legal technology

Subscribe to legal technology via RSS

In this episode of The Geek in Review, Greg Lambert and Marlene Gebauer welcome back ⁠Joel Hron⁠, Chief Technology Officer at ⁠Thomson Reuters⁠, for a timely conversation about the shifting relationship among foundation models, legal content providers, legal tech platforms, and the lawyers trying to make sense of the mess. Recent moves by Anthropic, including Claude’s legal practice area tools and MCP connections into legal platforms, raise a larger question for the market. Is a model provider still sitting behind the scenes, or is it starting to become a legal work environment of its own?

Hron explains Thomson Reuters’ commitment to what it calls ⁠fiduciary-grade AI⁠, a standard built around trust, verification, transparency, and accountability. For TR, legal AI needs more than a fast answer. It needs systems lawyers trust enough to stand behind. Hron points to Westlaw, Practical Law, KeyCite validity signals, citation ledgers, and verification tools as core ingredients in building AI systems suited for high-stakes professional work. In his view, almost right is not good enough when clients, courts, regulators, and professional obligations sit on the other side of the output.

The conversation turns to how CoCounsel and Westlaw Deep Research use legal content across far more than traditional research tasks. Hron explains that when AI systems gain access to trusted legal content and verification tools, they begin researching throughout the workflow, even while revising contract language or analyzing provisions. He also describes Litigation Document Analyzer, internally nicknamed the BS Detector, a tool designed to review claims in a document and map them to supporting authority, weak support, or no support at all. For lawyers who spend as much time verifying AI output as generating it, tools like these aim to move verification from a manual scavenger hunt into a structured process.

Greg and Marlene also press Hron on Anthropic’s legal plugins, MCP, and the idea of headless legal technology. Hron argues that MCP changes access, not advantage. In his view, the application layer is shifting, but the real competitive value sits in trusted content, expert systems, governance, and domain-specific intelligence. CoCounsel’s user interface represents one expression of TR’s legal agent capabilities, while MCP opens other ways for those capabilities to appear inside broader work environments. Some work will still need a purpose-built legal interface; other work might happen through email, Word, Claude, or another agentic workflow with little visible interface at all.

The episode closes with a larger discussion about what happens when AI starts performing more of the work itself. Hron shares TR’s internal engineering OKR, where more than 50 percent of pull requests should be written by AI, and explains why 51 percent serves as a useful mental model. Once AI performs a controlling share of the work, the human role shifts from doing the task to governing the system. For legal professionals, the same transition is coming. The key question is no longer only whether AI produces useful work. It is whether lawyers have built the systems, context, safeguards, and verification layers needed to trust the work, defend the work, and remain accountable for the work.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠

[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com

Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Legal AI, Trust, and Agents: Joel Hron on Thomson Reuters, Anthropic, and the Future of CoCounsel

This week on The Geek in Review, we talk with Lennie Nuara, co-founder of Flatiron Law Group, about what it means to build a talent-first, AI-powered legal practice. Nuara brings a rare mix of lawyer, technologist, operator, and systems thinker to the conversation, drawing from decades of experience using technology to improve legal work, from early portable computers and databases to today’s generative AI tools.

Nuara explains why he resists the phrase “AI-first” in legal practice. For him, legal work begins with talent, judgment, and expertise. AI enters as a force multiplier, not the driver. At Flatiron, the firm’s model was already built around flat fees, lean staffing, process discipline, and structured data before generative AI entered the picture. AI now adds more horsepower to a system already designed to reduce waste, repeat touches, and unclear workflows.

Much of the discussion focuses on M&A due diligence, where Flatiron rethinks the deal life cycle from intake through closing. Instead of throwing documents into a massive repository and hoping AI sorts it out, Nuara describes breaking work into smaller pieces: diligence questions, responses, documents, clauses, topics, closing checklists, and reports. That structure lets lawyers use AI for deduplication, extraction, clause comparison, first-pass drafting, and issue spotting while keeping human judgment between higher-risk steps.

Nuara also warns against getting seduced by polished AI output. He describes generative AI as persuasive, fluent, and sometimes dangerously average. The bigger risk, in his view, is less hallucination and more “model monoculture,” where legal drafting drifts toward sameness because models train from overlapping bodies of public material. In complex private transactions, average language is often the wrong answer. Lawyers still need to understand leverage, client priorities, risk allocation, and where to push beyond market terms.

The episode closes with a look at pricing, training, and the future structure of law firms. Nuara argues that AI will pressure the billable hour, change junior lawyer training, and force firms to rethink the traditional pyramid. He also raises a practical concern from the early Westlaw and Lexis days: the cost of the tool matters. Flatiron tracks AI usage down to the clause level, treating tokens as part of matter economics. For legal professionals watching AI reshape transactions, this conversation offers a grounded reminder: better tools matter, but better process and better judgment still decide the outcome.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Flatiron Law Group’s Lennie Nuara on Talent-First AI, M&A Workflows, and the Future of Legal Practice

This week on The Geek in Review, we talk with Andrew Thompson, CTO of Orbital, about why legal AI built for a specific practice area has a strong claim in a market crowded by general-purpose models. Thompson explains how Orbital focuses on real estate law, using AI, spatial intelligence, and legal workflow design to support transactions involving property portfolios, title review, survey analysis, and complex documentation. With more than 200,000 property transactions processed and a major $60 million, Series B investment fueling its U.S. expansion, Orbital sits at the center of the debate over whether the future of legal AI belongs to broad model platforms or tools built for the messy details of actual legal work.

Thompson’s path into legal technology brings a practical operator’s mindset to the conversation. Before Orbital, he worked across software, fintech, proptech, and real estate marketplaces, where speed, accuracy, and operational friction shaped business outcomes. That background informs his view that successful legal AI starts with the work itself rather than the model alone. For Orbital, the key is teaching AI to think like a real estate lawyer at the right level of abstraction, then pairing the model with domain-specific tools, data, and workflows.

The conversation gets especially interesting when Thompson walks through Orbital’s use of spatial intelligence. Real estate law often turns written legal descriptions, old maps, title documents, surveys, and boundaries into high-stakes decisions about physical land. Thompson explains the challenge of moving from words on a page to points, lines, curves, and property boundaries on a map. This leads to a broader discussion of large language models, visual language models, OCR, and classical machine learning, with Thompson making clear that the best current systems still require a toolbox rather than blind faith in one model.

We also explore Thompson’s concept of the “prompt tax,” the hidden maintenance burden created when model behavior changes faster than product teams expect. Thompson describes Orbital’s mantra of “betting on the model,” which means building for where AI capabilities are heading while still delivering value today. He separates durable domain expertise from brittle prompt tricks, arguing that legal AI companies need reusable legal knowledge, strong evaluation habits, and a willingness to rebuild assumptions as models improve.

Looking ahead, Thompson sees the impact of AI arriving faster than the standard three-to-five-year forecast. He points to software engineering as an early signal for what legal work might experience next, with professionals increasingly orchestrating humans and AI agents together. The billable hour, client value, accountability, empathy, and judgment all come under pressure as AI handles more cognitive labor. For real estate lawyers and legal technologists, Thompson’s message is direct: the winners will be those who understand the work deeply, build with technical humility, and know when the map matters as much as the document.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Orbital CTO Andrew Thompson on Practice Area AI, Real Estate Law, and the Future of Legal Work

Cat Moon and Mark Williams return to The Geek in Review wearing two hats, plus one tiara. The conversation starts at Vanderbilt’s inaugural AI Governance Symposium, where “governance” means wildly different things depending on who shows up. Judges, policy folks, technologists, in-house leaders, and law firm teams all brought separate definitions, then bumped into each other during generous hallway breaks. Those collisions led to new research threads and fresh coursework, which feels like the real product of a symposium, beyond any single panel.

One surprise thread moved from wonky sidebar to dinner-table topic fast, AI’s energy appetite and the rise of data centers as a local political wedge issue. Mark describes needing to justify the topic months earlier, then watching the news cycle catch up until no justification was needed. Greg connects the dots to Texas, where energy access, on-site generation, and data-center buildouts keep lawyers busy. The point lands, AI governance lives upstream from prompts and policies, down in grids, zoning fights, and infrastructure decisions.

From there, the episode pivots to training, law students, and the messy transition from “don’t touch AI” to “your platforms already baked AI into the buttons.” Mark shares how students now return from summer programs having seen tools like Harvey, even if firms still look like teams building the plane during takeoff. Cat frames the real need as basic, course-by-course guidance so students gain confidence instead of fear. Greg adds a perfect artifact from the academic arms race, Exam Blue Book sales jumping because handwritten exams keep AI out of finals, while AI still helps study through tools like NotebookLM quiz generation.

Governance talk gets practical fast, procurement, contract language, standards, and the sneaky problem of feature drift inside approved tools. Mark flags how smaller firms face a brutal constraint problem, limited budget, limited time, one shot to pick from hundreds of products, and no dedicated procurement bench. ISO 42001 shows up as a shorthand signal for vendor maturity, though standards still lag behind modern generative systems. Marlene brings the day-to-day friction, outside counsel guidelines, client consent, and repeated approvals slow adoption even after a tool passes internal reviews. Greg nails the operational pain, vendors ship new capabilities weekly, sometimes pushing teams from “closed universe” to “open internet” without much warning.

The closing crystal ball lands on collaboration and humility. Cat argues for a future shaped by co-creation across firms, schools, and students, not a demand-and-defend standoff about “practice-ready” graduates. Mark zooms out to the broader shift in the knowledge-work apprenticeship model, fewer beginner reps, earlier specialization pressure, and new ownership models knocking on the door in places like Tennessee. Along the way, Cat previews Women + AI Summit 2.0, with co-created content, travel stipends for speakers, workshops built around take-home artifacts, plus a short story fiction challenge to write women into the future narrative, tiara energy optional but encouraged.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

LINKS:

CAT MOON
Vanderbilt AI Law Lab
VAILL Substack
Women + AI Summit
Practising Law Institute (PLI)
American Arbitration Association (AAA)
Legal Technology Hub

MARK WILLIAMS
Hotshot Legal
The Information
Understanding AI (Timothy B. Lee)
One Useful Thing (Ethan Mollick)
SemiAnalysis
ISO/IEC 42001 standard overview
EU AI Act (Regulation (EU) 2024/1689)
Chip War (Chris Miller, publisher page)

Transcript

Continue Reading Tiara Time and Data Center Politics: Vanderbilt’s AI Governance Playbook with Cat Moon and Mark Williams

Judge Scott Schlegel of the Louisiana Fifth Circuit Court of Appeal joins The Geek in Review for a candid, funny, and unflinchingly practical conversation about AI inside the judicial system. Schlegel wears multiple hats, appellate judge, former prosecutor, reform-minded builder, plus a podcaster and Substack writer who speaks plainly about what works and what fails when technology hits real people on real timelines. The throughline stays consistent, courts do not need more hype, courts need competence, guardrails, and a process mindset.

Judge Schlegel tackles the messy reality of AI disclosures, certifications, and uneven court rules across jurisdictions. His core message lands fast, judicial authority lives with the judge, not an AI system. From there, he outlines why chambers guidance matters, along with a structured, step-by-step approach for responsible drafting support, including prompt discipline and workflow thinking. The goal stays simple, faster decisions without surrendering judgment to “bot overlords.”

The discussion then shifts to constraints judges live with every day, budgets, procurement rules, security anxiety, and the gap between shiny vendor demos and courthouse reality. Schlegel argues for a scrappy, process-first approach using small pilots, one chambers, one workflow, one measurable result. He compares the moment to early “cloud” adoption lessons, pay for the right security, avoid free tools where the user becomes the product, and treat sensitive records with strict care. Courts will see broader adoption as enterprise-grade options become attainable and baked into trusted platforms.

Then comes the part that lingers in your head after the episode ends, deepfakes and voice cloning as a near-term threat to due process, especially in domestic violence and protective order contexts. Schlegel explains why judges tend to err on the side of safety, and why “damage done” shows up long before expert testimony arrives. His practical recommendation focuses on pretrial practice, require disclosure, surface manipulation concerns early, and reduce surprises at trial. He even shares a simple family safety habit, a private “secret word” to confirm identity during urgent calls, since voice cloning tools lower the barrier for fraud.

Finally, Schlegel offers a sharp warning about confirmation bias, large language models often aim to please the user, which benefits advocates and harms neutral decision-making. His answer: an “AI alignment test” mindset, deliberate prompting, and refusal to outsource the white-page moment to a model. For the future, he points toward structural change courts rarely receive funding for, true legal technologists who redesign case management and public-facing guidance at scale. If courts stop printing emails and living in wire baskets, progress follows, and yes, somewhere in a parallel universe, Schlegel still wants a hologram machine.

Links

Judge Schlegel, his court, and his work

AI-in-courts guidance, plus his newsletter

Deepfakes, provenance, and content credentials

  • C2PA, Coalition for Content Provenance and Authenticity, “About” page. C2PA

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript

Continue Reading Bot Overlords, Deepfakes, and the Weight of the Robe: Judge Scott Schlegel on AI in the Courts

The Geek in Review closes 2025 with Greg Lambert and Marlene Gebauer welcoming back Sarah Glassmeyer and Niki Black for round two of the annual scorecard, equal parts receipts, reality check, and forward look into 2026. The conversation opens with a heartfelt remembrance of Kim Stein, a beloved KM community builder whose generosity showed up in conference dinners, happy hours, and day to day support across vendors and firms. With Kim’s spirit in mind, the panel steps into the year-end ritual: name the surprises, own the misses, and offer a few grounded bets for what comes next.

Last year’s thesis predicted a shift from novelty to utility, yet 2025 felt closer to a rolling hype loop. Glassmeyer frames generative AI as a multi-purpose knife dropped on every desk at once, which left many teams unsure where to start, even when budgets already committed. Black brings the data lens: general-purpose gen AI use surged among lawyers, especially solos and small firms, while law firm adoption rose fast compared with earlier waves such as cloud computing, which crawled for years before pandemic pressure moved the needle. The group also flags a new social dynamic, status-driven tool chasing, plus a quiet trend toward business-tier ChatGPT, Gemini, and Claude as practical options for many matters when price tags for legal-only platforms sit out of reach for smaller shops.

Hallucinations stay on the agenda, with the panel resisting both extremes: doom posts and fan club hype. Glassmeyer recounts a founder’s quip, “hallucinations are a feature, not a bug,” then pivots to an older lesson from KeyCite and Shepard’s training: verification never goes away, and lawyers always owed diligence, even before LLMs. Black adds a cautionary tale from recent sanctions, where a lawyer ran the same research through a stack of tools, creating a telephone effect and a document nobody fully controlled. Lambert notes a bright spot from the past six months: legal research outputs improved as vendors paired vector retrieval with legal hierarchy data, including court relationships and citation treatment, reducing off-target answers even while perfection stays out of reach.

From there, the conversation turns to mashups across the market. Clio’s acquisition of vLex becomes a headline example, raising questions about platform ecosystems, pricing power, and whether law drifts toward an Apple versus Android split. Black predicts integration work across billing, practice management, and research will matter as much as M&A, with general tech giants looming behind the scenes. Glassmeyer cheers broader access for smaller firms, while still warning about consolidation scars from legal publishing history and the risk of feature decay once startups enter corporate layers. The panel lands on a simple preference: interoperability, standards, and clean APIs beat a future where a handful of owners dictate terms.

On governance, Black rejects surveillance fantasies and argues for damage control, strong training, and safe experimentation spaces, since shadow usage already happens on personal devices. Gebauer pushes for clearer value stories, and the guests agree early ROI shows up first in back office workflows, with longer-run upside tied to pricing models, AFAs, and buyer pushback on inflated hours. For staying oriented amid fractured social channels, the crew trades resources: AI Law Librarians, Legal Tech Week, Carolyn Elefant’s how-to posts, Moonshots, Nate B. Jones, plus Ed Zitron’s newsletter for a wider business lens. The crystal ball segment closes with a shared unease around AI finance, a likely shakeout among thinly funded tools, and a reminder to keep the human network strong as 2026 arrives.

Sarah Glassmeyer

Niki Black

Marlene Gebauer

Greg Lambert

Transcript

Continue Reading Receipts, RAG, and Reboots: Legal Tech’s 2025 Year-End Scorecard with Niki Black and Sarah Glassmeyer

For decades, “the record” has meant one thing: a text transcript built by skilled stenographers, trusted by courts, and treated as the backbone of due process. In this episode of The Geek in Review, Marlene Gebauer and Greg Lambert sit down with JP Son, Verbit’s Chief Legal Officer, and Matan Barak, Head of Legal Product, to talk about what happens when a labor shortage, rising demand, and better speech technology collide. Verbit has been in legal work since day one, supporting court reporting agencies behind the scenes, but their latest push aims to modernize the full arc of proceedings, from depositions through courtroom workflows, with faster turnaround and more usable outputs.

A core tension sits at the center of the conversation: innovation versus legitimacy. Marlene presses on whether digital records carry the same defensibility as stenographic ones, and JP frames Verbit’s posture as support, not replacement. Verbit is not a court reporting agency; their angle is tooling that helps certified professionals and agencies produce better outcomes, including real-time workflows that once required heavy manual effort. The result is less “robots replace reporters” and more “reporters with better gear,” which feels like the only way this transition avoids an industry food fight in every courthouse hallway.

From there, the discussion shifts into the practical, lawyer-facing side: LegalVisor as a “virtual second chair.” JP describes it as distinct from the official transcript, a real-time layer built to surface insights, track progress, and support strategy while the deposition is happening. Matan adds the design story, discovery work, shadowing, and interviews to build for what second chairs are already doing, hunting inconsistencies, chasing exhibits, and keeping the outline on track. A key theme: the transcript is not going away, because lawyers still rely on it for clients, remote teammates, and quick backtracking, but the value climbs when the transcript turns into a live workspace with search, references, and outline coverage in front of you while testimony unfolds.

Accuracy and trust show up as recurring guardrails. Greg pokes at the “99 percent accurate” claims floating around the market, and Matan makes the point every litigator appreciates, the missing one percent contains the word that flips meaning. Verbit’s “human in the loop” posture and its Captivate approach focus on pushing accuracy toward the level legal settings require, including case-specific preparation by extracting names and terms from documents to tune recognition in context. The episode also tackles confidentiality head-on, with JP drawing a hard line: Verbit does not use client data to train generative models, and they keep business pipelines separate across verticals.

Finally, the crystal ball question lands where courts love to resist, changing the definition of “the record.” Marlene asks whether the future record becomes searchable, AI-tagged video rather than text-first transcripts. JP says not soon, pointing to centuries of text-based infrastructure and the slow grind of institutional acceptance. Matan calls the shift inevitable, arriving in pieces, feature by feature, so the system evolves without pretending it is swapping the engine mid-flight. Along the way, there are glimpses of what comes next, including experiments borrowing media tech, such as visual description to interpret behavior cues in video. The big takeaway feels simple: the record stays sacred, but the work around it no longer needs to stay stuck.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading The Record, Rewired: Verbit and the Next Era of Court Reporting – JP Son and Matan Barak

Artificial intelligence has moved fast, but trust has not kept pace. In this episode, Nam Nguyen, co-founder and COO of TruthSystems.ai, joins Greg Lambert and Marlene Gebauer to unpack what it means to build “trust infrastructure” for AI in law. Nguyen’s background is unusually cross-wired—linguistics, computer science, and applied AI research at Stanford Law—giving him a clear view of both the language and logic behind responsible machine reasoning. From his early work in Vietnam to collaborations at Stanford with Dr. Megan Ma, Nguyen has focused on a central question: who ensures that the systems shaping legal work remain safe, compliant, and accountable?

Nguyen explains that TruthSystems emerged from this question as a company focused on operationalizing trust, not theorizing about it. Rather than publishing white papers on AI ethics, his team builds the guardrails law firms need now. Their platform, Charter, acts as a governance layer that can monitor, restrict, and guide AI use across firm environments in real time. Whether a lawyer is drafting in ChatGPT, experimenting with CoCounsel, or testing Copilot, Charter helps firms enforce both client restrictions and internal policies before a breach or misstep occurs. It’s an attempt to turn trust from a static policy on a SharePoint site into a living, automated practice.

A core principle of Nguyen’s work is that AI should be both the subject and the infrastructure of governance. In other words, AI deserves oversight but is also uniquely suited to implement it. Because large language models excel at interpreting text and managing unstructured data, they can help detect compliance or ethical risks as they happen. TruthSystems’ vision is to make governance continuous and adaptive, embedding it directly into lawyers’ daily workflows. The aim is not to slow innovation, but to make it sustainable and auditable.

The conversation also tackles the myth of “hallucination-free” systems. Nguyen is candid about the limitations of retrieval-augmented generation, noting that both retrieval and generation introduce their own failure modes. He argues that most models have been trained to sound confident rather than be accurate, penalizing expressions of uncertainty. TruthSystems takes the opposite approach, favoring smaller, predictable models that reward contradiction-spotting and verification. His critique offers a reminder that speed and safety in AI rarely coexist by accident—they must be engineered together.

Finally, Nguyen discusses TruthSystems’ recent $4 million seed round, led by Gradient Ventures and Lightspeed, which will fund the expansion of their real-time visibility tools and firm partnerships. He envisions a future where firms treat governance not as red tape but as a differentiator, using data on AI use to assure clients and regulators alike. As he puts it, compliance will no longer be the blocker to innovation—it will be the proof of trust at scale.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Trust at Scale: Nam Nguyen on How TruthSystems is Building the Framework for Safe AI in Law

Few people understand the intersection of legal practice, data analytics, and diversity like Catherine Krow, Managing Director of Diversity and Impact Analytics at BigHand. In this episode of The Geek in Review, hosts Greg Lambert and Marlene Gebauer sit down with Krow to trace her journey from a high-powered trial lawyer to an influential legal tech leader. After seventeen years at firms like Orrick and Simpson Thacher, Krow’s turning point came when a client challenged her team’s billing after a major courtroom victory—a moment that sparked her mission to fix what she calls the “business of law.”

That single moment led to the creation of Digitory Legal, a company designed to give law firms the data and transparency they desperately needed but didn’t yet value. Krow describes how her framework—plan, measure, refine—became the basis for improving cost predictability and strengthening client trust. When BigHand acquired Digitory Legal in 2022, Krow’s vision found a larger stage. Now, her “data refinery” powers better pricing, resource allocation, and even equity within firms. As she explains, clean data doesn’t only improve profitability, it reveals hidden inequities in work allocation and helps firms retain their most promising talent.

Krow also digs into one of her favorite topics: “data debt.” Law firms are drowning in data but starved for information. She explains how poor data hygiene—like inconsistent time codes and messy narratives—has left firms unable to use their most valuable resource. BigHand’s impact analytics tools attack this problem head-on, transforming raw billing data into usable intelligence that drives decision-making across finance, staffing, and diversity efforts. And while the technology is powerful, Krow is clear that solving data debt is as much a cultural challenge as it is a technical one.

Another major theme is the evolving role of business professionals within law firms. Krow argues that lawyers’ traditional discomfort with financial forecasting and project management is holding firms back. Her solution? Combine legal expertise with the commercial acumen of allied professionals. Together, they can meet client demands for budgets, accountability, and measurable value—especially as AI begins to reshape how legal services are delivered and priced.

The episode closes with Krow’s broader reflection on the next decade of legal innovation. She warns that the biggest shift ahead isn’t about AI or analytics—it’s about mindset. Firms that embrace data-driven decision-making now will define the future of law; those that don’t will be left behind. Through her work at BigHand, Krow is helping to ensure that future is both more efficient and more equitable.

Links:

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Data Debt, Diversity, and the Business of Law: A Conversation with BigHand’s Catherine Krow

Daniel Lewis joins us this week to trace a path from Ravel Law to LexisNexis to LegalOn, with a throughline of data-driven thinking and practical outcomes for lawyers. Stanford roots shaped early work on judicial analytics, then a front-row view inside a global publisher broadened focus to content, guidance, and the daily reality of in-house teams. That experience pointed straight at contract review as a top pain for corporate counsel, which led to LegalOn’s product mission and global push.

Data access still shapes progress. Case law digitization advanced through projects like Harvard’s archive, yet comprehensive coverage, secondary sources, and news remain guarded by incumbents. Daniel explains why large datasets give scale, why startups face steep hurdles, and why thoughtful product scope matters. The lesson, build where data, workflow, and user value intersect.

LegalOn’s hybrid approach blends large models with attorney-built playbooks, practice notes, and suggested clause language. Consistency matters more than clever one-offs, so reviews align to standards, not model whimsy. Daniel shares a memorable demo from a rival where a phantom “California Code section 17” alert appeared, a cautionary tale that underscores the need for guardrails, verification, and explainability.

Conversation turns to multi-step agents and matter management. Picture an intake email from sales, missing key fields. An agent requests what is needed, opens a matter, applies a tailored playbook, highlights non-negotiables and fallbacks, then keeps stakeholders informed as work progresses. LegalOn also converts existing playbooks and prior redlines into AI-ready guidance, reducing setup chores while preserving organizational risk preferences.

Finally, Daniel outlines new muscles for legal teams. Daily AI usage shifts time from line-by-line edits to judgment, negotiation strategy, and process leadership. Tech fluency, business orientation, and change leadership rise in importance, along with a steady diet of outside-legal analysis from voices like Ben Thompson and Benedict Evans. The message, free lawyers from sludge, raise the ceiling on strategic work, and build for long-term improvement across the legal function.

Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]

⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.com
Music: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠

Transcript:

Continue Reading Building Consistent AI for Contract Review with LegalOn’s Daniel Lewis