated by advanced AI tools (the ability to conduct privilege analysis simultaneously with responsive analysis, for example), attorneys can still use the traditional TAR 1.0 and TAR 2.0 workflows they are familiar with in combination with more advanced AI tools. Attorneys can still direct subject matter experts or reviewers to code documents, and the AI tool will learn from those decisions and predictive responsiveness, privilege, etc.The difference will be in the results. A more advanced AI tool’s predictions regarding privilege and responsiveness will be more accurate due to its ability to take nuance and context into consideration –leading to lower review costs and more accurate productions.ConclusionMany attorneys are still hesitant to move away from the older, AI eDiscovery tools they have used for the last decade. But today’s larger, more complicated datasets require more advanced AI tools. Attorneys who fear broadening their technology toolbox to include more advanced AI may find themselves struggling to stay within eDiscovery budgets, spending more time on finding and less time strategizing – and possibly even falling behind on their discovery obligations.But this fear and hesitancy can be overcome with education, transparency, and support from legal technology companies. Attorneys should look for the right technology partner who not only offers access to more advanced AI tools, but also provides implementation support and expert advisory services to help explain the technology and results to other stakeholders, opposing counsel, and judges.To learn more about the advantages of leveraging advanced AI within TAR workflows, download our white paper, “TAR + Advanced AI: The Future is Now.” And to discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com.ai-and-analytics; chat-and-collaboration-data; ediscovery-review; lighting-the-path-to-better-ediscoveryreview, ai-big-data, tar-predictive-coding, blog, ai-and-analytics, chat-and-collaboration-data, ediscovery-review,review; ai-big-data; tar-predictive-coding; blogai-analyticssarah moran

Below is a copy of a featured article written by Denisa Luchian for The Lawyer.com that features Lighthouse's John Shaw.A highlight of the challenges arising from the increased use of collaboration and messaging tools by employees in remote-work environments.Our “top trends” series was born out of a desire to help in-house lawyers with their horizon scanning and with assessing the potential risks heading their way. Each post focuses on a specific area, providing companies and their lawyers with quick summaries of some of the challenges heading their way.Our latest piece in the series looks at the top 3 trends in-house lawyers should take notice of in the area of employment disputes, and was carefully curated by one of our experts – Lighthouse director of business development John Shaw. The Covid-19 pandemic has affected every sector of law and litigation, and employment law is certainly no exception. From navigating an ever-changing web of COVID-19 compensation regulations, to ensuring workplaces are compliant with shifting government health guidelines – the last six months have been chaotic for most employers. But as we all begin to regain our footing in this “new normal”, there is another COVID-19-related challenge that employers should be wary of: the increased use of collaboration and messaging tools by employees in remote-work environments.This past spring, cloud-based collaboration tools like Slack and Microsoft’s Teams reported record levels of utilisation as companies around the world were forced to jettison physical offices to keep employees safe and comply with government advice. Collaboration tools can be critical assets to keep businesses running in a remote work environment but employers should be aware of the risks and challenges the data generated from these sources can pose from an employment and compliance perspective.Intermingling of personal and work-related data over chatAs most everyone has noticed by now, working remotely during a pandemic can blur the line between “work life” and “home life.” Employees may be replying to work chat messages on their phone while simultaneously supervising their child’s remote classroom, or participating in a video conference while their dog chases the postman in the background. Collaboration and chat messaging tools can blur this line even further. Use of chat messaging tools is at an all-time high as employees who lost the ability to catch up with co-workers at the office coffee station transition these types of casual conversation to work-based messaging tools. These tools also make it easy for employees to casually share non-work related pictures, gifs, and memes with co-workers directly from their mobile phone.The blurring line between home and work, as well as the increased use of work chat messaging can also lead to the adoption of more casual written language among employees. Most chat and collaboration tools have emojis built into their functionality, which only furthers this tendency. Without the benefit of facial expressions and social cues, interpretation of this more casual written communication style can vary greatly depending on age, context, or culture.All of this means that personal, non-work related conversations with a higher potential for misinterpretation or dispute are now being generated over employer-sanctioned tools and possibly retained by the company for years, becoming a part of the company’s digital footprint.Evidence gathering challengesEmployers should expect that much of the data and evidence needed in future employment disputes and investigations may originate from these new types of data sources. Searching for and collecting data from cloud-based collaboration tools can be a more complicated process than traditional searching of an employee’s email or laptop. Moreover, the actual evidence employers will be searching for may look different when coming from these data sources and require additional steps to make it reviewable. Rather than using search terms to examine an employee’s email for evidence of bad intent, employers may now be examining the employee’s emoji use or reactions to chat comments on Teams or Slack.Evidence for wage and hour disputes may also look a bit different in a completely remote environment. When employees report to a physical office, employers can traditionally look to data from building security or log-in/out times from office-based systems to verify the hours an employee worked. In a remote environment, gathering this type of evidence may be a bit more complex and involve collecting audit logs and data from a variety of different platforms and systems, including collaboration and chat tools. A company’s IT team or eDiscovery vendor will need to understand the underlying architecture of these tools and ensure they have the capacity to search, collect, and understand the data generated from them.Employer best practicesEmployers should consider implementing an employee policy around the use of collaboration tools and chat functionality, as well as a comprehensive data retention schedule that accounts for the data generated from these tools. Keep these plans updated and adjust as needed. Ensure IT teams or vendors know where data generated by employees from these new data sources is stored, and that they have the ability to access, search, and collect that data in the event of an employment dispute.chat-and-collaboration-data; microsoft-365microsoft, cloud, emerging-data-sources, blog, chat-and-collaboration-data, microsoft-365microsoft; cloud; emerging-data-sources; blogthe lawyer

In the modern age of legal technology, cybersecurity and eDiscovery are unquestionably intertwined. As cybersecurity threats escalate and bad actors find success with new methods and sophisticated tools to gain access to the ever-growing volumes and types of confidential electronic data, legal departments and law firms are getting hit daily by cybersecurity incidents and breaches, with many not even knowing when the incidents have occurred. The legal world, and eDiscovery in particular, are enticing targets, as matters typically involve huge volumes of sensitive information and data often resides across multiple providers who play a part in the collection, processing, hosting, review, and production of data.From a security perspective, corporations are constantly dealing with the data their employees create, and thus they typically maintain a solid system focused on maintenance, protection, back-ups, and defense of that data. This internal process is implemented using governance, risk, and compliance standards that run pretty well from the inside. But security gaps arise when that data becomes subject to a legal hold for litigation and that once well-protected data gets sent out to law firms and/or outside providers.So how can organizations feel confident they’re effectively evaluating the cybersecurity stability of their law firms, third parties, cloud providers, etc.? Do your providers have relevant security controls in place to ensure your data resides in a reasonably similar method as you would store the data yourself? Here are the top three tips for structuring an effective and comprehensive eDiscovery security evaluation and creating a strong relationship with your providers:Leverage Industry-Standard CertificationsAt the security evaluation stage, it’s critical to get to know your providers well and develop trusted relationships. The best way to first evaluate their overall security is to leverage industry-standard certifications. If the provider has access to and holds your data, they should be able to demonstrate that they’re ISO 27001 and SOC 2 certified as those have become the standard security environment protocol in the eDiscovery industry. Industry-standard questionnaires such as the SIG can also be used to validate a provider’s security structure. If a provider already has a completed and updated the SIG, this can be immediately accepted without needing to recreate the wheel and require another type of basic security assessment. This should serve as your baseline and will aid your risk assessments overall. It’s also important for organizations to audit, on an annual basis, those fundamental controls your providers have in place as the industry continues to focus deeper into all areas of each certification. The days of checking the standard audits off your list and being considered compliant are quickly becoming a thing of the past. With the increase in breaches, we are also seeing deeper and more thorough inspections beyond your own company and a shift to the provider space. So make sure you’re getting involved and staying involved with your suppliers. They are critical elements of your success and you need to treat them as such.Devise Security Questions That Go Beyond the BasicsIn addition to the standard certifications and questions the SIG and other general security audits give you, it’s also important to go beyond the basics and devise questions for your eDiscovery vendors that will uncover any existing gaps. Outside of questionnaires that simply ask for “yes” or “no” answers, consider doing regular audits with specific and focused questions. For example, ask your providers to discuss what different technologies they’re considering in the next 12 months or what new security certifications they’re planning to pursue. This ensures that you’re acting in a forward-thinking manner and developing better insight into your partners’ future development. To combat the growing cybersecurity threat, organizations need to remain one step ahead and devise questions to find forward-thinking suppliers rather than ones that just check the boxes. It’s also crucial to apply focused energy to the evolution of the organization and its suppliers. Take the time to have open dialogue and explore different solutions with the goal of prevention of threats. In today’s market, most organizations are still operating in a reactive state, meaning solutions are in place to detect malicious behaviors already inside your boundaries. Remember the clock always wins and prevention is the preferred way to stay ahead of attacks. Ask your technology providers the tough questions around ransomware and look to see what kinds of SLAs or guarantees they can offer. This is a great place to start to separate products and services by the maturity of their offering.Consider a Managed Services EnvironmentIn the most ideal of situations, a corporation would know in advance their list of trusted providers for investigations and litigation, and they would have a regular flow of communication with those providers that includes updates on standard certifications as well as regular audits including questions that go beyond the basics. Many times, this secure workflow can be best served by establishing a dedicated managed services environment that can support a more seamless and secure flow of data when a matter transitions to eDiscovery. Taking advantage of the dedicated services that come with a managed services environment, the corporation gets a technically skilled and more diverse talent base to draw from – one that becomes an extension of your team and treats the security of your data as if it were their own. Within that environment, law firms and document review lawyers all log into the same database and a partnership develops between all parties, creating a more secure environment. In addition, you’ll see cost savings by not having to invest in your own security infrastructure and separate cybersecurity personnel.Overall, vendor security is an integral part of an organization’s cybersecurity strategy. It’s imperative for corporations who transfer sensitive data out of their control to third parties to make sure that each and every supplier who handles the data meets all of the organization’s internal security requirements, as well as established regulatory requirements. This can be achieved by choosing providers who maintain industry-standard security certifications, performing regular audits outside of standard security questionnaires, and at the most secure level, by creating a managed services environment with your suppliers. data-privacy; ediscovery-reviewcybersecurity, cloud-security, ediscovery-process, blog, data-privacy, ediscovery-reviewcybersecurity; cloud-security; ediscovery-process; bloglighthouse

Legal Operations is a relatively new field and one that is constantly evolving. With that comes lots of new challenges as well as lessons learned around building an effective Legal Operations department. Below are six key takeaways from a recent Illumination Webinar Series webinar, where legal operations veterans discussed common pitfalls in legal operations, how to avoid them, and best practices for the future.Legal Operations is an Evolving Field - Whether you define it as herding cats, the land of misfit toys, or the grey space in legal, one thing is certain - legal operations is a multi-disciplinary evolving field. If you use the membership numbers from the Corporate Legal Operations Consortium (CLOC) as a barometer of the growth of the profession, the increase of professionals is 1000% from 2016 to 2019. The work these professionals are doing varies from organization to organization. However, there are a few core areas that most legal operations departments focus on - ebilling, contract lifecycle management, vendor management, legal workflows, and legal department data and analytics.Change Management is One of the Biggest Challenges - Legal operations is a cross-functional department that is responsible for driving change in legal. As such, it is not a huge surprise that change management and the things that go along with that are big struggles for the function. Gaining executive support, getting enough funding, and identifying key stakeholders are all critical in the first stage of trying to make a change. Additionally, gaining adoption after a change is made can be a challenge as lawyers don’t tend to be early adopters.Understanding the Issue and Putting in Time at the Outset of a Project Can Help You Overcome Challenges - When considering what to solve for, make sure you understand the impact and pervasiveness of each and prioritize the most pervasive and impactful. Then, take the time to truly diagnose the problem. Don’t get distracted by the symptoms. Once you have identified the right problems, make sure you spend plenty of time clarifying all the specifications and understanding where the blockers may be. This will prevent missteps later and allow you to move quickly if you hit any roadblocks. Finally, make sure you get buy in along the way. This starts with buy in from your stakeholders on the specifications. Then, as you start to execute, share out your successes at each step and get stakeholder buy in on those successes. These steps will increase the success of any project you are leading.Knowing your Audience and your Data Can Really Help With Success in This Field – At the onset of any project, identify who you cheerleaders and naysayers are, that way you can identify the challenges that may arise. It is also wise to take a look at what is working and incorporate that into your future state so you don’t inadvertently break something that is going well. Make sure that you are leveraging relevant data to both identify the proposed improvements as well as to show them once achieved. And finally, to create supporters and build relationships across functions, you should look at ways to fill in the gaps in the legal department and offer support on projects. With these tips, your projects should be smoother to roll out.Analytics and AI are the Future - As in much of the world, artificial intelligence and business analytics are a big point of discussion in the legal operations space. This can be anything from analytics on top of a single existing platform all the way to cross-software AI to predict the outcome of litigation. Discussions about and the implementations of these tools are expected to continue in the next several years. Another exciting change for the field is the influx of new talent. As this is a new field, many of the current professionals transferred from another discipline. However, programs are being created to train for this area that will generate an influx of new talent that will move our profession forward. Finally, we expect more defined rules of engagement, both within legal operations but also with other departments in the company. This field is new so those rules have only recently started to form. That should solidify over the next several years.The Impacts of COVID-19 Should Not Drastically Change the Profession - Operationally, we were in a good situation given that legal operations is in the technology space. Departments were easily able to shift to work from home. Additionally, budgetary impacts have been different than any impacts that companies as a whole have felt.Legal operations has evolved significantly and will continue to change as the field matures. legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse

The landscape for Hart-Scott-Rodino (HSR) filings has undergone immense flux over the last two years. The economic upheaval of the COVID-19 pandemic and regulatory shifts of a new presidential administration have impacted both the volume of large merger and acquisition (M&A) transactions and the scrutiny they receive from regulatory agencies. This makes it hard for businesses and law firms to know what to expect from upcoming M&As, including the likelihood of receiving a Second Request and how regulators will handle that investigation.Data on recent Second Requests can help by giving parties at least a general sense of what their peers are experiencing. Official numbers for 2021 won’t be published until autumn of this year — but we can look at past trends to try to predict those numbers to a reasonable degree.A close reading of historical data and current context suggests something of a paradox: The number of Second Requests in 2021 was likely fairly high but, at the same time, may have represented a historically small share of the year’s HSR filings. This is due to the extraordinary surge in HSR transactions and other factors, which are summarized below. For a full analysis, see our 2021 Second Request Trends Report.HSR filings plummet and rebound amid pandemic In 2020, the economic lockdown and business hesitancy caused by the COVID-19 pandemic brought HSR filings to their lowest total in 7 years. The Federal Trade Commission (FTC) and Department of Justice (DOJ) reported 1,673 filings for the year, of which 48 resulted in Second Requests. While this is less than the 61 Second Requests issued in 2019, it reflects the same annual percentage. That rate of 3% is slightly higher than the rates in both 2017 and 2018, which landed between 2 and 2.5%.Then, the economy surged in late 2020 and early 2021, bringing HSR filings with it. Preliminary data from federal agencies show HSR filings in 2021 more than doubled from the year before, reaching 3,644.Second Requests in 2021 likely resembled 2020 Most likely, the number of Second Requests in 2021 was close to the total in 2020. However, that means the percentage rate of Second Requests versus total HSR filings likely dropped significantly, by half or more.This is because maintaining the 3% rate from 2019-2020 seems unattainable. At that rate, agencies would have to investigate more than 100 proposed M&As — far beyond anything we’ve seen in the last 20 years.It’s also far too many for the FTC and DOJ to manage, given their recent struggles with capacity. Since December 2020, both agencies have made multiple budget requests and policy changes to help them keep up with the volume of transactions and workload associated with them. For example, FTC officials have publicly called for more time to review filings, saying the traditional review period of 30 days hasn’t, “kept pace with the increased volume and complexity of transactions and their related data and documents.”A more realistic rate for 2021, therefore, is somewhere between 1 and 2%. That would produce around 50 Second Requests — a total consistent with last year, as well as the average annual number over the last 20 years.HSR is more complex for everyone While HSR filings have clearly bounced back from their dip in 2020, the overall Second Request landscape is marked by complexity and uncertainty. Officials continue to make and seek revisions to regulations, making the terms of engagement a moving target. The soaring data volumes and diverse data sources cited by the FTC pose challenges for companies as well, who may find it increasingly difficult and expensive to meet HSR deadlines and other requirements.This was evident in a recent survey conducted by Lighthouse of more than 100 experts from corporations and law firms, who selected the following challenges as top of mind during the Second Request process:Getting the data in and processed quicklyEnsuring the deal goes throughProducing quicklyChoosing the right technologyThese responses underscore the need for parties to accurately read the landscape and leverage outside tools and expertise to improve speed and efficiency.For a deeper dive into the Second Request landscape, including insights from experienced attorneys in the field, a detailed primer on regulatory changes, and what to expect in the current year, check out our 2021 Second Request Trends Report.antitrusthsr-second-requests, blog, acquisitions, mergers, antitrusthsr-second-requests; blog; acquisitions; mergerslighthouse

Emerging challenges with big data—large sets of structured or unstructured data that require specialized tools to decipher— have been well documented, with estimates of worldwide data consumed and created by 2025 reaching unfathomable volumes. However, these challenges present an opportunity for innovation. Over the past few years, we’ve seen a renaissance in AI products and solutions to help address and evolve past these issues. From smaller players creating bespoke algorithms to bigger technology companies developing solutions with broader applications, there are substantial opportunities to harness AI and rethink how to manage data.A recent announcement of Microsoft’s Syntex highlights the immense possibilities for, and investment in, leveraging AI to manage content and augment human expertise and knowledge. The new feature in Microsoft 365 promises advanced AI and automation to classify and extract information, process content, and help enforce security and compliance policies. But what do new solutions like this mean for eDiscovery and the legal industry?There are three key AI benefits reshaping the industry you should know about:1. Meeting the challenges of cloud and big data2. Transforming data strategies and workflows3. Accelerating through automationMeeting the challenges of cloud and big data Anyone close to a recent litigation or investigation has witnessed the challenge posed by today’s explosion of data—not just volume, but the variety, speed, and uncertainty of data. To meet this challenge, traditional approaches to eDiscovery need to be updated with more advanced analytics so teams can first make sense of data and then strategize from there. Simultaneous with the need to analyze post-export documents, it’s also clear that proactively managing an organization’s data is increasingly essential. Organizations across all industries must comply with an increasingly complex web of data privacy and retention regulations. To do so, it is imperative that they understand what data they are storing, map how that data flows throughout the organization, and have rules in place to govern the classification, deletion, retention, and protection of data that falls within certain regulated categories of data types. However, the rise of new collaboration platforms, cloud storage, and hybrid working have introduced new levels of data complexity and put pressure on information governance and compliance practices—making it impossible to use older, traditional means of information governance workflows. Leveraging automation and analytics driven by AI advances teams from a reactive to proactive posture. For example, teams can automate a classification system with advanced AI where it reads documents entering the organization’s digital ecosystem, classifies them, and labels them according to applicable sensitivity or retention categories implemented by the organization—all of which is organized under a taxonomy that can be searched later. This not only helps an organization better manage data and risks upfront—creating a more complete picture of the organization’s data landscape—but also informs better and more efficient strategies downstream. Transforming data strategies and workflows New AI capabilities give legal and data governance teams the freedom to think more holistically about their data and develop strategies and workflows that are updated to address their most pressing challenges. For eDiscovery, this does not necessarily mean discarding legacy workflows (such as those with TAR) that have proven valuable, but rather augmenting them with advanced AI, such as natural language processing or deep learning, which has capabilities to handle greater data complexity and provide insights to approach a matter with greater agility. But the rise of big data means that legal teams need to start thinking about the eDiscovery process more expansively. An effective eDiscovery program needs to start long before data collection for a specific matter or investigation and should contemplate the entire data life cycle. Otherwise, you will waste substantial time, money, and resources trying to search and export insurmountable volumes of data for review. You will also find yourself increasingly at risk for court sanctions and prolonged eDiscovery battles if your team is unprepared or ill-equipped to find and properly export, review, and produce the requested data within the required timeline. For compliance and information governance teams, this proactive approach to data has even greater implications since the data they’re handling is not restricted to specific matters. In both cases, AI can be leveraged to classify, organize, and analyze data as it emerges—which not only keeps it under control but also gives quicker access to vital information when teams need it during a matter.Advanced AI can be applied to analyze and organize data created and held by specific custodians who are likely to be pulled into litigation or investigations, giving eDiscovery teams an advantage when starting a matter. Similarly, sensitive or proprietary information can be collected, organized, and searched far more seamlessly so teams don’t waste time or resources when a matter emerges. This allows more time for case development and better strategic decisions early on.Accelerating through automation Data growth continues to show no signs of slowing, emphasizing the need for data governance systems that are scalable and automated. If not, organizations run the risk of expending valuable resources on continually updating programs to keep pace with data volumes and reanalyzing their key information.The best solutions allow experts in your organization to refine and adjust data retention policies and automation as the organization’s data evolves and regulations change. In today’s cloud-based world, automation is a necessity. For example, a patchwork of global and local data privacy regulations (GDPR, California’s CCPA, etc.) include restrictions related to the timely disposal of personal information after the business use for that data has ended. However, those restrictions often conflict with or are triggered by industry regulations that require companies to keep certain types of documents and data for specific periods of time. When you factor in the dynamic, voluminous, and complex cloud-based data infrastructure that most company’s now work within, it becomes obvious why a manual, employee-based approach to categorizing data for retention and disposal is no longer sustainable. AI automation can identify personal information as it enters the company’s system, immediately classify it as sensitive data, and label it with specific retention rules. This type of automation not only keeps organizations compliant, it also enables legal and data governance teams to support their organization’s growth—whether it’s through new products, services, or acquisitions—while keeping data risk at bay. Conclusion Advancements in AI are providing more precise and sophisticated solutions for the unremitting growth in data—if you know how to use them. For legal, data governance, and compliance teams, there are substantial opportunities to harness the robust creativity in AI to better manage, understand, and deploy data. Rather than be inhibited by endless data volumes and inflexible systems, AI can put their expertise to work and ultimately help to do better at the work that matters. practical-applications-of-ai-in-ediscovery; ai-and-analytics; chat-and-collaboration-data; microsoft-365; lighting-the-path-to-better-information-governancemicrosoft, ai-big-data, cloud-security, blog, record-management, ai-and-analytics, chat-and-collaboration-data, microsoft-365,microsoft; ai-big-data; cloud-security; blog; record-managementmitch montoya

Recently we took Lighthouse’s legal technology podcast series Law and Candor on the road and broadcast a special live edition to our audience straight from Legaltech. One episode focused on the issue that’s at the forefront of the eDiscovery and information governance world: data privacy compliance in the post-GDPR world. Our distinguished Law and Candor hosts spoke with special guest Kelly Clay, global eDiscovery counsel and head of information governance at GlaxoSmithKline (GSK), about the key challenges or “opportunities” that GDPR, CCPA, and other burgeoning laws around data privacy have presented, and subsequently how the associated risks have permanently shifted the legal landscape.With the two-year anniversary of GDPR’s first day of implementation right around the corner, it’s a perfect time to reflect on where we are now. Organizations around the world have become more comfortable with the idea that data governance, privacy, and security are more than just new challenges they are being forced to solve. Businesses are beginning to see the new opportunities that come from data privacy regulations as they realize the benefits that come from cross-functional stakeholders working together across all of their internal support functions.So what are organizations doing to get a handle on the information governance side of the house and ensure compliance in this post-GDPR era? Here are three steps to take on the road to continual compliance:Understand where your data resides. It might seem obvious, but the number one place to start (and some would argue the most important) is taking a detailed look at your data and understanding all of the different types your organization generates, and the various locations where it all resides. Many who have already embarked on this journey have found silos during the process and encountered complications in understanding the full extent of their data and where it is. Now’s the time to use the information you gather to create a detailed and comprehensive data map that can be easily and automatically updated as new locations and new data are constantly created.Focus on the general principles. It’s easy to get overwhelmed in the data mapping process, especially if you’re a large organization whose employees utilize many different communication methods and IT has traditionally employed disparate storage methods for that never-ending mountain of data. Once your data map is in place, take a step back and realize you can’t tackle every potential compliance issue at the same time. Instead, continue to focus on the overall general principles like understanding where the data is flowing from and where it’s going, whether it’s email, chats, or data in the Cloud.Change the narrative. Historically, Legal and IT have operated separately and handled data based on the nature of their specific job functions. For example, Legal views data and information through the lens of risk management, while IT has a different approach in how it views managing and archiving data within an enterprise. With GDPR, CCPA, and likely many more privacy regulations to come, organizations need to handle data differently and understand everyone is accountable and must work cross functionally. Key players from the technology group to the procurement team to the business strategy group must change their mindset and be mindful of how they deal with data while keeping legal risk at the forefront.Ultimately, the post-GDPR era is here to stay and organizations should treat these dramatic changes in how we view and handle data as an opportunity not a challenge. Getting a handle on how to create an effective compliance program is a team effort that requires everyone to get on the same page, and it’s particularly important to involve your key stakeholders early on in the process.More on this topic can be found in this article, How GDPR and DSARs are Driving a New, Proactive Approach to eDiscovery. data-privacy; information-governanceccpa, gdpr, cloud-security, blog, data-privacy, information-governanceccpa; gdpr; cloud-security; bloglighthouse

Lawyers, and the legal field in general, are not exactly known for their willingness to embrace new technology and change the tried and true, traditional ways they’ve always used to practice law. But as technology has taken over our everyday lives and become the norm across most industries, there’s no time like the present for lawyers and litigation support professionals to take a second look at how they can get up to speed on the best and newest eDiscovery technology that will ultimately transform their business, and in turn, create happier clients who are laser focused on reducing costs and increasing efficiency.Like cassette tapes and the beloved Walkman, when it comes to eDiscovery, that old model of managing your own IT infrastructure and utilizing on-prem review platforms is becoming a thing of the past. This reminds me of other eDiscovery relics we knew and loved… not to call anyone out, but dare I mention Concordance or Clearwell in case you’re still using them?!In this changing technology landscape where most clients are moving (or have moved) their data to the cloud, it’s a perfect match to also modernize your law firm’s eDiscovery program and adopt a self-service, spectra model that will work seamlessly with data stored in the cloud, and deliver less risk and more benefits for both you and your clients.Just what are those benefits? Here are three reasons why adopting new technology and going to a SaaS eDiscovery solution will bring added efficiency, more billable hours, and happier clients.Eliminate the Risk and Expense of Managing Your Own IT Infrastructure - For law firms, managing an IT infrastructure and maintaining servers for the purpose of hosting client data is expensive and involves a large amount of risk. Electronic data has become overwhelmingly voluminous and types of data have become so much more complex than when law firms first got into this business and we were primarily dealing with email. Think about mobile devices, chat data, ephemeral communication, etc. as just the tip of the iceberg. With cybersecurity as a top concern for corporations, I think it’s fair to say that law firms probably never meant to take on the risk that comes with managing a complex IT infrastructure for their clients. Having a self-service, spectra, modern SaaS solution at their fingertips, law firms can lower costs and transfer the risk of hosting client data to the SaaS solution provider.Using SaaS Review Platforms Improves Client Services - Not only will a SaaS solution provide the benefit of relieving the security and risk burden, it will improve client services which is a win-win for the firm and the client. Although on-prem review platforms are what law firms have typically used, a SaaS platform reduces costs and improves efficiency. With an on-prem solution, license fees and infrastructure maintenance fees generally create out-of-pocket costs with no cost recovery mechanism. Moving to a SaaS solution introduces new ways to recover costs and makes solving substantive client concerns the primary job, rather than the inefficiencies that come along with maintaining an on-prem solution. To make the process of implementing a SaaS solution much easier, it’s important to note at this stage that building a business case and getting senior management on board with upgrading to a SaaS solution is critical. That way all parties understand the benefits to both the firm and its clients will be on the same page with making the change.Upgrading to SaaS Allows Firms to Provide the Latest Technology to Clients - Wouldn’t it be amazing if you could easily and quickly upgrade your eDiscovery technology and always provide the latest and greatest technology to clients? Moving to a SaaS platform immediately provides this benefit as the service provider maintains the infrastructure and makes technology upgrades behind the scenes for you. In case you’re feeling a little nervous that opportunity for some portions of internal work will disappear with this eDiscovery model, in fact the opposite is true. This isn’t a threat to the traditional litigation support model. It will instead allow for a greater focus on more valuable and strategic work while a solid partnership is established with the trusted service provider who runs the infrastructure of the SaaS platform and will work alongside you.If your primary goal is to create efficiency, lower costs, and ultimately make your clients happy, now’s the time to take your eDiscovery program to the next level and adopt a SaaS, self-service, spectra solution. You’ll have a modernized eDiscovery platform that allows for independent access and control to process, review, and produce data, while removing the risk and cost that comes with managing an IT infrastructure.ediscovery-review; ai-and-analyticscloud, self-service, spectra, cloud-security, blog, ediscovery-review, ai-and-analyticscloud; self-service, spectra; cloud-security; bloglighthouse

We often get questions from our clients about how best to select an electronic discovery vendor. Important considerations in this process are what questions to ask, how best to compare vendors and what are the important issues that are typically missed in the selection process. In particular, our clients often tell us that they sometimes struggle in the vendor selection phase to be able to best assess the quality and capabilities of a vendor. Given the challenges of choosing the right vendor, we often hear that law firms default to making their decision based almost exclusively on price considerations. Our list of questions can help you make the right decision based on more than just price.Top Questions To Ask When Choosing an eDiscovery VendorScope of ServicesWhat services does the vendor offer?If case parameters change, will the vendor be able to meet your needs and time frames?Are there volume benefits/discounts if you use multiple services (e.g. processing, hosting and production versus just hosting)?What services are sub-contracted out and does data ever leave the vendor’s site?What size or type of case is too big for the vendor?What have been vendor’s toughest cases?Expertise (Not all vendors are created equal; and it is not all about price)What is the vendor’s knowledge level of the technical issues?Are the vendor’s employees certified in the tools they use?What is the vendor’s level of understanding of the legal process?Are there legal professionals on staff?How does the vendor’s expertise compare to other vendors?Quality of ServicesIs this a vendor that you could see yourself establishing a longer term relationship?How does the vendor manage ensuring high quality service consistently: accurate and on-time?Are errors tracked? What are considered errors? How are errors addressed?What do the references say about the vendor?Customer ServiceWhat hours does the vendor operate?How available are the vendor’s employees during non-business hours?How much lead time is needed for processing and production?How are cases staffed?Who is the primary point of contact? Is it the same throughout the case?What is the nature of the vendor’s project management team and approach?How are issues escalated?Technical SpecificationsDoes the vendor use proprietary versus non-proprietary software and what are the benefits/trade-offs?If the data is not being processed locally, what is the vendor’s FTP connection speeds and how does this compare with the law firm’s FTP speeds?What is the vendor’s policy on backing up data?What is the vendor’s policy regarding storing data?ediscovery-reviewediscovery-process, blog, ediscovery-review,ediscovery-process; bloglighthouse

In 2016, European companies doing business in the US were able to breathe a sigh of relief. The European Commission deemed the Privacy Shield to be an adequate privacy protection. For the next half a decade, this shield, as well as Standard Contractual Clauses (SCCs), created the foundation upon which most global businesses were able to manage the thousands of data transfers that occur in each of their business days.Everything changed in July 2020 when the Court of Justice of the European Union gave its seismic judgment in a case generally known as Schrems II. As we will see, the decision has a particular impact on any companies relying on, or moving to, a cloud computing strategy. Businesses have been left needing to make a risk decision with seemingly no ideal outcome. Some legal, privacy, and compliance teams may be advocating for staying away from a cloud approach in light of the decision. The business teams, however, are focused on the vast array of benefits that cloud software offers.So what is the right decision? Where does the law stand and how do you manage your business in this uncertain time? In this four-part blog series, we’ll explain the impact of Schrems II, provide practical tips for companies in the midst of making a cloud decision, give specific advice regarding companies who have, or are implementing, Microsoft’s cloud offering (M365), and offer our view as to the future.Schrems II and Its ImpactFirst, let;s look at the Schrems II decision. The background to the case is well worth exploring but for the sake of brevity and providing actionable information we’ll focus on the outcome and the consequences. The key outcomes impact the two primary ways in which most data transfers between Europe and the US:The EU-US Privacy Shield was invalidated with immediate effect.SCCs (the template contracts created by the EU Commission which are the most common way in which data is moved from the EU) were declared valid, but companies using SCCs could no longer just sign up and send. A company relying on SCCs would have to verify on a case-by-case basis that the personal data being transferred was adequately protected. This process is sometimes called a Transfer Impact Assessment, although the court did not coin that phrase. If the protection is inadequate, then additional safeguards could be needed.The consequences of the decision are still revealing themselves, but as things stand:The Privacy Shield (used by more than 5,000 mostly small-to-medium enterprises) has gone with no replacement in sight (although the Biden administration appears to recognise its importance with the rapid appointment of the experienced Christopher Hoff to oversee the process).There have been significant developments in relation to SCCs, additional safeguards, and transfer impact assessments:The US published a white paper to help organisations make the case that they should be able to send personal data to the US using approved transfer mechanisms.The European Data Protection Board (EDPB) published guidance on how to supplement transfer tools.The European Commission published draft replacement SCCs.The EDPB and the European Data Protection Supervisor adopted a joint opinion on the draft replacement SCCs requesting several amendments.There is not a clear timetable as to when the replacement SCCs or EDPB guidance (which has completed a period of publication consultation) will be finalised. The sooner the better because there seem to be inconsistencies between them. For example, the Schrems II judgment and draft replacement SCCs permit a risk assessment (i.e., it is possible to conclude that personal data might not be completely protected, but that the risk is so small that the parties can agree to proceed), whereas the EPDB recommendations seem to deal in black and white with no shades between (i.e., there is either adequate protection or there is not). It will be important to monitor which, if any, of these drafts moves and in which direction. Whether the SCCs are supported with a risk assessment or analysis along the lines of the EDPB recommendations (or perhaps both), going forward using SCCs may be rather cumbersome particularly in a cloud environment where the location and path of the data is not always crystal clear. Companies are therefore in something of a grey triangle, the sides of which are a judgment of the highest European Court, a draft replacement to the SCCs the Court reviewed in its judgment, and draft guidance about additional safeguards. In part two </span><span>of the series, we will offer companies some practical guidance on how to move forward in light of this grey triangle.To discuss this topic further, please feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governancemicrosoft, data-privacy, blog, privacy-shield, data-privacy, microsoft-365, information-governance,microsoft; data-privacy; blog; privacy-shieldlighthouse

By now, legal teams facing discovery are aware of many of the common technology and technology-enabled workflows used to increase the efficiency of document review on a single matter. But as data volumes grow and legal budgets shrink, legal teams must begin to think beyond a “matter-by-matter” approach. They must start applying technology more innovatively to create efficiencies across matters to minimize the burden of repeatedly reviewing the same documents again and again. Fortunately, many common technology-enabled review workflows (e.g., technology assisted review (TAR), advanced search guided by linguistic experts, and AI-powered review analytics) can help teams apply work product and insights from past matters to current and future matters. This not only saves time but also increases consistency and lowers the risk of inadvertent disclosures and cumbersome clawbacks.The opportunity to reduce repeated review is quite large, both because the problem is rampant and the technology that can help solve it is underutilized. A 2022 survey by the ABA showed that “predictive coding” is the least common application of eDiscovery software, used by only one in five law firms. In fact, 73% of respondents said they don’t know what predictive coding is (we explain it below). As document review continues to grow in complexity, and budget and other constraints apply pressure from other directions, more organizations should consider taking advantage of everything that technology has to offer.Repeated review is a large and familiar burdenRepeated review is baked into the status quo. Matters spanning multiple jurisdictions, civil litigations tied to government investigations, and matters involving the same or related IP are just a few examples in which the same documents could come up for review multiple times. Instead of looking across matters holistically, legal teams often feel obligated to roll up their sleeves, lower their heads, and review the same documents all over again—even when relevancy overlaps and for categories of information that remain relatively static across matters (privilege, trade secret, personally identifiable information (PII), etc.). This has obvious consequences for time and cost. The time invested on reviewing documents for privilege in a current matter, for example, becomes time saved on future matters involving those same documents. Risk is a factor as well. A document classified as privileged, or that contains PII or another sensitive category, in one matter should be classified the same way in the next one. But without a record of past matters, attorneys start over from scratch each time, which opens the door to inconsistency. And while it’s certainly possible to undo the mistake of producing sensitive documents, it can be quite time-consuming and expensive.Rejecting the status quo While the burden and risks associated with repeated review are felt every day, few legal teams and professionals are searching for a solution. Those willing to look beyond the status quo, however, will see that repeated review isn’t actually necessary, at least not to the degree that it’s done today. We also find that the keys to reducing repeated review lie in technology that many teams already use or have access to.Reusing work product from TAR and CAL workflows TAR 1.0, TAR 2.0, and Continuous Active Learning (CAL) workflows use machine learning technology to search and classify documents based on human input and their own ability to learn and recognize patterns. This is called predictive coding and it’s most often used to prioritize responsive documents for human review. The parameters for responsiveness change with the topics of each matter, so it’s not always possible to reuse those classifications on other matters. TAR and CAL tools can also be effective at making classifications around privilege, PII, and junk documents, which are not redefined from matter to matter. If a document was junk last time (say company logos attached to emails, blank attachments, etc.) it’s going to be junk this time too. Therefore, reusing these classifications made by technology on one matter can save legal teams even more time in the future. Refining review with linguistic expertsLinguistic experts add an extra layer of nuance to document review technology that makes them more precise and effective at classification. They develop complex criteria, based on intricate rules of syntax and language, to search and identify documents in a more targeted way than TAR and CAL tools.They can also help reduce repeated review by conducting bespoke searches informed by past matters. This process is more hands-on than using TAR and CAL tools; human linguists take lessons learned from one matter and incorporate them into their work on a related matter. It’s also more refined, so it can help in ways that TAR and CAL tools can’t.Litigation related to off-label drug use offers a good example. A company might have multiple matters tied to different drugs, making relevance unique for each matter. In this scenario, linguistics experts can identify linguistic markers that show how sales reps communicated with healthcare providers within that company. Then when the next off-label document review project begins, documents with those identifiers can be segregated for faster review. In this way, work from linguistic experts in one matter can help improve efficiency and minimize first-level review work on new matters. Apply learnings across matters using AI Review tools built on AI can reduce repeated review by classifying documents based on how they were classified before. AI tools can act as a “central mind” across matters, using past decisions on company data to make highly precise classifications on new matters. The more matters the AI is used on, the more precise its classifications become. The beauty here is that it applies to any amount of overlap across matters. The AI will recognize any documents that it has reviewed previously and will resurface their past classifications.Some AI tools can even retain the decision on past documents and associate it with a unique hash tag, so that it can tell reviewers how the same or similar documents were coded in previous matters—without the concern of over-retaining documents from past matters. Curious to challenge your status quo?TAR, AI, and other solutions can be invaluable parts of a legal team’s effort to curb repeated review — but they’re not the only part. In fact, the most important factor is a team’s mindset. It takes forethought and commitment to depart from the status quo, especially when it involves unfamiliar tools or strategies.The benefits can be profound, and the road to achieving them may be more accessible than you think.Find tips for starting small, as well as more information about how and why to address the burden of repeated review, in our deep dive on the subject.ai-and-analytics; ediscovery-review; lighting-the-path-to-better-ediscoveryreview, ai-big-data, blog, ai-and-analytics, ediscovery-reviewreview; ai-big-data; blogminimizing-re-reviewsarah moran

It feels fitting that the summer of 2020 would bring us Schrems II. This surprising Court of Justice of the European Union (CJEU) decision wreaked havoc in late July by invalidating the EU - U.S. Privacy Shield and calling into question other mechanisms for transferring the personal data of EU citizens into the United States (and beyond) under the GDPR. Let’s take a deeper dive into that decision and what it means for companies that need to transfer EU citizens’ data into the U.S.Shrems HistorySchrems II is the second decision by the CJEU that is based on privacy complaints made against Facebook by Austrian privacy activist Max Schrems. Both cases stem from privacy concerns related to the U.S. National Security Agency (NSA)’s ability to access the personal data of EU citizens, famously disclosed by Edward Snowden in 2013.In the first Schrems decision in 2015, the CJEU invalidated the U.S. - EU Safe Harbor Framework (the predecessor to the EU - U.S. Privacy Shield) as a means to transfer personal data from the EU into the U.S., finding that the protections afforded by the Safe Harbor framework did not meet fundamental privacy rights guaranteed within the EU to EU citizens.In the aftermath of the first Schrems decision, the U.S. Department of Commerce and the EU Commission collaborated to implement the EU-U.S. Privacy Shield as a replacement to the Safe Harbor Framework, again allowing for a broader transfer mechanism of personal data into the U.S. compared to the alternatives (namely, “standard contractual clauses” (SCCs) and “binding corporate rules” (BCRs) – more on those below). Since its implementation in 2016, over 5,000 organizations have met the requirements administered by the International Trade Administration to join the Privacy Shield. Meeting those requirements can mean a large investment for organizations in overhauling their data privacy practices.That brings us to Schrems II, wherein Schrems brought a second complaint against Facebook, this time challenging the validity of SCCs as a mechanism to transfer personal data into the U.S. In Schrems II, he argued that the same privacy concerns related to the NSA’s ability to access EU citizens’ personal data under the Safe Harbor framework also applied to personal data transferred via an SCC. It should be noted here that around the same time, European privacy advocates also filed a challenge to the new EU-U.S. Privacy Shield with the European Court.Schrems II CJEU DecisionIn the Schrems II ruling in July, the CJEU ultimately decided to address both the EU-U.S. Privacy Shield and SCC issues.The Court upheld the validity of SCCs as a means to transfer personal data from the EU into the U.S. However, rather than carte blanche approval, the Court laid out obligations for both parties of an SCC and data protection supervisory authorities within the EU. Those obligations include:Entities that are transferring personal data of EU citizens into the U.S. must verify “on a case by case basis” that the protections afforded by the SCC can be met and that there is an “adequate level of protection” in the U.S. to protect the personal data of EU citizens.Entities that are receiving personal data of EU citizens in the U.S. have an obligation to notify the data exporter if they are unable to comply with the SCC for any reason.Data protection supervisory authorities within the EU have a mandatory obligation to evaluate not only the terms of the SCCs themselves, but also whether the data protections afforded by the U.S. legal system can meet those terms. If the SCC is found to be insufficient, the supervisory authority has an obligation to stop the transfer.This decision puts SCCs (and thereby BCRs) on shaky ground throughout the entire world, because the threshold set by the Court applies to any third country, not just the U.S. (see Questions 2 and 6 of the FAQ issued by the European Data Protection Board for more information on these points).However, the real kicker of Schrems II for U.S.-based companies with an international presence is that the CJEU completely invalidated the EU-U.S. Privacy Shield. The Court found that the U.S. does not provide sufficient protection of EU citizens’ personal data because of the access the U.S. government has to EU citizens’ personal data and because EU citizens have no means of redress against U.S. authorities should their privacy rights be violated.What Does Shrems II Mean for Companies that Need to Transfer Personal Data from the EU into the U.S.Companies that were relying on the Privacy Shield to transfer EU data into the U.S. should:Work to put individual SCCs or BCRs in place to achieve these transfers. There is no grace period during which a company can keep transferring data using the Privacy Shield mechanism, according to the European Data Protection Board (see Question 3 for more information).Continue to comply with all current Privacy Shield obligations. While the CJEU decision invalidates the Privacy Shield, it does not relieve current participant organizations of their obligations.Watch for further guidance from both the European Data Protection Board and the U.S. Department of Commerce (DOC). DOC and the European Commissioner for Justice issued a joint press release in early August, stating that they have initiated discussions to evaluate the potential for an enhanced EU-U.S. Privacy shield framework that would meet the requirements laid out by the CJEU.Companies that rely on SCCs or BCRs as a means to transfer personal data should: Conduct a risk assessment to determine whether those agreements and the recipient of the data in the U.S. can provide an adequate level of data protection, according to the European Data Protection Board (see Questions 5 and 6 for more information).Watch for further guidance from data protection authorities in relevant countries related to SCCs and BCRs in the wake of Schrems II. The transfer of personal data between countries is vital to the lifeblood of many companies, large and small. While Schrems II has thrown a wrench into the legality of those transfers… all is not lost. Stay tuned for updates from U.S. and EU authorities that may help ease the burden of this unexpected decision by the CJEU. Resources for More Information CJUE Schrems II full decision: http://curia.europa.eu/juris/document/document.jsf?text=&docid=228677&pageIndex=0&doclang=en&mode=lst&dir=&occ=first&part=1&cid=16606736CJEU press release on its Schrems II decision: https://curia.europa.eu/jcms/upload/docs/application/pdf/2020-07/cp200091en.pdfEU – U.S. Privacy Shield Program Schrems II FAQs: https://www.privacyshield.gov/article?id=EU-U-S-Privacy-Shield-Program-UpdateEuropean Data Protection Board Schrems II FAQs: https://edpb.europa.eu/our-work-tools/our-documents/ovrigt/frequently-asked-questions-judgment-court-justice-european-union_enS. Secretary of Commerce Wilbur Ross Statement on Schrems II ruling and the importance of EU-U.S. data flows: https://www.commerce.gov/news/press-releases/2020/07/us-secretary-commerce-wilbur-ross-statement-schrems-ii-ruling-andJoint press statement from the U.S. Secretary of Commerce and the European Commissioner regarding initiated discussions for a new privacy shield: https://www.commerce.gov/news/press-releases/2020/08/joint-press-statement-us-secretary-commerce-wilbur-ross-and-europeanUK’s Information Commissioner’s Office updated statement on the Schrems II decision: https://ico.org.uk/make-a-complaint/eu-us-privacy-shield/To discuss this topic further, please feel free to reach out to me at SMoran@lighthouseglobal.com. Or, take a look at other Worldwide Data Privacy Updates.data-privacycloud-security, blog, data-privacycloud-security; blogsarah moran

In the eDiscovery space, we are always spotting new trends. Our industry has seen text messages, chat message platforms, websites, and various unstructured data sources become increasingly relevant during discovery. Over the past several years, we have started to see another new trend emerge - many of our clients are using Corporate G Suite rather than Office 365.The use of emerging technologies is part of everyday life for many companies in the space. However, we are beginning to see established biotech, healthcare, manufacturing, and retailers shift to G Suite, an area that was once almost exclusively dominated by on-prem Microsoft products. This transition introduces some new considerations around managing discovery. In this post, we talk about three impacts that G Suite data has on downstream eDiscovery workflows, and the need to factor these items into your discovery plan. Recipient Metadata: Gmail renders email header information in a unique format. While the last-in-time email in a given string will have all expected sender and recipient information (From, To, CC, BCC), all other previous messages exchanged in the email string will display only the sender information and will not display the recipient information. This is not a collection, processing, metadata, or threading issue. Rather, this relates to how Gmail stores and exports recipient information. This presents some unique document review challenges, as previous parts of the thread could include recipients that are not visible to the reviewer, and may include attorneys who have sent privileged communications. As a result, it is important to work closely with your project management team to create workflows related to Gmail. ‚ÄçLinks: Historically, we have all attached copies of documents (e.g. Word, Excel, and PowerPoint files) to an email during the normal course of business. Due to the emergence of technologies such as SharePoint and Google Drive, we now have the ability to send emails with embedded links that reference documents rather than attaching the document itself. When Gmail is exported from Google Vault, the documents referenced in links embedded throughout email exchanges are not exported. As a result, reviewers will encounter these links, but will be unable to readily view the corresponding document referenced in said link. At present, Google Vault does not allow for the mass search and export of these links. However, you do have the ability to manually pull documents referenced in these links. You should be mindful of this issue when drafting your ESI protocol, as opposing parties and regulators may request that your company retrieve these documents.‚ÄçExported Load File: Unlike a standard PST export, when you export a mailbox or set of documents from Google Vault, you have the ability to retrieve a corresponding load file that contains metadata captured in G Suite. Sometimes, the date-related metadata extracted during processing, will not align with dates exported from G Suite. There are a variety of legitimate reasons for this. You will need to determine if you want to produce the date metadata extracted from the processing platform, date values exported from Vault, or both.All of the above items are manageable when in-house legal teams, outside counsel, and eDiscovery vendors work together to proactively implement appropriate downstream eDiscovery workflows. If you have experience with G Suite data or thoughts on managing the discovery of G Suite data, please reach out to me at ashier@lighthouseglobal.com.chat-and-collaboration-data; information-governancechat-and-collaboration-data, information-governanceemerging-data-sources; g-suite; preservation-and-collection; blogalison shier

The Schrems II decision invalidated the EU-US Privacy Shield – the umbrella regulation under which companies have been transferring data for the last half-decade. In earlier parts of this four-part series, we described the impact of the Schrems decision, discussed how companies should evaluate their risk in using cloud technologies, and took a deeper dive on M365 in light of Schrems II. In sum, if you are a global business that previously relied upon Standard Contractual Clauses (SCCs) to transfer data, there is no clear guidance on what to do currently.It is even murkier in a cloud environment because the location of the data is not as transparent. Fortunately, there are ways to undertake a risk assessment to determine whether to proceed with any new cloud implementations. In the case of Microsoft products, there is also additional support from Microsoft with changes in its standard contractual terms and features in the product to mitigate some risks. Even so, many companies are holding off making any changes because the legal landscape is evolving. In this final part, we opine on what the future may hold. We can expect in the first half of this year that the European Commission will finalise the amended SCCs. We can anticipate that the EDPB will also produce another draft of its recommendations concerning data transfers. We should see plenty of risk assessments taking place. Even for companies adopting a “wait and see” policy in terms of taking significant steps, those companies should still be looking at their data transfers and carrying out risk assessments to make sure they are as well placed as possible for the moment when the draft SCCs and EDPB guidance are finalised.It would not be a surprise to see Microsoft continue to expand and develop M365 so that it offers yet more services that could be used as technical measures to reduce the risk around data transfers. These changes would strengthen the position of any company doing business between Europe and the US using M365.We do not have a crystal ball, and like many of you, are eager to see what happens next in this space. We will continue to monitor and keep you up to date with developments and our thoughts. If you have any questions in the meantime, feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governance; chat-and-collaboration-datamicrosoft, cloud, data-privacy, blog, law-firm, data-privacy, microsoft-365, information-governance, chat-and-collaboration-datamicrosoft; cloud; data-privacy; blog; law-firmlighthouse

In part one of this series, we described the state of the EU-US Privacy Shield and the mechanisms global companies have relied upon to transfer data from their multiple locations. In short, a recent decision – Schrems II – invalidated the Privacy Shield and shook the foundation of Standard Contractual Clauses (SCCs). Companies are now left asking the question of how to respond.In this post, we will share our view on how to navigate forward. If your organization is not already highly reliant on cloud software, we recommend weighing the benefits and risks of making that move. As you assess your options, keep in mind that this move may come at a higher cost because of the need to do periodic risk assessments during this uncertain time. For those already in the Cloud, the motto here is “do everything that you reasonably can.” The position no company wants to find itself in is one of stasis. It is difficult to see such a position being looked upon favourably should regulators start to investigate how companies are responding to Schrems II and the consequences that go along with it.The touchstone is the EDPB guidance and its six-stage approach to assessing data transfers, which we recommend companies undertake:Identify your data transfers: It is an obvious first step, although in practice this could prove challenging. You’ll need to know all the scenarios where your data is moved to a non-European Economic Area (EEA) country (at the time of writing this article, the UK, although out of Europe, is still under the European umbrella until at least the 30th of June).Identify the data transfer mechanisms: You need to decide the grounds upon which the transfer is taking place, such as on the basis of an adequacy decision (this does not apply to the US), SCCs, or a specific derogation (such as consent).Assess the law in the third country: You need to assess “if there is anything in the law or practice of the third country that may impinge on the effectiveness of the appropriate safeguards of the transfer tools you are relying on, in the context of your specific transfer.” There is more guidance from the EDPB as to how the evaluation should be carried out (i.e., an independent oversight mechanism should exist). How effective or practical it is to suggest each company has to perform its own thorough legal assessment as the entire range of relevant legislation in any importing country is open to debate and might perhaps be considered further as these recommendations are refined.Adopt supplementary measures if necessary to level up protection of data transfers: The EDPB has published a non-exhaustive list of such measures, which essentially fall into one of three categories - technical (i.e., encryption), contractual (i.e., transparency), and organisational (i.e., involvement of a Data Protection Officer on all transfers). We’ll have a look at these measures in more detail below in relation to Microsoft 365.Adopt necessary procedural steps: If you have made changes to deliver the required level of protection, these need to be embedded into your operation (i.e.., by means of policy).Re-evaluate at appropriate intervals: This is not a job that can be completed and then left. It needs continual monitoring. There is no specific guideline as to what an appropriate interval is, but quarterly is probably a reasonable approach.Essentially this boils down to carrying out a risk assessment and taking steps to mitigate the risks that are uncovered. If your cloud strategy includes Microsoft 365, the next part of this blog series is a must-read. We will share what Microsoft has done in response to Schrems II as well as some specific configuration options that will influence steps 4 and 5, listed above. Bear in mind that these recommendations could change and you should watch the space. To continue the discussion or to ask questions, please feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governancemicrosoft, cloud, data-privacy, blog, corporate-legal-ops, data-privacy, microsoft-365, information-governance,microsoft; cloud; data-privacy; blog; corporate-legal-opslighthouse

The International Women’s Day (IWD) theme for 2021 is “choose to challenge.”What a fitting theme for a year when 5.4 million women lost their jobs and over 2.1 million women left the workforce, while the COVID-19 pandemic wreaked havoc, and social and racial inequity issues were raised to the forefront of the international consciousness. There was certainly no shortage of challenges for women to choose from this past year.However, the IWD initiative website elaborates on the “choose to challenge” theme by noting that “a challenged world is an alert world and from challenge comes change.” It is that idea that should really resonate with us, as we move past 2020 and into 2021. There have been many examples this year of women who have chosen to rise to the challenges presented in 2020 and by doing so, have created change for other women.In keeping with this theme, Lighthouse is featuring five such women in the legal and technology fields. Five women who have risen to the challenges presented this year and created change. Those five women are:Laura Ewing-Pearle, eDiscovery Project Manager at Baker Botts LLPJenya Moshkovich, Assistant General Counsel at GenentechGina M. Sansone, Counsel – Litigation Support at Axinn Veltrop & Harkrider LLPAmy Sellars, Director, Discovery Center of Excellence at Cardinal HealthRebecca Sipowicz, VP and Assistant General Counsel at Ocwen Financial CorporationWe had the honor of interviewing these inspirational women about the “choose to challenge theme” – including the stressors of 2020, how to empower other women, how to leverage innovation to shape a more gender-equal world, and how to address social justice issues. That discussion led to some powerful lessons on how to rise to our current challenges and create meaningful, lasting change.Empowering Women Durning a PandemicLike any societal change, empowering women starts small, at the individual level. We do not have to wait for some grand opportunity or postpone our effort until we have the time to volunteer – especially during a pandemic when our personal time may feel even more precious and many in-person volunteer opportunities have halted. Empowerment can happen by simply reaching out to the women around us – women we work with, women in our personal lives, and women within our own families.Laura Ewing-Pearle noted, “One principle to keep in mind is that women are not a monolithic bloc, and that empowering women usually means empowering the individual. A woman with twenty years’ experience in the legal world caring for aging parents has a different set of stressors and goals than a woman fresh out of school with a toddler, especially under the new Covid protocols…Seeing past “woman” to the individual brings us all closer to a more gender-equal world.”In our professional lives, empowering at the individual level can mean reaching out to our women co-workers, teammates, and those that may be on “lower rungs” of the corporate or law firm ladders and offering them a chance to sit down (virtually) for a cup of coffee to talk about their personal goals and challenges. This provides women a space to be heard and seen, first and foremost. It is from these conversations that the seeds of change are often planted.Rebecca Sipowicz stated, “During the summer I became responsible for co-oversight of our back-office team in India, which is approximately 25% female. For at least the past 10 years, the India team has not reported, directly or indirectly, to a woman. I have reached out on an individual level to these women to discuss their career goals and how we can work together to achieve them. I also started a monthly “catch-up” where, in this virtual environment, we can meet for 30 minutes to talk about work, life, and the state of the world. Through these conversations, I have not only gotten to know better my colleagues who are located off-shore but also have been able to share life experiences, such as how to take advantage of our remote work world while parenting and managing online school. The continued growth of this group of employees is one of my most important goals for 2021.”These conversations often help us learn not only about individual ambitions and challenges, but also may help us learn about unsung accomplishments and milestones that women often are less apt to tout about themselves within their own organizations and networks. In turn, this can provide an excellent opportunity to be a champion for those women, by calling out successes that would otherwise go unrecognized.Gina Sansone said, “I am a strong believer in being a vocal cheerleader for the women around me who may be less comfortable with promoting their strengths and accomplishments. Women often play multiple roles at work and at home that are not obvious to others and get overlooked because they tend to be less measurable in a traditional sense. These contributions are nonetheless valuable and crucial to an organization and the lives of others, and it’s really important to notice and appreciate them along the way.”Empowering at the individual level also means leading by example during these conversations. The stressors of the pandemic have changed our lives dramatically, both professionally and personally. It is unchartered territory for everyone, and studies are showing that women are shouldering the brunt of the burden at home – often juggling full-time virtual schooling with children while working full-time jobs or dealing with the bulk of household maintenance. Leading by example and being honest about ourselves and our own hurdles during our conversations can empower women to be honest about their own struggles and needs.Jenya Moshkovich stated, “[I empower other women by] being honest about my own challenges and creating and holding space for others to be their true, authentic selves with all the complexities and messiness that can bring. The line between our private lives and work is blurrier now than it has ever been and we have to let go of trying to pretend that we have it all together all the time because no one does, especially these days.”The example we set and the honesty with which we portray ourselves can especially be important for those closest to us – the people within our own families and homes.Rebecca Sipowicz mentioned, “…Having my children home from school for six months enabled my 11-year-old daughter to witness firsthand how involved my job is and to learn how difficult but rewarding it is to juggle parenting and a career. This is a valuable lesson for all children, not just girls.”Leveraging Innovation to Shape a More Gender Equal WorldIf the legal and technology industries have anything in common, it is that women have been historically under-represented in both spaces. Fortunately, technological innovation can help close the gender gap in both industries:Rebecca Sipowicz shared, “The pandemic really pushed all of corporate America to take steps that will help to advance gender equality in the workplace – namely the move from in-office to remote work. This unquestionably provides working mothers with more equal access to the workplace. Through the use of video software such as Zoom and Teams, and the ability to work around parenting responsibilities, fewer women should feel the pressure to leave the workforce in order to parent….This flexibility allows women to continue to contribute to the workforce and grow in their careers while caring for their families, without feeling like they are short-changing either side. This should enable women to continue to take on more prominent roles and push women throughout the world to request an equal seat at the table.”Technological innovation can also help people push their organizations and law firms to empower women and support equality. Many companies have seen how innovation and technology can help close the gender gap, and we can work within those systems to further those efforts.Gina Sansone said, “I really don’t know how we can begin to work toward a gender-equal world without leveraging innovation. To me, innovation means creating a dynamic work environment that encourages everyone to move forward, which could mean training and managing members of the same team differently. While consistency is important, recognizing differences, being flexible, and empowering people to think differently and not simply check a box are steps toward shaping a more gender-equal world.”Laura Ewing-Pearle added, “Encouraging and leveraging more on-line training certainly helps anybody juggling family and career to keep pace with new technology and change. I’m grateful that Baker Botts as a firm encourages everyone to create new, innovative ideas to improve business processes and culture.”Jenya Moshkovich mentioned, “I am very fortunate to work for a company that has started innovating in this space years ago and where I am in the position to benefit from these efforts. Since 2007, Genentech has more than doubled the percentage of female officers from 16 to 43% and today over half of our employees and over half of our directors are women. In our legal department, ALL of our VPs are women. Genentech’s efforts to move towards gender equality have included senior leadership commitments, programs to drive professional development and open up opportunities for career advancement, among others.”Going forward, it will be equally important to continue efforts to support changes in our industry. While we have come a long way and made considerable progress, it is still important to push companies and law firms to recognize equity gaps and encourage the use of innovation and technology to help close those gaps.Amy Sellars stated, “Corporate practices favor men, and Covid exacerbates this problem. Will companies acknowledge that women took on most of the additional burdens of children at home, education at home, of people at home all the time (more dishes, more cleaning, more cooking, less dry cleaning, and more laundry)?”Rebecca Sipowicz said, “It is up to all of us to make sure that the realization that flexibility can result in increased productivity and satisfaction continues long after the pandemic, allowing women (and men of course) to have the best of both worlds.”Addressing Social Justice and Equality Issues2020 was also a devastating year for people of color, as well as underrepresented and low-income communities. The tragic events throughout the year brought social inequality issues and systemic racism to the forefront of the conversation in many families, workplaces, and social circles. Many of the lessons learned in the fight for gender equality can also be applied to the fight for racial and social equality. For instance, just as empowering women can start at the individual level, the fight for social and racial equality can also start with small, individual acts.These acts can be as simple as personally working to educate ourselves on the work to be done, so that we can act on social justice issues in the most impactful way:Jenya Moshkovich said, “2020 was a difficult year in so many ways including the tragic deaths of George Floyd, Breonna Taylor, and Ahmaud Arbery and many incidents of xenophobic violence against Asian Americans. My personal focus has been on educating myself, speaking up for others, listening, and fostering belonging. And there is so much more that needs to be done.”Gina Sansone added, “The social issues raised in 2020 were unfortunately just a magnification of issues that have existed for a long time. It was a perfect storm of events that certainly made me and others face the thought patterns, inequalities, and general civil unrest that has been festering in our society. It is very easy to live in a bubble and lose sight. I think one of the most important things that happened was people stopped being quiet and just accepting. Change will not happen unless it is absolutely forced and we need to continue recognizing that the world is not equal.”Creating social justice change also can mean utilizing the education we do have about these issues, and working within our communities to help in any way possible – both at the individual level and on a broader scale:Amy Sellars stated, “My husband and I have always been passionate about voting rights and participate in get out the vote efforts. 2020 was a particularly important year for voting issues, as so many people were isolated and had even less access to register to vote or get to polls than normal. Working with the League of Women Voters, we did neighborhood registration drives, and we volunteered as non-partisan poll watchers. We also picked up Meals on Wheels shifts. All around the country, meal recipients who used to be fed at central locations were transitioned to home deliveries, and it has taken an army of volunteers in personal vehicles…We are also volunteering on the domestic crisis hotline.”We can also leverage the networks and programs put in place within forward-thinking organizations to help bring about social change. More and more law firms and organizations are working to help close the gender gap and fight racial and social inequity. Employees of those organizations are in a unique position to join those initiatives to make more of an impact:Laura Ewing-Pearle said, “While (Baker Botts) had resources in place prior to the events of last year, the firm has also increased efforts over the past twelve months to address social issues including greater outreach to diverse communities, and creating a significant pro bono partnership with Official Black Wall Street, among other major initiatives.”Rebecca Sipowicz added, “I am a member of the Ocwen Global Women’s Network (OGWN), which supports the attainment of Ocwen’s goals in diversity, inclusion, and talent development. I am also on the planning committee for the National Association of Women Lawyers (NAWL) mid-year meeting. NAWL’s mission is to empower women in the legal profession, while cultivating a diverse membership dedicated to equality, mutual support and collective success. Membership in and support of organizations such as NAWL and OGWN provide me with a platform to address the diversity and social issues that permeated 2020.”‍ConclusionThe lesson learned from these strong women during a year full of challenges is that seemingly “small” acts can have big impacts. Change starts with all of us, at an individual level, working to empower women and make impactful societal changes – one person, one organization, and one community at a time.Thank you to the five women who participated in our 2021 International Women's Day Campaign! Take a look at our 2020 and 2019 International Women's Day campaigns for more inspiring stories of women in our industry making bold moves to promote gender equality.For more information, please reach out to us at info@lighthouseglobal.com.diversity-equity-and-inclusionblog, diversity-equity-and-inclusion,bloglighthouse

eDiscovery pricing has always been nuanced and inconsistent across vendors and technology providers, making it difficult for law firms and corporations alike to compare and contrast options. So, it is no big surprise that this same challenge exists across self-service, spectra eDiscovery tools and software as well, making it extremely challenging to model out an apples-to-apples comparison across solutions. This inability to accurately compare costs across different platforms leaves you and your team in the dark when it comes to choosing the right tool and pricing model to fit your needs.The ChallengeToday’s self-service, spectra solutions are frequently priced based on data sizes/volumes at different phases of the eDiscovery processing, review, and production workflow, often with each of these steps having their own cost trigger associated with them. For example, many solutions charge based off of hosted volume, raw data size, or even post-extraction data volume, while others charge a flat-fee per matter.Although attractive on their face, on a per matter plan you may be in good shape if you are able to entirely self-support, but any requests for help or training are frequently not included in the flat-fee. The lack of the ability to predict the future needs for support make the flat-fee a riskier choice. While paying for eDiscovery based off of per GB sizes is a very popular method, not knowing the expansion rates, the hosted volume, or not needing an entire data-set post culling and filtering means you may fall victim to data size anomalies or paying for data you don’t need.Lastly it is important that you make sure to understand the full ecosystem of potential charges to avoid any surprises. Make sure to understand if there are other costs or “gotchas” you need to be aware of around user fees, OCR costs, Bates endorsement fees, user trainings, additional license fees to other platforms, costs to process specific file types, language translation, etc. Not to mention, you also have to consider the various technology platforms that are included and assess the need for ongoing expert support.There is no perfect pricing model. The key to all of this is choosing the right model for you and your eDiscovery profile, but, how do you go about that?The SolutionWhen you are evaluating pricing for self-service, spectra platforms and you have narrowed down to a few technology providers that offer technology that fits your needs, make sure to leverage the following tips to ensure you’re making an informed comparison:Trust but verify. Ask the technology provider to explain the price point and both how and when it is measured. Discuss how the confluence of the eDiscovery workflow and cost actually come together. Will all workflows trigger all cost points? Do you have to pay for technology you don’t want or need? Understanding the answers to these questions will allow you to get a big picture understanding and to get a feel for where you may see your costs rise or decrease.Set up a real case example. Ask the potential providers to use your actual data volumes to illustrate what the cost would like look for a given period of time (i.e. a month or even a few years). This will allow you to see what actuals would be across platforms as well as give you the opportunity to explore different pricing models with the vendor to meet your budgetary constraints.Use a pricing calculator. Create a pricing calculator to compare self-service, spectra tools. Add as many variables as you would like to understand across all possible scenarios and across the different platforms you are evaluating. Leverage this to compare bottom-line numbers and determine the right fit for you. Additionally, lean on your vendor to help you build this out and make a comparison.To discuss this topic more or to learn how we can help you make an apples-to-apples comparison, feel free to reach out to me at bthompson@lighthouseglobal.com.ediscovery-reviewcloud, self-service, spectra, ediscovery-process, blog, ediscovery-review,cloud; self-service, spectra; ediscovery-process; blogbrooks thompson

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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