Taming Modern Data Challenges: Legal Data Intelligence

In our last post, we discussed how the importance of information governance (IG) has evolved in eDiscovery, why IG is an important component in taming modern data today, the role that technology plays in effective IG and best practices for building an IG program that supports your eDiscovery initiatives.

While we have discussed various forms of modern data and the criticality of information governance in managing those modern data forms effectively, it’s also necessary to consider emerging industry initiatives that are impacting how that data is managed. In our last post in the series, we will discuss one such initiative: Legal Data Intelligence.

What is Legal Data Intelligence?

Legal Data Intelligence (LDI) was born out of recognition that legal teams today are drowning in data. The About page on the LDI site describes LDI as an initiative that “empowers the legal industry with a vocabulary, framework, and best practices to manage legal data,” helping legal professionals turn data from obstacle to opportunity. LDI emphasizes that most legal data is “ROT” (redundant, obsolete, and trivial), while the goal is to identify the “SUN” data that is sensitive, useful, and necessary. Founded by industry leaders from major in-house legal teams, law firms, and service providers, the initiative brings together domain expertise to reshape how legal data is understood and governed.

LDI was formally launched in May 2024 at the CLOC Global Institute, marking the start of a coordinated, community-based effort to modernize legal data practice. From day one, its ambition has been to transcend siloed data or tool approaches and to create a shared model across disciplines (i.e., law, operations, analytics, technology) that can be applied in real legal settings. Additionally, LDI’s Resources section offers articles, white papers, podcasts, and toolkits to help practitioners deepen their knowledge.

The LDI Model Framework

The LDI model framework provides a step-by-step discussion of how to manage legal data challenges and use technology across a range of legal use cases, from litigation & dispute resolution and regulatory requests to DSARs and data breach responses. As of this writing, LDI has 17 use cases to which it applies its model framework. The use cases that LDI supports include these eDiscovery-related use cases:

• Litigation & Dispute Resolution: structuring data workflows in lawsuits or arbitration.
• Regulatory Requests: responding to government or agency inquiries efficiently.
• Third-Party Subpoenas: handling external demands for data with consistent processes.
• Internal Investigations: triaging data internally for misconduct, compliance, or risk.
• Mergers, Acquisitions & Divestitures: due diligence on contracts, obligations, regulatory filings, and unstructured data.
• Data Subject Access Requests (DSARs) & Data Breach Response: coordinating requests from individuals or breach investigations across systems.

How the LDI Model Framework Works

The LDI framework was designed to bring order to this chaos by defining clear phases — initiate, investigate, and implement — that help teams manage legal data consistently, defensibly, and efficiently.

Using the litigation & dispute resolution use case as our example, here’s how the framework works and where technology makes a difference.

Phase 1: Initiate – Defining the Matter and Building the Plan

When a dispute emerges or a lawsuit is filed, the “initiate” phase sets the foundation.

Key steps:

• Define scope, objectives, claims, and defenses.
• Identify stakeholders: corporate counsel, IT, compliance, outside counsel, service providers.
• Locate data sources — email, collaboration platforms, cloud repositories, mobile devices, legacy archives.
• Assess risk and cost factors such as privilege, privacy, proportionality.
• Establish governance: decision-makers, escalation paths, and metrics.

Technology’s role:

• Data mapping & connectors surface repositories quickly.
• Metadata analytics (age, volume, duplication) help prioritize.
• Workflow tools streamline legal holds and custodian outreach.
• Early-case assessment dashboards give quick insight into scope and cost.

Takeaway: Early sampling of data validates assumptions and strengthens defensibility.

Phase 2: Investigate – Turning Data into Evidence-Ready Insight

Once the plan is set, the “investigate” phase digs into the data to surface facts that matter most for litigation strategy and discovery obligations.

Key steps:

• Collect and process data, preserving chain of custody.
• Deduplicate, index, and filter to focus on what’s responsive.
• Use analytics to reveal patterns — timelines, entities, key custodians.
• Validate results with sampling and quality control.

Technology’s role:

• Automated processing & deduplication cut volume and ensure scalability.
• Email threading & clustering streamline review and add context.
• Advanced analytics & visualization spotlight hot documents and communication networks.
• AI-driven prioritization (TAR 2.0 / CAL) accelerates review.
• QC dashboards document accuracy and defensibility.

Takeaway: “Investigate” is iterative — findings often refine scope or add custodians — so audit trails and privacy controls are critical.

Phase 3: Implement – Acting on Findings and Delivering Results

The “implement” phase turns insight into action: productions, disclosures, negotiations, or trial prep.

Key steps:

• Produce documents in the required formats (Bates-stamped PDFs, load files, natives).
• Apply redactions and privilege checks at scale.
• Execute litigation strategy while tracking progress and quality.
• Capture lessons learned for future matters.

Technology’s role:

• Production & redaction tools improve speed and accuracy.
• Privilege-screening AI reduces risk of inadvertent disclosure.
• Case-management workflows centralize deadlines and approvals.
• Audit logs & reports provide transparency for courts and opposing counsel.
• Retention & remediation tools handle data disposition post-matter.

Takeaway: Timely, defensible execution requires strong governance and collaboration between internal and external teams.

Applying LDI’s initiate – investigate – implement structure to litigation & dispute resolution makes complex matters more predictable and defensible. It aligns technology with each phase: initiate (mapping and legal holds), investigate (analytics), and implement (production workflows. This reduces cost, risk, and time-to-insight when stakes are highest.

Conclusion

Data within organizations is always evolving, which means that there will always be modern data challenges that need to be “tamed”. Whether it’s mobile device data, enterprise solutions and collaboration apps, linked documents, structured data, emojis, generative AI created content or new data sources yet to become discoverable, the ability to apply best practices and leverage technology to keep these data sources from being “wild” could determine the success of your discovery project. Disciplines like information governance and initiatives such as the Legal Data Intelligence framework will continue to grow in importance as vital tools to help keep your modern data “tamed”.

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