🎙️ TSL.P Ep. #135: Ethical AI, Paperless Practice, and Smart Hardware Choices with ABA LTRC Chair Alan Klevan ⚖️🤖

/ The Tech-Savvy Lawyer.Page/

My next guest is Alan Klevan, a veteran personal injury lawyer and Chair of the ABA Law Practice Division’s Legal Technology Resource Center (LTRC), known for running one of the first paperless practices in New England and for his clear-eyed approach to AI in law. In this live episode recorded at the ABA Spring Conference in San Diego, Alan and I dig into how solos and small firms can use AI, case management platforms, hardware, and workflows to practice more efficiently while honoring their ethical duties and protecting client confidentiality.

Join Alan Klevan and me as we discuss the following three questions and more!

  • What are the top three ways Alan uses AI and other tech tools to control discovery and document management at scale, protect client confidentiality, and communicate complex case progress to clients who only care that it is accurate and on time?

  • As Chair of the ABA Law Practice Division’s Legal Technology Resource Center, what top three technology practices does Alan wish every small or solo lawyer would adopt in the next 12 months?

  • What were the three most important technology decisions Alan made early in his career around paperless workflows, practice management, automation, and AI‑powered research—and how can today’s practitioners follow that lead?

In our conversation, we covered the following:

  • [00:00:00] Live from the ABA Spring Conference in San Diego, introducing Alan Klevan and the setting of the conversation 🌴

  • [00:00:30] Alan’s mirrored bi‑state setup: two Lenovo i7 laptops in Massachusetts and Florida, dual 24" HP HD monitors, two ScanSnap iX1600 scanners, laser printers, and Microsoft OneDrive syncing between offices 💻📠

  • [00:01:10] Traveling with a third “road warrior” Lenovo laptop, iPhone as primary smart device, and using the reMarkable 2 tablet for handwritten notes that sync into client and ABA files ✍️

  • [00:01:45] Early impressions of the Plaud (AI wearable) device, background-noise muting, and why Alan limits it to non‑critical meetings due to privilege concerns 🎧

  • [00:02:20] Judicial skepticism about AI recording tools in court; motion practice, privilege issues, and a New York judge flatly banning AI recorders in the courtroom 🚫

  • [00:03:10] AI hallucinations in legal practice, roughly 1,300 known hallucination incidents, and why the real problem is lawyers not checking citations—highlighted by a recent Oregon sanctions case 💸

  • [00:04:00] The Oregon lawyer who tried to “fix” hallucinated citations with a motion to refile instead of candor to the court and opposing counsel, and how that became a fraud‑on‑the‑court issue under the Oregon Rules of Professional Responsibility

  • [00:04:45] Using Google Scholar as an AI‑prompting “hack” to verify every citation and case suggested by AI tools 🔍

  • [00:05:20] Question 1 restated: top three ways Alan uses AI and tech to (1) control discovery, (2) protect confidentiality and ethical duties, and (3) communicate complex case progress to clients

  • [00:05:45] Drafting AI and social media policies directly into contingency‑fee agreements so clients do not post about their case or use open‑source AI on case‑related issues 📜

  • [00:06:30] Hepner and Warner: open‑source vs enterprise AI, attorney–client privilege, work product concerns, and emerging discoverability questions for public‑facing AI platforms

  • [00:07:20] Trap for the unwary: why Alan insists clients notify him before using AI on their case and why he prefers enterprise versions of AI for better protection and governance 🧠

  • [00:08:10] The Nippon Life Insurance case: client uploads attorney communications into ChatGPT, asks if her lawyer is gaslighting her, then files 44 AI‑drafted motions—raising product liability and disclaimer questions for AI vendors 🏛️

  • [00:09:30] Court pushback on AI disclaimer language, defective product theories, and the infancy of AI‑related legal liability

  • [00:10:10] Alan’s big personal‑injury “Aaron Brockovich‑type” case with a deep‑pocket defendant and using AI to level the playing field on litigation management and motion practice ⚖️

  • [00:11:00] Feeding facts, parties, defense counsel names, and pleadings into a case management system with a built‑in, highly accurate legal AI component (VL) and generating 50‑state case research for negligent infliction of emotional distress claims 📂

  • [00:12:00] Running the same matter through two AI platforms (case management AI and Claude) to compare outputs, reduce hallucination risk, and mold responses to Alan’s writing style and Massachusetts practice

  • [00:13:00] Using Claude (enterprise tier) to draft an opposition to a motion to dismiss seven emotional‑distress claims, followed by manual review and cross‑checking in the case management AI—leading to the defendant’s motion being denied ✅

  • [00:14:15] Alan’s process for verifying AI outputs: second set of “AI eyes,” Google Scholar citation checks, and lawyer‑level review of every filing

  • [00:15:00] Advice for new attorneys: try AI platforms before buying, choose a tool that fits your workflow, avoid shiny‑object syndrome, and do not over‑commit to annual plans while the market is moving fast 🧩

  • [00:16:00] Michael’s caution about yearly plans, vendor lock‑in, and ensuring your data is nimble enough to move between AI platforms without costly migrations

  • [00:16:45] Alan’s rule: do not chase every AI; become a master of one platform, learn it deeply, and resist the temptation to constantly switch 🧠

  • [00:17:10] Both hosts stress “review, review, review”—AI as a law librarian or 3L intern, not as your practicing lawyer, and the concept that AI does not have a JD 🎓

  • [00:18:00] Anecdote from 1990: Alan is sent to court unprepared, gets sent out of the courtroom to learn his file, and how that story frames his modern view of AI oversight and responsibility

  • [00:19:10] Question 2: as LTRC Chair, Alan’s top three technology practices every small or solo lawyer should adopt in the next 12 months

  • [00:19:30] Tech Practice #1: invest in a fast machine (Windows or Mac) with as much RAM and storage as you can reasonably afford, and strip the “crapware” off box‑store Windows machines 🖥️

  • [00:20:10] Discussion of Apple vs Windows pricing, the need for more than 16 GB of RAM, multi‑core processors, and why Alan buys Lenovo laptops with 32 GB RAM and expects 3–4 year laptop lifespans 💾

  • [00:21:30] Backups and storage: redundant cloud backups, redundant hard drives, using external 5 TB drives from Staples, and keeping active machines “clean” for better AI performance

  • [00:22:30] Tech Practice #2: immerse yourself in what is happening with AI and law practice, become a master of one AI platform, and continuously read ethics and disciplinary decisions about AI use 📚

  • [00:23:15] Tech Practice #3: your head is your most important piece of technology—using judgment, stepping back to assess risks, and making sure anything submitted to court or client is accurate

  • [00:24:00] Economic access, hardware costs, and why Alan still believes lower‑resource attorneys can get workable hardware by being strategic about purchases, specs, and lifecycles

  • [00:25:10] Michael’s storage philosophy: lots of local SSD, multiple backups, and revisiting older briefs and arguments (e.g., mailbox‑rule analysis) to build new work more efficiently

  • [00:26:10] Disk space versus backup strategy, internal vs external drives, cloud vs local files, and disaster recovery considerations

  • [00:27:20] Question 3: top three early technology decisions Alan made around paperless practice, automation, and AI‑powered research

  • [00:27:40] Answer #1: going fully paperless in 2005—the first paperless practice in New England—and eliminating almost all postage costs by sending encrypted electronic communications and demand packages ✉️

  • [00:28:15] Answer #2: becoming a power‑user of Adobe Acrobat and PDF workflows so he can respond to massive production requests (e.g., 10,000 pages) in seconds instead of hours 📑

  • [00:29:00] Answer #3: adopting case management platforms with AI‑driven workflows that automatically assemble record requests, HIPAA authorizations, and certifications for medical providers

  • [00:29:45] Dusty hardware: why Alan’s printer and ScanSnap are seeing less use, yet scanners remain necessary for partners who still prefer paper and non‑electronic delivery 🖨️

  • [00:30:20] Michael’s own shrinking paper consumption, stamps.com, and transitioning to PDF‑based workflows with secure electronic delivery

  • [00:31:00] Adobe Acrobat as “gold standard” for lawyers, why every attorney must understand PDFs deeply, and Alan’s “learn it, love it, live it” mantra 📄

  • [00:31:40] Bonus segment: what the ABA Legal Technology Resource Center (LTRC) is, its role as a “delivery board,” and how it serves both the Law Practice Division and the broader ABA membership 🏛️

  • [00:32:20] LTRC’s four pillars of law practice management—marketing, technology, practice, and finance—and how it delivers content via Law Technology Today, webinars, podcasts, and roundtables

  • [00:33:10] 2024–25 LTRC theme: AI‑centric content from intake through trial, and why Alan believes LTRC may become the ABA’s most important board for practitioners navigating AI

  • [00:34:00] Using AI for law‑firm marketing, content creation, case‑law recaps, and SEO—along with warnings about legal advice, PII, and AI‑generated “SEO articles” that sound inauthentic

  • [00:35:00] Call to action: join the ABA Law Practice Division and LTRC, become one of roughly 30 tech‑focused thought leaders, and help shape AI guidance for the profession 🙌

  • [00:36:00] Where to find Alan: why he is minimizing social presence during a major move and high‑stakes case, and the best way to reach him on LinkedIn

Hardware mentioned in the conversation

Software & cloud services mentioned

TSL LABS BONUS: Dynamic Random-Access Memory (DRAM): Why It Matters for Law Firm Performance and Data Security ⚖️💻

/ The Tech-Savvy Lawyer.Page/

Join us for an AI-powered deep dive into the ethical challenges facing legal professionals in the age of generative AI. 🤖 In this episode, we break down our April 20, 2026, Tech‑Savvy Lawyer editorial on how a global DRAM shortage and AI data center demand are driving up PC prices, pushing many legal professionals toward Apple hardware, and redefining what technological competence really means. We explore how unified memory, on‑device AI, and long‑term support lifecycles are changing the Mac vs. Windows calculus, and why “cheap but weak” laptops may now create serious competence and confidentiality risks for your clients.

In our conversation, we cover the following:

  • 00:00 – Why upgrading your work laptop in 2026 feels like buying a luxury vehicle, not a routine office expense.

  • 00:45 – Setting the stage: a “seismic shift” in hardware pricing hitting professional industries, with a focus on the legal field.01:30 – Introducing Michael D.J. Eisenberg’s Tech‑Savvy Lawyer editorial and its core thesis about a tech hardware crisis.

  • 02:15 – The global DRAM crunch: how AI data centers are buying up memory like airlines hoard jet fuel, and why PC OEMs are getting squeezed.

  • 03:30 – Microsoft’s April 2026 Surface price hikes and the end of the “Windows is cheaper” assumption for law firms.

  • 05:15 – The “value inversion”: when high‑end Windows laptops now cost more than roughly comparable MacBooks.

  • 06:30 – Why this isn’t a normal tech price cycle and how it breaks 20 years of corporate IT purchasing assumptions.

  • 07:15 – Apple’s structural advantage: vertical integration, unified memory, and shielding itself from spot‑market DRAM volatility.

  • 08:30 – The M‑series (M5) advantage: performance per watt, thermal behavior, battery life, and running local AI plus heavy legal workloads.

  • 09:45 – Yes, Apple prices are rising too—why the relative “security‑to‑cost” and performance story still favors Macs for many professionals.

  • 10:45 – When “cheap but weak” hardware crosses the line: connecting underpowered laptops to ABA Model Rule 1.1 (competence) and Comment 8 on tech competence.

  • 12:00 – From annoyance to ethical exposure: how sluggish systems cripple eDiscovery, AI‑driven research, and document automation.

  • 13:00 – Why laptop purchasing is now core client‑service strategy, not just a back‑office procurement task.

  • 13:45 – On‑device vs. cloud AI: where computation happens, why that matters, and how it ties into ABA Model Rule 1.6 (confidentiality).

  • 14:30 – The role of Apple’s Neural Engine and local processing in reducing reliance on external AI APIs and third‑party servers.

  • 15:30 – Clarifying the security nuance: Windows is not inherently less secure, but comparable on‑device AI capability often costs more.

  • 16:30 – Redefining security in 2026: it’s not just antivirus and passwords; it’s where the AI thinking physically happens.

  • 17:15 – Building a documented purchase matrix: price, performance, storage, memory, security, lifecycle, and critical software compatibility.

  • 18:15 – When you can’t leave Windows: legacy legal software, state e‑filing systems, and the hidden costs of moving to macOS.

  • 19:00 – Survival strategies for Windows‑locked practices: non‑Surface OEMs, staggered refresh cycles, and buying fewer but higher‑quality machines.

  • 19:45 – Treating laptops as long‑term infrastructure instead of disposable commodities.

  • 20:15 – Big‑picture recap: DRAM shortages, unified memory, ethical duties, and shifting hardware norms in law practice.

  • 20:45 – The closing question: will AI‑driven hardware requirements quietly raise the price of access to justice?

RESOURCES

Mentioned in the episode

Hardware mentioned in the conversation

Software & Cloud Services mentioned in the conversation

If you want your next laptop purchase to strengthen—not weaken—your ethical obligations, client security, and AI‑powered workflows, hit play now and learn how to build a smarter, future‑proof hardware strategy. 🎧💡

🎙️ Ep. #131, Supercharging Litigation With AI: How StrongSuit Helps Lawyers Transform Research, Doc Review, and Drafting 💼⚖️

/ The Tech-Savvy Lawyer.Page/

My next guest is Justin McCallan, founder of StrongSuit, an AI-powered litigation platform built to transform how litigators handle legal research, document review, and drafting while keeping lawyers firmly in control. In this episode, Justin and I dig into practical, real-world workflows that solos, small firms, and big-firm litigators can use today and over the next few years to change the economics, pace, and strategy of litigation—without sacrificing accuracy, ethics, or the quality of advocacy.

Join Justin and me as we discuss the following three questions and more!

  1. What are the top three ways litigators should be using AI tools like StrongSuit right now to change the economics and pace of litigation without sacrificing accuracy, ethics, or quality of advocacy?

  2. What are the top three mistakes lawyers make when adopting AI for litigation, and what practical workflows help lawyers stay in the loop and use AI as a force multiplier instead of a risk? 

  3. Looking ahead to 2026 and beyond, what are the top three AI-driven workflows every litigator should master to stay competitive, and how can platforms like StrongSuit help build those capabilities into day-to-day practice? 

In our conversation, we cover the following

  • 00:00 – Welcome and guest introduction

    • Justin joins the show and shares his current tech setup at his desk. 

  • 00:00–01:00 – Justin’s current tech stack

    • Lenovo laptop, ultra-wide monitor, and regular use of StrongSuit, ChatGPT, and Gemini for different AI tasks.

    • Everyday tools: Microsoft Word and Power BI for analytics and fast decision-making.

  • 01:00–02:00 – Android vs. iPhone for AI use

    • Why Justin has been on Android for 17 years and how UI/UX familiarity often drives device choice more than AI capability.

  • 02:00–05:30 – Q1: Top three ways litigators should be using AI right now

    • Using AI for end-to-end legal research across 11 million precedential U.S. cases to build litigation outlines and identify key authorities.

    • Scaling document review so AI surfaces relevant documents and synthesizes insights while lawyers focus on strategy and judgment.

    • Leveraging AI for drafting and editing—improving style, clarity, and consistency beyond traditional spelling and grammar checks.

  • 05:30–07:30 – StrongSuit vs. basic tools like Word grammar check

    • How StrongSuit aims to “up-level” a lawyer’s writing, not just catch typos.

    • Stylistic improvements, clarity enhancements, and catching subtle inconsistencies in legal documents.

  • 06:00–08:00 – AI context limits and scaling doc review

    • Constraints of large models’ context windows (around ~1M tokens ≈ ~750 pages).

    • How StrongSuit runs multiple AI agents in parallel, each handling small page sets with heuristics to maintain cohesion and share insights.

  • 08:00–09:00 – Handling tens of thousands of documents

    • How StrongSuit can handle between roughly 10,000–50,000 pages at a time, with the ability to scale further for enterprise matters.

  • 09:00–11:30 – Origin story of StrongSuit

    • Why Justin saw a once-in-a-generation opportunity when large language models emerged and how law, with its precedent and text-heavy nature, is especially suited to AI.

    • StrongSuit’s focus on litigators: supporting lawyers from intake through trial while keeping them in the loop at every step.

  • 11:30–13:30 – From intake to brief drafting in minutes

    • Generating full litigation outlines, research, and analysis in about ten minutes, then moving directly into drafting memos, briefs, complaints, and motions.

    • StrongSuit’s long-term goal: automating 50–99% of major litigation workflows by the end of 2026 while preserving lawyer control and judgment.

  • 12:00–14:30 – How StrongSuit tackles hallucinations

    • Building a full database of all precedential U.S. cases enriched with metadata: parties, summaries, holdings, and more.

    • Validating citations by checking whether the Bluebook citation actually exists in StrongSuit’s case database before surfacing it to the user.

    • Why lawyers should still review cases on-platform before filing, even when AI has filtered out hallucinations.

  • 14:30–16:30 – Coverage and jurisdictions

    • Coverage of all U.S. jurisdictions, federal and state, focused on precedential cases.

    • Handling most regulations from administrative agencies, and limits around local ordinances.

    • Uploading your own case files and using complaints and prior research as inputs into StrongSuit workflows.

  • 15:00–17:00 – Security and confidentiality for litigators

    • SOC 2 compliance and industry-standard encryption at rest and in transit.

    • No model training on user data.

    • Optional end-to-end encryption that can even prevent developers from accessing case content, using local encryption keys.

  • 16:30–20:30 – Q2: Top mistakes lawyers make when adopting AI for litigation

    • Mistake #1: Talking about AI instead of diving in with structured experiments and sanitized documents.

    • Using a framework to identify high-impact tasks: high volume, repetitive work, and heavy data/analysis (e.g., doc review, research, contract drafting).

    • How to shortlist tools: look for SOC 2, real product depth, awards, and a focus on your specific workflows.

    • Mistake #2: Expecting immediate mastery instead of moving through predictable adoption stages—from learning the tool, to daily use, to stringing workflows together.

  • 20:30–22:30 – Building firm-wide AI workflows over time

    • Moving from isolated experiments to integrated, low-friction workflows, such as automatic intake-to-research pipelines.

    • Using client intake audio or transcripts to automatically extract facts, issues, and research paths.

  • 22:30–24:30 – Time constraints and “no-time” lawyers

    • Why lawyers don’t need to be “technical” to use StrongSuit.

    • Reframing AI as text-based tools where lawyers’ writing skills and analytical thinking are assets, not obstacles. 

  • 24:00–26:00 – Practical workflows beyond intake

    • Using AI to prepare for expert depositions, including reviewing valuation analyses, flagging departures from market consensus, and generating targeted questions.

    • Reinforcing the value of AI-enhanced legal research and drafting as core litigation workflows.

  • 26:00–29:30 – Q3: 2026 and beyond – AI-driven workflows every litigator should master

    • Rapid improvement of baseline models (e.g., jumping from single-digit to high double-digit performance on difficult benchmarks year over year). 

    • The idea of “tipping points,” where small performance gains turn AI from marginally useful to essential in specific tasks.

    • Why legal research is a great training ground for understanding where AI excels, where it falls short, and how to divide labor between human and machine.

    • The value of learning basic prompting skills to get more from AI systems, even when platforms offer visual workflows.

  • 29:30–32:30 – Will workflows actually change—or just get better?

    • Why Justin expects familiar litigation workflows (doc review, research, drafting) to remain structurally similar, but become far faster and more sophisticated.

    • AI agents handling the grind work while lawyers focus on synthesis, judgment, and strategy.

    • A future where “AI + lawyer vs. AI + lawyer” resembles high-level chess: same rules, but much deeper thinking on both sides.

  • 32:30–End – Where to find Justin and StrongSuit

    • How to connect with Justin and learn more about StrongSuit’s litigation tools.

Resources

Connect with Justin

Hardware mentioned in the conversation

Software & Cloud Services mentioned in the conversation

ILTACON 2025: Legal AI Revolution Accelerates as Major Providers Unveil Next-Generation Platforms

/ The Tech-Savvy Lawyer.Page/

Lexis, vlex, westlaw highlight their newest ai functions!

The International Legal Technology Association’s 2025 annual conference (#ILTACON2025) in the National Harbor just outside of Washington, DC, became the epicenter of legal AI innovation as Thomson Reuters, LexisNexis, and vLex/Fastcase showcased their most advanced artificial intelligence platforms. Each provider demonstrated distinct approaches to solving the legal profession's technology challenges, with announcements that signal a fundamental shift from experimental AI tools to enterprise-ready systems capable of autonomous legal workflows.

Thomson Reuters Launches CoCounsel Legal with Groundbreaking Deep Research

Thomson Reuters made headlines with the launch of CoCounsel Legal, featuring what the company positions as industry-leading Agentic AI capabilities. This launch represents a fundamental evolution from AI assistants that respond to prompts toward intelligent systems that can plan, reason, and execute complex multi-step workflows autonomously.

The platform's flagship innovation is Deep Research, an AI feature that conducts comprehensive legal research by leveraging Westlaw Advantage’s proprietary research tools and expert legal content. According to Thomson Reuters, CoCounsel Legal combines advanced generative models with the exclusive resources of Westlaw and Practical Law, aiming to deliver trusted, up-to-date, and relevant legal analysis for practitioners. The company emphasizes that its Agentic AI operates directly within Westlaw, making use of the platform’s curated research toolset and authoritative content to enhance accuracy and reliability in legal workflows.

Thomson Reuters Launches CoCounsel Legal with Groundbreaking Deep Research

Key capabilities include guided workflows for drafting privacy policies, employee policies, complaints, and discovery requests, with Thomson Reuters planning incremental releases of new workflows. The platform addresses the critical challenge of document management system integration through federated search technology, which leverages existing Document Management System (DMS) search systems while applying AI for re-ranking and summarization.

The company also introduced Westlaw Advantage on August 13, 2025, positioned as the final versioned release of Westlaw, with future improvements delivered through continuous updates rather than new license agreements. This shift to a traditional Software-as-a-Service (aka SaaS) delivery model includes multi-year subscriptions with automatic upgrades at no additional cost.

Thomson Reuters has invested $10 billion in transforming legal technology foundations, with over $200 million annually dedicated specifically to integrating AI into flagship products. The platform already serves over 20,000 law firms and corporate legal departments, including the majority of AmLaw 100 firms.

LexisNexis Introduces Protégé General AI with Industry-First Voice Capabilities

LexisNexis announced on August 11, 2025, the preview launch of Protégé General AI, expanding its personalized AI assistant to include secure access to general-purpose AI models alongside legal-specific tools. This development builds on the company's March 2025 launch of the legal industry's first voice-enabled AI assistant for complex legal work. This voice feature allows users to interact naturally with the platform, guiding legal research and drafting by issuing spoken requests. The tool is designed to help legal practitioners streamline routine workflows, surface key insights, and perform drafting and search tasks hands-free, all within a secure and integrated environment.

LexisNexis Introduces Protégé General AI with Industry-First Voice Capabilities

Protégé's key differentiator lies in its toggle functionality, allowing users to switch between authoritative legal AI (grounded in LexisNexis content) and general-purpose AI models including GPT-5*, GPT-4o, GPT-o3, and Claude Sonnet 4. This eliminates the need to switch between different AI tools while maintaining enterprise-grade security.

The platform processes documents up to 300 pages long (a 250% increase over previous limits) and offers unprecedented personalization capabilities. It learns individual user workflows, preferences, writing styles, and jurisdictions to deliver customized responses. The system integrates with document management systems to ground responses in firm-specific knowledge while maintaining strict security controls.

Approximately 200 law firms, corporate legal departments, and law schools are participating in the customer preview program, with general availability expected later in 2025.

vLex Showcases Vincent AI Spring '25 with Studio Workflow Creation

vLex presented its Vincent AI Spring '25 Release at ILTACON 2025, highlighting enhanced agentic capabilities and the introduction of Studio, a platform allowing users to create custom workflows without coding. The company emphasized its data-centric approach, leveraging its billion-document global legal database spanning over 100 countries.

vLex Showcases Vincent AI Spring '25 with Studio Workflow Creation

vLex’s Spring ’25 release also emphasizes its Vincent Tables feature, which allows users to extract and compare key data points across large sets of documents and generate structured outputs like memos. Their General Assist capability supports drafting tasks—such as composing emails and summarizing meeting notes—within Vincent’s secure, enterprise-grade environment. Overall, vLex positions Vincent AI as a comprehensive workflow platform that delivers consistent, authoritative legal insights powered by a global database of over one billion documents from more than 100 jurisdictions.

During ILTACON, vLex also announced the 2025 Fastcase 50 awards, recognizing legal innovation leaders who are "engineering the future of legal practice". The company positioned itself as serving the "engineering minds and visionary leaders driving the legal profession's transformation".

🔎 Feature Comparison: How the Big Three Actually Stack Up

Market Positioning and Strategic Differentiation

The three providers have established distinct market positions based on their 2025 announcements. Thomson Reuters targets enterprise-level implementations, evidenced by multi-year contracts with the U.S. Federal Courts system, including the U.S. Supreme Court, and a focus on consistent, reliable workflows for large-scale legal operations.

LexisNexis emphasizes user experience and personalization, with Protégé designed to understand individual lawyer preferences and adapt to different work styles. The voice interface represents a significant advancement in accessibility and usability, particularly valuable for lawyers with physical accessibility needs or those who prefer natural language interaction.

vLex positions itself as serving both mid-size firms and AmLaw 100 practices, emphasizing comprehensive workflow solutions and global legal coverage. The Studio platform addresses the growing demand for customizable AI workflows tailored to specific practice requirements.

Final Thoughts: Industry Impact and Measurable Results

ILTACON was a great experience - I learned and hope to share a lot!

These ILTACON 2025 announcements demonstrate the maturation of legal AI from experimental tools to platforms delivering measurable business value. Case studies reveal significant cost savings, with startups like OMNIUX reporting monthly savings of $15,000 to $20,000 in legal fees using CoCounsel.

Independent analysis shows that contract review tasks, which previously required two to two and a half hours, can now be completed in 10 minutes, representing productivity improvements of over 90%. Legal professionals report that document analysis tasks requiring days of manual work can now be completed in under an hour.

The competitive landscape now features three mature approaches: Thomson Reuters' enterprise-focused agentic workflows with deep legal research integration, LexisNexis's personalized voice-enabled AI with comprehensive model flexibility, and vLex's comprehensive workflow platform with global legal intelligence.

As legal professionals evaluate these platforms, selection criteria should include firm size, practice areas, existing technology infrastructure, required customization levels, and specific workflow requirements. The legal profession's digital transformation has clearly accelerated beyond the experimental phase, with AI becoming essential infrastructure for competitive legal practice.

But what does this mean for the solo, small-, and medium-size law forms? Stay Tuned as my analysis on that will be posted soon!

Happy Lawyering!

* (Note, the original launch was supposed to include GPT-5 but it has been pulled pending resolution of issues in its program - see MTC: Why "Newer" AI Models Aren't Always Better: The ChatGPT-5 and Apple Intelligence Reality Check for Legal Professionals! for reference).