Case Studies

We work with our clients to solve complex data problems, address compliance and privacy challenges, and achieve better legal outcomes. Read the case studies.

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January 24, 2024
Case Study

AI Powers Successful Review in Daunting Second Request

AI Powers Successful Review in Daunting Second Request With limited time and no margin for error, Lighthouse identifies responsive, privilege, and key docs quickly and accurately Key Actions Integrated the latest in analytics and review for faster, more consistent results. Used regulator-approved, battle-tested AI models for responsive and privilege review tasks. Key Results 3.6M starting documents reduced to 670K produced docs. 2.2K unique privilege log descriptions drafted by AI and approved/edited by attorneys. Document production and privilege logging completed ahead of schedule. 300 key docs (0.05% of produced documents) delivered for early case analysis and deposition preparation. Two Months to Tackle Three Million Documents A financial institution responding to a Hart-Scott-Rodino Second Request by the Department of Justice had 2 months to review 3.6M documents (2.4TB of data) to reach substantial completion. With that deadline, any time that reviewers spent on irrelevant documents or unnecessary tasks risked pushing them off schedule. So outside counsel called on Lighthouse to help efficiently produce documents to regulators. AI and Experience Prove Up to the Challenge Using our Second Request review solution, we devised an approach that coordinated key data reduction tactics, modern AI, and search expertise at different stages of review. Junk Removal and Deduplication Set the Stage We started by organizing the dataset with email and chat threading and removing 137K junk documents. Then we shrank the dataset further with our proprietary deduplication tool, which ensures all coding and redactions applied to one document automatically propagate to its duplicates. AI Model Removes 1.5 Million Nonresponsive Documents To build the responsive set, we used our AI algorithm, built with large language models for sophisticated text analysis. We trained the model on a subset of documents then applied it to all 2.2M TAR-eligible documents, including transcripts from chat platforms. The model identified 80% of the documents containing responsive information (recall) with 73% accuracy (precision). The final responsive set consisted of 650K family-inclusive documents—18% of the 3.6M starting corpus. AI Supports Privilege Detection, QC, and Descriptions Our AI Privilege Review solution supported reviewers in multiple ways. First, we used a predictive algorithm in conjunction with privilege search terms to identify and prioritize potentially privileged documents for review. During QC, we compared attorney coding decisions with the algorithm’s assessment and forwarded any discrepancies to outside counsel for final privilege calls. For documents coded as privileged, we used a proprietary generative AI model to draft 2.2K unique descriptions and a privilege log legend. After reviewing these, attorneys left nearly 1K descriptions unchanged and performed only light edits on the rest. Search Experts Surface the 300 Documents Most Important for Case Prep Alongside the production requirements for the Second Request, Lighthouse also supported the institution’s case strategy efforts. Each tranche of work was completed in 4 days and within an efficient budget requested by counsel, who was blown away by the team’s speed and accuracy. Using advanced search techniques and knowledge of legal linguistics, our experts delivered: 130 documents containing key facts and issues from the broader dataset, for early case analysis. 170 documents to prepare an executive for an upcoming deposition. Beating the Clock Without Sacrificing Cost or Quality With Lighthouse Review—including the strategic use of state-of-the-art AI analytics—outside counsel completed production and privilege logging ahead of schedule. The financial institution met a tough deadline while controlling costs and achieving extraordinary accuracy at every stage.
December 15, 2023
Case Study
Key document identification, KDI, ai-and-analytics

Lighthouse Litigation Prep Proves Invaluable in Complex Litigation

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.
December 15, 2023
Case Study

Lighthouse Uncovers Key Facts In Misappropriation Investigation

Searching for Evidence in 8TB of Chat and Technical Data Senior executives at an information technology company suspected that former employees had utilized company resources and intellectual property when starting a rival company. To determine whether litigation was called for, executives needed to find the most relevant documents within 8TB of processed data. The data was extremely complex, dating back 6+ years and consisting mostly of Slack data and attachments including highly technical documents, applications, logs, and related system files—tallying over ten million files. The company engaged a senior partner at an AM50 law firm, who recommended using keyword search terms, filters, and targeted linear review to find the “smoking gun” documents—which was estimated to take several months. The company came to Lighthouse looking for a faster, more strategic search alternative for their investigation. Pinpointing Key Docs with Linguistic Analysis Two Lighthouse search and linguistics experts met with company executives to learn exactly what information they suspected the former employees had misappropriated. From there, our experts created linguistic-based search criteria that go well beyond keywords, taking into consideration the unique vocabulary and syntax of software engineers and developers, the conversational quirks of Slack and other chat-based communications, and the coded language used by people who are trying to get away with something. The team delivered documents in 2 batches, refining their search based on input from the executives—and resulting in only 39 files for the company to review. Getting Results—and a Start on Case Strategy—in Days In less than 10 days, 2 Lighthouse experts pierced the subterfuge in the employees’ chat messages to reveal patterns in their behavior and attempts to cover their tracks. In all, we found 39 documents representing possibly questionable conduct, which required only 141 hours of eyes-on review. In comparison, using conventional analytics would have identified 5-20% of the search population as key documents—up to 50K documents to review in this matter. So in the end, Lighthouse saved the company over 3 months and nearly $200K.Armed with knowledge of the key events, timelines, and context of conversations buried within the data, the company was primed to begin litigation efforts and had a team ramped up to perform additional searches when needed.Lighthouse KDI vs Linear Review
September 22, 2023
Case Study

Lighthouse Transforms Complex Enterprise Data Protection with Microsoft Purview

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
September 7, 2023
Case Study
antitrust, ai-and-analytics-ediscovery-review, kdi, key document identification

Lighthouse Key Document Identification Proves Pivotal to Antitrust Defense

Lighthouse leveraged linguistic expertise and cutting-edge analytics to efficiently locate only the documents that mattered in a complicated, year-long antitrust criminal investigation and trial. What They Needed Senior executives from a global food manufacturing company faced federal criminal antitrust charges related to allegations of 15 instances of price fixing over a five-year period. A joint defense team comprised of outside counsel representing each of the executives was assembled by the company. The prosecution expected to make rolling productions of evidence up to and through the trial. As those productions rolled in, the joint defense team could tell that many of the evidentiary documents, timelines, and conversations that were key to the prosecution’s case were taken out of context or failed to include all the exculpatory evidence. However, the joint defense team was having trouble finding key evidence because much of the nuance was located within piecemeal chat conversations and complex bid spreadsheets that were buried among millions of similar documents. The joint defense team needed a document search team that was nimble and could quickly identify the most important documents to the defense and share them across the team. They came to Lighthouse because we could quickly identify key documents with accuracy and nuance. How We Did It Lighthouse first organized a central search desk, where all members of the joint defense team could go for document search requests, with results shared across three defense teams. Next, the Lighthouse team located the most important documents related to each of the 15 episodes of price-fixing allegations, on a priority basis. They used linguistic expertise to create narrow searches, taking into consideration the nuance of acronyms, slang, and terminology used within the company and the food manufacturing industry. They also leveraged Lighthouse’s proprietary, cutting-edge search analytic tools to look for key information buried in hundreds of thousands of Excel spreadsheets and chat messages. As the government produced more documents, the Lighthouse team refreshed their searches, looking for key documents in each new production and quickly sharing results across the defense team. As defense preparations continued throughout the year, we we supported all aspects of trial preparation, including two mock trials, all witness preparation binders, and the James hearing. Lighthouse support will continue through the criminal trial for the senior executives, due to our proven success in supporting ad hoc search requests and providing results in real time. The Results The Lighthouse team efficiently delivered incredibly accurate results, saving the underlying client more than $3M thus far. Out of an always-in-flux review population that eventually grew to over 16M documents, Lighthouse was able to cull through the irrelevant data to find and deliver only the most important documents for the defense team’s utilization. In the end, that amounted to less than 1% of the initial review population, including: 4.7K documents for the joint defense group to defend the episodes of alleged price fixing 5.3K documents for defense team’s specific ad hoc and witness kit requests (an average of 400 documents per witness kit) In comparison, a traditional linear review using search terms and conventional analytics performed by multiple case teams typically results in 5-20% of the data population being tagged as “key documents.” This volume would then be funneled to the case teams for review as well, where they would waste valuable time and resources looking at hundreds of thousands of irrelevant or run-of-the-business documents. In addition to cost-efficiency, the team has gained expertise in the key events, timelines, and context of conversations buried within the data. As such, the team is now a critical resource to the defense, supporting all stages of the investigation and assisting in pivot ad hoc requests. Examples include finding a unique pricing document buried among volumes of near duplicates, as well as the relevant context surrounding a single line of a chat message. In the end, Lighthouse saved the underlying company significant time and money that could not have been achieved otherwise. Additionally, our expertise in the data was a critical resource to the joint defense team, which relied on Lighthouse at each step of trial preparation. Lighthouse expert support will continue throughout the criminal trial. ‍ Corporate Case Studyantitrust; ai-and-analytics; ediscovery-reviewantitrust, ai-and-analytics-ediscovery-review, kdi, key document identification
September 7, 2023
Case Study
ediscovery-review, ai-and-analytics, biotech

Alignment and Savings Across a Dynamic Portfolio

A global biotech achieves consistent and efficient document review with Lighthouse review. Key Actions Coordinating efforts across disparate review teams and counsel Integrating advanced AI and other innovations on an incremental basis ‍ Key Results Streamlined and efficient approach to document review Saving more than $340,000 through a tailored workflow in one recent matter A Lack of Coordination Drove High Costs and Complexity Document review for a global biotech was expensive and inconsistent, due to a high frequency of litigations with often overlapping timelines and different outside counsel. Lighthouse had been managing the company’s electronically stored information (ESI) for years, saving the company hundreds of thousands of dollars through plans and policies introduced over time. After learning of our expertise in managed review, the company hired Lighthouse to bring order and efficiency to that domain as well. Laying a Foundation with Standard Protocols Our first order of business was to establish universal standards across matters, outside firms, and review vendors. These included: Upstream changes , such as data management protocols that made documents easier to search and sort. Overarching review protocols , such as QC process guidelines and specifications for production. Changes to specific tasks , such as refining privilege filters and standardizing coding layouts so review performance could be compared across different matters and teams. A Lighthouse review manager trained all current firms and vendors and was on hand to monitor progress and answer questions, as well as onboard new firms and vendors as needed. Increasing Efficiency Through Technology Over time, Lighthouse gradually introduced accelerators to help increase efficiency and cost savings. Initially, this consisted of: Deduplication improvements , through strategies like single-instance review and normalized deduplication. Review accelerators such as privilege log automation and redaction automation. To drive even more savings, Lighthouse led the company through a test-and-learn process for building workflows around advanced AI and other, more in-depth technology. The process involved trying out a new technology on a live matter, then conducting a post-mortem to clarify what worked and what could be improved. In this way, Lighthouse and the company developed a rubric for determining which workflows were the right fit for different matters. Streamlined, Aligned, and Eager to Keep Innovating In 5 years, Lighthouse transformed the company’s disconnected, manual, expensive approach to document review into a coordinated and robust program that boosts efficiency at every level. For one recent matter—a patent litigation with a tight timeline overlapping the winter holidays—this review program drove extraordinary efficiency and savings. Tailoring the client playbook for the specific matter, the review manager designed a complex workflow that reduced eyes-on review: The initial dataset of almost 8M documents was reduced to a corpus of 388K through deduplication, culling, and removal of embedded and redundant documents. The population was further reduced through search hit only protocols and by employing a continuous active learning (CAL) model, stopping review when responsive documents became scarce. Finally, Lighthouse reunited document family members, automatically giving members tied to responsive documents the coding of their source docs. In the end, Lighthouse: Reduced eyes-on review to just 92K documents (25% of the documents promoted to review) Saved the company an estimated $341,000 in review costs Going forward, the company is ready to increase its use of technology, including classifiers built with advanced AI and an automated workflow for redactions of personally identifiable information (PII). Corporate Case Studyai-and-analytics; ediscovery-reviewediscovery-review, ai-and-analytics, biotech
August 3, 2023
Case Study
Case-Study; client-success; ai-and-analytics; analytics; document-review; eDiscovery; fact-finding; investigations; KDI; key-document-identification; keyword-search; TAR; TAR-Predictive-Coding; technology-assisted-review; machine-learning; transportation-industry; automotive-industry; edicovery-review; ai-and-analytics

Unprecedented Review Accuracy and Efficiency in Federal Criminal Investigation

A global transportation company was under investigation for possible infractions of the Foreign Corrupt Practices Act (FCPA) in India. The company’s legal counsel needed to quickly produce responsive documents and find key documents to prepare their defense. Key Results 4M total documents reduced to 250K through 2 rounds of responsive review, with precision rate and recall of 85% or higher. 810 key documents quickly delivered to outside counsel, saving them hours of review and gaining more time for case strategy. A Complex Dataset Requiring Nuanced Approaches The company collected 2M documents from executives in India and the U.S. Information in the documents was extremely sensitive, making it critical to produce only those documents related to the India market. This would be impossible for most TAR tools, which use machine learning and therefore can’t reliably differentiate between conversations about the company’s business in India from discussions solely pertaining to U.S. business. Finding key documents to prepare a defense was challenging as well. The company wanted to learn whether vendors and other third parties had bribed officials in violation of the FCPA, but references to any such violations were sure to be obscure rather than overt. Zeroing In On the Right Conversations Lighthouse used a hybrid approach, supplementing machine learning models with powerful linguistic modeling. First, our linguistic experts created a model to remove documents that merely referred to India but didn’t pertain to business in that market, so that the machine learning TAR wouldn’t pull them into the responsive set. Then our responsive review team developed geographic filters based on documents confirmed as India-specific and used those filters to train the machine learning model. The TAR model created an initial responsive set, which our linguists refined even further with an additional model, based on nuances of English used in communications across different regions of India. By the end, our hybrid approach had reduced the corpus by 97%, with an 87% precision rate and 85% recall. Once this first phase of review was successfully completed, Lighthouse dove into an additional 2M documents collected from custodians located in India. Finding Key Documents Among Obfuscated Communications To help inform a defense, our search specialists focused on language that bad actors outside the company might have used to obfuscate bribery. The team used advanced search techniques to examine how often, and in what context, certain verb-noun pairs indicating an “exchange” were used (for instance, commonly used innocent pairings like give a hand vs. rarer pairs like give reward). The team could then focus on the documents containing language indicating an attempt to conceal or infer. $1.7M Saved, 810 Key Documents Found to Support Defense Lighthouse performed responsive review on two datasets of 2M documents each, reducing them to less than 250K and saving the client more than $1.7M. Out of the 237K responsive documents, Lighthouse uncovered 810 hot docs spanning 7 themes of interest. The work was complete in just 3 weeks and enabled outside counsel to provide the best defense to the underlying company. Corporate Case Studykdi; key-document-identification; case-study; investigations; reviewediscovery-review; client-success; ai-and-analyticsCase-Study; client-success; ai-and-analytics; analytics; document-review; eDiscovery; fact-finding; investigations; KDI; key-document-identification; keyword-search; TAR; TAR-Predictive-Coding; technology-assisted-review; machine-learning; transportation-industry; automotive-industry; edicovery-review; ai-and-analytics
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