Case Studies

Key ResultsDocument set reduced from 750,000 to 158,000 documents Review speed increased from 10 to up to 60 docs/hour from bulk issue coding AI privilege model trained for reuse, improving speed and consistency 310 key documents identified across six core topics Production delivered with confidence, accuracy, and defensibility The Challenge: A Sweeping Request and a Tight Timeline At the outset, the FTC issued an expansive request that pulled in more than 750,000 records including emails and Slack messages. Agreement on keywords proved difficult, as regulators pushed for maximum disclosure.Lighthouse supported outside counsel through nine rounds of negotiation, including line-by-line responses to regulator objections, landing on a refined population of 158,000 documents—an 80% reduction in review scope. Review at Scale: Fast, Focused, and Credible One immediate challenge with prioritized document review for this matter was the large number of issue codes. Previously, similarly complex issue codes had slowed review to just 10 documents per hour. Moreover, outside counsel expected the FTC to heavily scrutinize the issue code distribution, making accuracy and nuance critical. To guide reviewers away from default or overly broad issue codes, a classifier was used to apply issue codes to responsive documents. Three refinement cycles ensured the issue codes were applied accurately, and as counsel directed. This method not only passed regulator scrutiny, review was accelerated by 4.5-6x. Key Document Identification and Proactive QC In parallel to review, Lighthouse began 4 rolling deliveries of key documents supporting six topics. Over four weeks, the team surfaced a highly-curated set of 310 documents to support case strategy. The work to identify key documents was also used to identify documents that were likely under-coded by contract reviewers—enabling the team to course-correct in real time. Building an AI Privilege Model for This Matter—and the Next The team next trained an AI privilege model to support privilege review, not just for this matter, but for future matters as well. The process began with a linguistically curated sample set, which counsel coded with future applicability in mind. The trained AI privilege classifier analyzed documents, delivering outputs in Relativity, allowing reviewers to reference privilege scores as part of their decision-making. Technical Execution: Overcoming Real-World Complexity Behind the scenes, Lighthouse had to address several technical hurdles. The review was hosted in RelativityOne, and initial data connectors required custom adjustments to work with the client’s Slack and metadata structure. In particular, Lighthouse developed a workaround to solve for Slack transcripts, which didn’t have file extensions, thus breaking standard ingestion processes.

The ChallengeIn a high-stakes regulatory investigation for a heavily regulated client, outside counsel faced a massive task: produce a 200,000-entry privilege log with specificity, consistency, and speed—without drawing regulatory fire. The Lighthouse SolutionLighthouse’s GenAI-powered privilege log solution gave outside counsel something neither traditional privilege log methods or other GenAI privilege log solutions could: customized, defensible entries at scale—with almost no manual drafting by review teams or outside counsel. What set it apart? The human-in-the-loop model. Lighthouse AI experts partnered with the legal team to fine-tune outputs for that matter’s unique needs, iterating on key components of each log line until the results were exactly right. Why It WorkedRather than force-fit the log into one-size-fits-all templates or get stuck with GenAI outputs that weren’t a good fit for this very unique matter, Lighthouse tailored and continuously iterated our GenAI prompting across three key dimensions: Document Type (e.g., Email, Memo) Legal Hook (Why the document is privileged e.g., “requesting legal advice”)Subject Matter (What the privileged information is generally regarding)How We Did ItOutside counsel needed subject matter descriptions to be as specific as possible without giving away privilege content, while creating uniformity across the document type and legal hooks based on the unique documents at issue in the investigation. Through prompt engineering and targeted feedback with outside counsel, the AI’s first draft evolved from raw potential to precision output that exactly met their needs:100+ document types condensed to a consistent set of 9 that outside counsel needed ‍80+ legal hooks refined down to 8, specific to the way attorneys worked at the underlying company ‍120,000+ unique Re: line descriptions that explained specific legal projects and work, none reused more than 1% of the time The Results200K+ log entries generated on a tight timeline No vague or red-flag phrasing—achieved by iterating with GenAI prompts to ensure that negative language caught in QC was removed across the entire privilege log Near-zero manual drafting by the legal team Custom configurations (e.g., suppressing references to specific entities) tailored to client preferencesFocused QC efforts where it mattered—resulting in massive time and cost savingsThe ROIOutside counsel’s job? Review, not write. By shifting their time to targeted QC and feedback instead of manual drafting, the legal team met their deadline under pressure—and under budget.

Company Overview A global Fortune 500 manufacturing company with facilities and offices across North America, Latin America, Europe, Asia, and Australia.ChallengesThe company was evaluating Microsoft Purview E5 licenses to support its information protection, insider risk management, data loss prevention, and sensitivity labeling goals. The data protection team needed to validate the efficacy of the Purview tools when applied to company data within their M365 environment. The data project leader shared a list of use cases to test against the platform’s risk identification and alert capabilities. SolutionLighthouse’s consultants designed and ran a four-month pilot to test Microsoft Purview’s sensitivity labeling, Data Loss Prevention (DLP), Insider Risk Management (IRM), and Defender for Cloud Apps capabilities across the client’s live Microsoft 365 environment. The team configured and validated more than 10 distinct data protection policies, including global personal information labels for Exchange, Teams, OneDrive, and endpoint devices. The project included six sensitive information types (such as PII, PCI data, and passport numbers), and piloted risk-based alerts for questionable user and departing employee behavior. Lighthouse developed a detailed Report Card and Recommendations Report, delineating a clear path for full implementation of validated controls company-wide. Key OutcomesDuring the initial four-month engagement, Lighthouse’s experts successfully validated each use case, demonstrating that Microsoft Purview E5 was indeed the correct tool for the client’s data protection needs. The client purchased Purview E5 licenses and engaged Lighthouse to guide the full implementation of all the capabilities we had piloted. By following the guidance of Lighthouse data experts, the company’s data protection team developed an ongoing, flexible data protection strategy and program which mitigated multiple risks by automating data classification, labeling, and user notifications. Lighthouse helped this client accelerate its data protection maturity model and establish best practices, workflows, and classifiers to strengthen data privacy and security. We can do the same for you. Contact an expert to get started.

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.

How Lighthouse DeliveredLighthouse piloted its tailored end-to-end eDiscovery experience, including our self-service eDiscovery solution (Lighthouse Spectra) and deep capabilities in forensics, full-service support, and advanced AI tools that are driving ROI for law firms now (including custom predictive and GenAI technology). The firm’s eDiscovery team was particularly drawn to Lighthouse’s early investment and leadership in these practical AI solutions.The OutcomeFollowing a successful pilot, the firm selected Lighthouse as a strategic eDiscovery partner. The decision was driven by Lighthouse’s ability to meet the firm’s need for both flexible, self-directed tools and deep bench strength in complex discovery. As a result, the firm:Adopted Lighthouse Spectra as its self-service eDiscovery platformEngaged Lighthouse for digital forensics, full-service eDiscovery, and advanced AI solutions—including custom predictive models and generative AINamed Lighthouse a preferred eDiscovery provider, formalizing a partnership focused on innovation and efficiencyLighthouse Solutions Delivered

The Challenge Four executives from a multinational food company were sued by the Department of Justice for alleged price fixing. A joint defense group of law firms represented the executives and sought a fast, flexible way to find key documents for the case. The SolutionLighthouse utilized Key Document Identification (KDI) to serve as a central search desk to lower costs for the group’s firms and ensure consistency across case teams. ResultsLighthouse reduced the 16M documents down to 10k that were useful to counsel and saved the client an estimated $3M by supporting the joint defense group with a single team. In all, we supported the client through three trials: Two resulted in mistrials, and the third resulted in a complete acquittal.

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.

The challenge wasn’t just about volume—it was about orchestrating a symphony of moving parts. Each jurisdiction had its own unique scope of relevancy and was managed by different case and eDiscovery teams. To tackle this challenge, Lighthouse architected a strategic workflow powered by AI. The cornerstone of the approach was creating a unified document repository alongside jurisdiction-specific databases and training a team of specialized reviewers to handle both universal and jurisdiction-specific responsiveness criteria. The results exceeded expectations on multiple fronts. The review scope was reduced to just 90,000 documents requiring human review. Automating coding propagation to families, this resulted in a national database of 150,000 documents. This database meant that counsel could instantaneously produce a tranche of documents, buying them more time to review documents unique to each jurisdiction and for strategic case assessment.

An employee complaint about potential improper expenses on a healthcare company’s financial statements triggered in internal investigation. The company turned to Lighthouse to quickly identify documents needed for counsel to decide next steps. Day 1, 67K relevant docs handed to Lighthouse. Day 10, 150 unique key documents delivered to client. Counsel had the time and documents needed to determine next steps due to the speed and curation of the Lighthouse key document identification process.

The ChallengeA healthcare technology company faced over 7.4M documents following collection, processing and deduplication in a civil litigation. Lighthouse used AI to remove relevance review, reduce privilege review to a fraction of the responsive set, and perform privilege logging and key document identification with minimal linear coding. The Solution The client and counsel opted to use a document review workflow powered by AI to optimize both efficacy and efficiency. ROI Overall, using Lighthouse AI saved $13M. AI-Powered TAR Counsel reviewed less than 5K documents to stabilize, measure, and validate a model that measured 83% precision at 75% recall. This TAR workflow removed 5M documents from review, delivering an ROI of $11M on 1L contract attorney and outside counsel review and QC. Non-TAR: 93% Review Reduction Junk file analysis identified that 1.2M documents out of the 1.3M non-TAR eligible documents were highly likely to be junk and could undergo a sampling workflow instead of a full linear review. AI-Powered Privilege Review: 40% Review Reduction Lighthouse used an AI classifier for privilege for culling and review acceleration. Based on AI results and sampling, counsel determined that 88K documents could be removed without individual review. Once the privileged documents were identified, Lighthouse used AI to generate first-pass privilege descriptions for the 43K documents in the privilege log. This fully removed 1L human drafting of log lines and instead enabled a quick creation of the log for internal and outside counsel QC.

Solution Lighthouse has long used AI to support data breach matters. With the emergence of more sophisticated LLMs, we can more finely tune our approaches to each client’s data. For this matter, we built an AI workflow calibrated to analyze scanned documents while maintaining PII linkage. Mid-way through review, it became necessary to add business-level information about the types of accounts that created some of the PII. The teams deployed AI with prompts already calibrated to the document set, enabling rapid analysis without delaying the timeline. Conventional methods would have required document re-review, resulting in significant schedule setbacks. Conclusion The implementation of a generative AI solution by Lighthouse proved to be a highly effective solution for the financial intuition’s data breach response. Using AI, 30 PII components were efficiently identified and extracted from a dataset of 300K documents and link them to individuals and account details. Lighthouse’s generative AI expertise and custom workflows ensured the accuracy and integrity of the data being extracted. Overall, the project demonstrated the power of Lighthouse AI in expediting the review process in a complex data breach, leading to a total savings of $550K. Novel AI Image Analysis Speeds Data Breach Response While the organization of data breach responses can be similar, every company’s data contains unique PII, making it an arduous process, even when using technology. Lighthouse partnered with outside counsel to create and deploy a novel approach using GenAI to alleviate the burden of PII extraction and linking while maintaining the rigor that a breach response requires. Challenge When a financial institution suffered a data breach, outside counsel was faced with 300K documents—many scanned—to review and support the response. OCR is a common way to include images into document review, but can lose key information and formatting, including removal of the link between a piece of data and its data owner(s). Further, in addition to standard pieces of PII that needed to be extracted, there were client-specific nuances we needed to capture and address.