At ILTACON this year, I conducted an interview with Chuck Kellner, Senior Strategic Discovery Advisor at Everlaw to discuss the Legal Data Intelligence (LDI) initiative, its objectives, key developments, and most important ideas. Here are the highlights of that interview.

I. Introduction to LDI and Chuck Kellner’s Involvement

Chuck Kellner, a Senior Strategic Discovery Advisor at Everlaw, is actively involved with LDI due to both personal and professional motivations. With a career spanning “eDiscovery consultant on the front lines,” working at “a big law firm,” and serving as “an expert witness and a forensics investigator,” Kellner was drawn to LDI by the “leadership that I saw represented on that group of founding members,” many of whom he has collaborated with on other esteemed legal think tanks like Sedona and EDRM.

II. The Fundamental Importance of Data in Legal Operations

Kellner highlighted a critical, often overlooked aspect of legal technology: the indispensable role of data. He emphasizes that “without the data the right data to feed the technology you don’t have the technology.” This underscores LDI’s core premise: that data intelligence is foundational to leveraging advanced legal technologies, including AI.

Historically, dispute resolution was “driven completely by the lawyering and the legal teams,” focusing on “find the data, get the work out, win the case, close the investigation.” However, a new paradigm has emerged, coinciding with the rise of “legal operations as a discipline.” This shift emphasizes “counting things” – metrics and data analysis – not just for resolving current disputes but also for:

• Preventing future incidents: “how to prevent it from happening again.”
• Cost-benefit analysis: “what’s the cost/benefit ratio of certain kinds of approaches.”

Kellner’s role on the “value engineering team at Everlaw” aligns perfectly with LDI’s focus on identifying “what are the metrics that matter to people who are managing and resolving disputes.”

III. LDI’s Unique Approach and Key Developments

LDI stands out from other legal thinktanks due to its rapid output and focus on actionable advice. Unlike organizations where “work product that actually gets issued” can “taken years to develop,” LDI “measur[es] our output by weeks” and produces “practical, actionable advice” on a “fairly frequent basis,” often “pretty much every month.” This includes “actionable white papers” that are not extensive tomes like “a 275 page principles of eDiscovery.”

Kellner is a member of the Disputes & Investigations LDI Architect team, led by Jeremiah Weasenforth and Kelly Friedman. This cross-disciplinary team comprises professionals from “law firms, corporate law departments, service providers,” who pool their collective experience to:

• Understand dispute response from the “client standpoint.”
• Analyze “lawyering and the negotiating.”
• Incorporate “metrics and the analytical tools” from technology and service providers.

This collaborative approach aims to develop strategies that, while conceptually similar to the “EDRM left to right approach,” incorporate “different features than it did 5 or 10 or 20 years ago.” Critically, these features go beyond “new technology” to include “data points that we understand now are important not just for the resolution of the dispute, but for preventing disputes in the future.”

IV. Practical Use Cases and Future Directions

LDI’s cornerstone is its identification and application of principles to practical use cases.

A. Government Investigations (Recently Released Paper)

LDI has recently released a paper on The Application of Legal Data Intelligence to Government Investigations, co-authored by Kellner, Kevin Clark, Melina Efstathiou, Kelly Friedman, and Daniel Miller. This paper addresses the unique aspects of government investigations, which differ from typical litigation in several ways:

• No guaranteed settlement: Parties “don’t necessarily have a choice to just be able to settle for example on a dollar amount.”
• Incremental development: Investigations often “develops incrementally” with a “question and then an answer and then it’s either over or it’s not.”
• Dynamic scope: Unlike civil litigation focused on a claim or defense, a government investigation “can go anywhere and it can become broader or narrow.” This necessitates flexibility in “negotiation that goes all the way back to the production to the preservation and the early data assessment phase.”

The paper outlines a workflow that, while resembling the EDRM, emphasizes:

• Modern Early Data Assessment (EDA): EDA is no longer just about “minimize potentially non-responsive data,” but is now a powerful tool “to help model storytelling even before you spend a lot of time and money.”
• Diverse Data Sources: The need to normalize and chronologize “structured data, mobile data devices, short messaging from all different platforms” to answer the key investigative question: “who knew what?”
• Advanced Tools for Storytelling: Utilizing “advanced tools… for storytelling” and “negotiation.”

B. Preventive Risk Analysis (Upcoming Effort)

Building on the government investigations paper, LDI’s next major effort will focus on preventive risk analysis. This involves using “the data that we develop and that we collect in managing an investigation” for “preventive risk maintenance.” Key aspects include:

• Feedback Mechanism: Employing a feedback loop, which was previously unavailable due to lack of tools, to “feed it back into the business.”
• Identifying Language and Conduct: Analyzing “the language of the dispute” and “the conduct” that led to an investigation.
• Proactive Compliance: Using analytical tools to “identify that conduct before it becomes, for example, a compliance matter.”
• Business Environment Analysis: Identifying “a business environment that precedes the evolution of a compliance matter or an investigation” or “a behavior pattern that we’re able to identify” to prevent future incidents.

C. Integration of Advanced Tools and Generative AI

LDI is actively exploring “how to use advanced tools,” including “generative AI based discovery tools,” for dispute and investigation management. This involves:

• Early Storytelling through EDA: Shifting the traditional storytelling process, usually occurring late in discovery, to the early data assessment phase. By taking “key features of your metrics, key features of your document collections,” and “model[ing] the storytelling around that,” attorneys can “interrogate the same collection of data in different ways to yield different stories and interpretations” using large language models.
• Improved Negotiation and Resolution: These tools are expected to “help attorneys negotiate scope” and “help their clients get to the end of investigations earlier.”
• Upstream Application: Moving these tools “more upstream into the compliance environment” for predictive risk analysis, rather than solely focusing on “traditional downstream litigation management.”

D. The Business of Law

LDI also encompasses a crucial “whole part… called the business of law.” This sub-committee, comprised of “litigators and legal operations people,” focuses on:

• Delivering Legal Services: Examining “how do we deliver legal services.”
• Managing Fees and Costs: Addressing “how do we manage things like fees and costs.”
• Business Drivers of Law Departments: Understanding the “business drivers associated with… managing a law department.”
• Metrics for Value: Shifting the perception of law departments from “a cost center” to demonstrating “the value of the law department” through metrics like “time to resolution of the dispute.” Kellner notes that “the sooner you can resolve a dispute the statistics show that the parties are happier and that the dollar amounts are smaller.” This is achieved by “get[ting] to first insight on what the facts are much earlier using some of these advanced tools.”

V. Conclusion

LDI represents a significant and rapidly evolving initiative dedicated to advancing legal data intelligence. By focusing on practical, actionable advice, leveraging cross-disciplinary expertise, and integrating advanced tools like generative AI, LDI aims to transform how legal professionals manage disputes, conduct investigations, prevent future risks, and ultimately, demonstrate the strategic value of legal departments.

So, what do you think? What has the impact of LDI so far been on the legal community? Please share any comments you might have or if you’d like to know more about a particular topic.

Note: This write-up from a recorded interview was prepared with the assistance of NotebookLM from Google and reviewed and edited by both Chuck and me for accuracy.

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by my employer, my partners or my clients. eDiscovery Today is made available solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Today should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.