In this episode of The Geek in Review, we welcome three powerhouse guests—Cas Laskowski, Taryn Marks, and Kristina (Kris) Niedringhaus—who are charting a bold course for Artificial Intelligence & the Future of Law Libraries. These three recently co-authored a major white paper, Artificial Intelligence and the Future of Law Libraries (pdf), which we see as less of a report and more of a call to arms. Together, we explore how law librarians can move from reactive observers of AI’s rise to proactive architects shaping its ethical and practical integration across the legal ecosystem.

Cas Laskowski, Head of Research Data and Instruction at the University of Arizona College of Law, shares how the release of ChatGPT in 2022 jolted the profession into action. Librarians everywhere were overwhelmed by the flood of information and hype surrounding AI tools. Cas’s response was to create a space for collective thinking and planning: the Future of Law Libraries initiative and a series of roundtables designed to bring professionals together for strategic collaboration. One of the paper’s most ambitious recommendations—a centralized AI organization for legal information professionals—aims to unify those efforts, coordinate training, and sustain a profession-wide vision. Cas compares the idea to data curation networks that transformed academic libraries by pooling expertise and reducing duplication of effort.

Kris Niedringhaus, Associate Dean and Director of the University of South Carolina School of Law Library, takes the conversation into education and training. She makes a compelling case that “AI-ready librarians,” much like “tech-ready lawyers,” need flexible skill-building models that recognize different levels of engagement and expertise. Drawing from the Delta Lawyer model, Kris calls for tiered AI training—ranging from foundational prompt literacy to higher-level data ethics and system design awareness. She also pushes back against the fear surrounding AI in academia, noting that students are often told not to use AI at all. We couldn’t agree more with her point that we’re doing students a disservice if we don’t teach them how to use these tools effectively and responsibly. Law firms now expect graduates to come in with applied AI fluency, and that expectation will only grow.

When we turned to Taryn Marks, Associate Director of Research and Instructional Services at Stanford Law School’s Robert Crown Law Library, the discussion moved to another key recommendation: building a centralized knowledge hub for AI-related best practices. Taryn describes how librarians are eager to share materials, lesson plans, and policy frameworks, but the current efforts are fragmented. A shared repository would “reduce duplication of effort” and allow ideas to evolve through open collaboration. It’s similar to how standardized models like SALI help the legal industry align without giving away anyone’s secret sauce. We loved this idea of a commons where librarians, educators, and technologists work together to lift the entire profession.

As we explored the broader implications, all three guests agreed that intentionality is key. Cas emphasizes that information architecture—the design of how knowledge is gathered, tagged, and retrieved—is central to AI’s success. Kris points to both the promise and peril of automated legal decision-making, warning that “done well, AI can expand access to justice; done poorly, it can amplify bias.” And Taryn envisions a future where legal information professionals are trusted collaborators across the entire lifecycle of data and decision-making.

We closed the conversation feeling both inspired and challenged. The message is clear: law librarians shouldn’t sit on the sidelines of AI. They are uniquely positioned to lead, to teach, and to ensure that the technologies shaping law remain grounded in ethics, accessibility, and the rule of law. For those who want to get involved, Cas directs listeners to the University of Arizona Law Library’s Future of Law Libraries Initiative page, which includes the white paper and volunteer opportunities. This episode reminded us that the future of AI in law won’t be defined by the tools themselves, but by the people—especially librarians—who decide how those tools are used.

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

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

Transcript:

Continue Reading Law Librarians Take the Lead: The Future of AI and Legal Information

I’ve been thinking about a story that I believe deserves more attention than it’s getting.

Robin AI, once positioned as a rising star in legal AI, has missed its funding round, cut a third of its staff, and landed on a distressed sale marketplace. The question isn’t whether this is unfortunate. It’s whether this is a harbinger. (Non-Billable)

Is Robin AI’s collapse a one-off execution failure, or the first visible crack in a legal tech AI bubble?

What happened at Robin AI

Robin AI launched in 2019 with a compelling premise: a “lawyer-in-the-loop” contract review system that combined large language models with proprietary contract data. The founding team brought credibility: lawyer Richard Robinson and machine-learning researcher James Clough building something at the intersection of both worlds. In early 2024, they raised $26 million in Series B funding.  The marketing was aggressive: major enterprise clients, ambitious platform expansion across drafting and negotiation, claims of transformative efficiency gains.

By late 2025, the picture had changed dramatically. Internal reports suggested the company failed to secure another major funding round (targeting roughly $50 million), laid off about a third of its workforce, and quietly listed itself for sale on a distressed marketplace.

That trajectory, from high-profile funding to forced sale in under two years, warrants closer examination.

The red flags were there

Robin AI never publicly disclosed its Series B valuation. In a market where lofty valuations typically accompany large deals, that absence now looks less like discretion and more like avoidance. Without a clear number, it’s impossible to assess whether investor expectations matched operational reality or whether growth projections were ever grounded in achievable metrics.

More telling were the employee accounts. Reviews on Glassdoor described a culture of overwork, inadequate support, and marketing claims that outpaced product capability. One reviewer noted the company positioned itself as AI-driven while “in practice most of the work is handled manually by staff.”   Another called it their “worst professional experience to date,” citing a “rule by fear” environment where junior team members shouldered contract reviews with minimal support.

These aren’t just grievances about workplace culture. They’re signals about the gap between what was being sold and what was being delivered.

What looks like a fluke Continue Reading Is the Collapse of Robin.AI a One-Off or a Sign of a Legal Tech AI Bubble?

This week on The Geek in Review, Greg Lambert and Marlene Gebauer sit down to compare notes from a busy conference season. Marlene shares her experience at the American Legal Technology Awards where The Geek in Review was honored for excellence in journalism. She recounts the surreal joy of being recognized among friends and peers in legal tech, including fellow nominees like Steve Embry, and how a spontaneous speech turned out to be one of the night’s highlights. The duo reflects on how events like this underscore the sense of community that continues to define the innovation side of the legal industry.

Greg takes listeners behind the scenes at ClioCon, describing it as one of the most energetic user conferences around. He dives into his conversation with Clio CEO Jack Newton and how the company’s recent vLex acquisition signals a bold expansion into the Big Law space. With $900 million in funding, Clio appears ready to bridge the divide between small-firm technology and enterprise-level workflows. Greg also teases an illuminating hallway chat with Ed Walters, now at Clio Library (formerly vLex/Fastcase), about the major leap forward in legal research accuracy driven by improvements in RAG (retrieval-augmented generation) and vector database indexing.

Marlene offers her own takeaways from the Association of Corporate Counsel (ACC) Annual Meeting, where AI and governance dominated the agenda. She describes a landscape where in-house lawyers are wrestling with both the promise and peril of generative AI, from shadow AI concerns to data hygiene challenges. Her biggest surprise was seeing law firms themselves exhibiting at the ACC conference, signaling a shift toward direct engagement between firms and their corporate clients in shared learning spaces.

Together, Greg and Marlene unpack the emerging themes of human-centered governance, the evolving role of AI in matter management, and the race among vendors to automate core workflows without losing the human touch. From Clio’s plans to build AI-driven workflow mapping that could auto-draft documents, to Marlene’s caution about how bespoke law firm processes might resist one-size-fits-all automation, their discussion paints a picture of a profession both accelerating and self-checking at once.

The episode winds down with lighter reflections on travel mishaps, conference after-parties, and the long arc of Richard Susskind’s The End of Lawyers? conversation—still ongoing, now infused with cautious optimism about AI’s role in expanding access to justice. As always, they end where The Geek in Review thrives: at the intersection of humor, humility, and the hopeful chaos of legal innovation.

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 Conferences, Catch-ups, and Clio’s Big Swing at Big Law

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

 

I’ve been watching the legal-tech landscape for a long time, and this morning’s announcement from Thomson Reuters’ partnership with DeepJudge marks a moment worth pausing over. (DeepJudge) On October 22, 2025, TR disclosed that DeepJudge’s enterprise-search and AI-knowledge-platform capabilities will be integrated into TR’s CoCounsel Legal offering to bring internal-firm knowledge and external content into a unified workflow. (Thomson Reuters) For legal innovation folks like me, this is interesting because it suggests a pivot from piecemeal tools toward platform thinking. Also, for more experienced legal innovation folks like me, this sounds a lot like what we used to get from Thomson Reuters with Westkm. But, with a lot more potential.

Here’s why the move matters in practical terms. Many law firms and corporate legal departments generate massive volumes of internal work-product like memos, closing binders, client-matter files that sit behind siloes. DeepJudge is built for just that scenario by its ability to index disparate internal sources (DMS, SharePoint, HighQ, email archives) and surface relevant content fast. (Artificial Lawyer) Meanwhile, TR has been the longtime provider of high-value external legal content (Westlaw, Practical Law, etc.). Bringing those two domains into one searchable, actionable ecosystem offers firms a “360-degree” view of firm knowledge and external insight. (Artificial Lawyer)

That said, I’m not buying into the idea that this solves everything overnight. Integrating internal sources across a global law firm is hard. Really hard!  Things like permissions, data governance, security protocols, taxonomy, indexing, change-management all still loom large in this integration. The announcement acknowledges this. (Thomson Reuters) For many peer firms I talk to, the biggest bottleneck remains adoption and workflow redesign rather than raw technology. Having it available is one thing but embedding it into how lawyers work is quite another.

From a business model and vendor-ecosystem perspective, this partnership is signal-rich. Rather than buying multiple point tools and handling multiple contracts, firms may now sign on with TR for its content, AI workflows, and DeepJudge’s internal-search engine under one procurement umbrella. According to the interview coverage, “in most cases, customers can subscribe to Thomson Reuters and DeepJudge solutions on one single contract … procurement and billing are streamlined.” (Artificial Lawyer) For legal ops and KM leaders, that simplifies vendor management—but it also raises questions: How will ROI be measured? What will change in the outside-counsel bidding process? If internal reuse of knowledge becomes a selling point, will fee structures change accordingly?

Strategically, this might shift how law firms approach their AI and knowledge agendas. Many firms are still running pilots, experimenting in one practice group or region. This partnership offers a more scalable “platform” option by indexing internal knowledge, connecting it to curated external content, and plugging in AI workflows. DeepJudge CEO, Paulina Grnarov, puts it like this: “Every firm working on their AI strategy is realising that fast, efficient access to the right information is the foundation … for making any AI workflows or agents truly effective.” (Artificial Lawyer) For innovation leaders inside firms, the message is clear: move from experimentation to enterprise-scale discipline.

What does this mean for corporate legal departments and legal operations teams? If your outside counsel or you are working with a firm using this combined TR/DeepJudge capability, you should begin asking:
“How are you leveraging internal precedent and firm knowledge in my matter?”
“Are you measuring reuse of knowledge as a value driver?”
“Are you expecting fewer hours or faster turnaround because of built-in indexing and AI?”

As clients increasingly insist on value-based service, this sort of capability may become a differentiator. The risk for firms is that those who don’t evolve may lose ground.

The TR–DeepJudge collaboration is a signal, not a destination. It suggests a next phase in legal-tech evolution through a combined unified internal and external knowledge, AI-augmented workflows, vendor consolidation. But success will depend on execution, governance, adoption, metrics, and change management inside firms. From where I sit, the question isn’t whether this partnership is interesting, because it is. The question is whether law firms will turn the promise into practice, and whether clients will ask hard enough questions to make it matter.

I threw a bit of a fit on LinkedIn three weeks ago when the KM&I for Legal conference published their speaker list and agenda for this year’s conference, happening today and tomorrow in Manhattan. The issue for me was the inclusion of Brad Karp, Chairman of Paul Weiss, to speak on a panel with some fellow BigLaw chairpersons. If that panel was billed as being about the difficulties facing law firm leadership as they attempt to stand up to authoritarian overreach, or even about the importance and role that Knowledge Management and Innovation can play in supporting firm leadership as they face authoritarian policies, or maybe if it was simply billed as an “Ask Me Anything” session affording attendees a chance to better understand Brad Karp’s recent decisions, THEN I would probably have been first in line to pay the $6500 to attend KM&I this year.

Instead the panel is entitled, “Innovation and the Executive Mandate: How Law Firm Leaders Are Reimagining the Future of Law Firms.”

In my original rant, I suggested that Patrick J. McKenna, the consultant who will be moderating the panel, should ask Mr. Karp “what do you believe will best prepare future leaders to defend the rule of law against intense political pressure from an authoritarian executive?”

Mr. McKenna responded to my post and said that “Brad has advised me that he’s prepared to answer that question.”  Bravo Mr. McKenna and thank you Mr. Karp.

I will not be attending KM&I this year, but I strongly encourage my friends and colleagues who will be in attendance to hold Mr. McKenna and Mr. Karp to their word.

Why does it matter?

  • I do not believe that Brad Karp is a bad man.
  • I do not believe that he intended for his actions to precipitate the authoritarian collaboration of other firms, or indeed, the collapse of the rule of law this country.
  • I firmly believe that he thought he was saving his firm from the wrath of a vengeful president through rhetorical appeasement, rather than by giving the administration anything of substance. I have heard that Mr. Karp has argued in other venues that Paul Weiss has only agreed to perform work that they would have done anyway.
  • I believe that Mr. Karp was in a remarkably difficult position and had to make a hard choice and he did the best he could.

None of that excuses his actions.

Our lawyers and law firms are a bulwark against tyranny; the steadfast line of defense against abuses of power and attacks on the rule of law. Mr. Karp failed to understand that the president wanted his rhetorical appeasement more than he wanted $40 Million in pro bono work. The president has since used Mr. Karp’s rhetorical appeasement to brow beat other firms into promising even greater sums of pro bono work for his pet causes. (BTW, isn’t pro bono work intended for people who can’t afford to pay?)

Mr. McKenna, in the comments of my LinkedIn post, said that “Firm Leaders are often called upon to face unprecedented situations.” That is absolutely true and they are well compensated for exactly that contingency. However, that is not the scenario that Mr. Karp faced in March. Eight days prior to the Executive Order targeting Paul Weiss, Perkins Coie faced an almost identical order. Perkins said to the president, in effect, 1) we think your executive order is illegal, 2) we know some pretty good lawyers, and 3) we will see you in court. So which part of that was Mr. Karp unwilling or unable to say?

In fact, every firm that has stood up to the administration has won in court. Maybe those firms are just better law firms, or are willing to hire better law firms. Maybe their leaders are more courageous, or have less to lose. Or maybe they learned in elementary school that appeasement of a bully, even if it’s rhetorical, only leads to more bullying.

If Brad Karp stands up at KM&I and says, “I had good reasons at the time to justify the decisions that I made, but I was wrong. And here is how I, and Paul Weiss, are going to lead the charge to shore up the rule of law in this country in the face of what I now understand to be extreme executive overreach that has consequences far beyond me and my firm.” Then, I will await with bated breath, each and every word that he utters. If his plan is legitimate, even if foolhardy, I will stand beside him in that fight. I will offer MY services pro bono to him and Paul Weiss to “face this unprecedented situation” together.

Brad Karp is not my enemy, but his cowardice in the face of tyranny is not worthy of veneration. His actions to date have disqualified him, in my opinion, from the privilege of waxing poetic on the future of law firm leadership that his colleagues at other firms should enjoy. We don’t need to attend a panel session, to know what “signals” he is watching or what “bets” he is making on behalf of Paul Weiss. He has already made that abundantly clear.

If you attend KM&I on Thursday, and these issues are addressed to your satisfaction before the pontification begins, then enjoy the session and let me know (publicly or privately) what you think, what you learned, and how you feel about Mr. Karp and his decision after hearing his perspective. If it is not addressed right up front or if you do not find his explanation satisfying, then I would encourage you to stand up, and walk out, and use that session time to go meet with the sponsors of the conference, or go get coffee, or go to the bathroom, or do something else more worthy of your time.

The promise of generative artificial intelligence (AI) in legal practice is seductive: speed up document review, contract drafting, legal research, and thereby shave down hours billed. Yet the reality for many law firms is different. A recent survey by the Association of Corporate Counsel (ACC) and Everlaw found that nearly 60% of in-house counsel reported “no noticeable savings yet” from outside counsels’ use of generative AI. (Bloomberg Law News) Among those who did see some benefit, only 13% pointed to fewer billable hours and 20% to faster turn-around.  That suggests the headline of “AI slashes bills” is premature.

One major reason is that law firms remain where they always were: a patchwork of experiments instead of a unified transformation. The business model based on time-spent (“billable hours”) is deeply embedded. As a Harvard Law piece puts it, large law firms’ productivity gains from AI clash with the traditional billable hour model. (clp.law.harvard.edu) When a firm charges by the hour, there is a disincentive to reduce hours spent; improvements in efficiency don’t automatically translate to fewer billable hours. (2Civility) Until the billing model evolves, firms have less motivation to push AI’s full potential into cost-reducing workflows.

Compounding the billing-model friction is uneven adoption of AI across practices and firms. Some firms or practice groups test tools for document review; others do contract-drafting automation; many lag behind entirely. Legal tech firms struggle to sell their AI products to large law firms because the billable hour model skews incentives. (Legal.io) Put differently: the technology is advancing but the institutional deployment lags. An Everlaw survey showed lawyers enabling generative AI report saving up to 260 hours annually, but such gains don’t necessarily map to billable-hour reductions if those hours are reallocated rather than eliminated. (everlaw.com)

From the client side the pressure is mounting. Many in-house legal departments expect outside counsel to adopt generative AI tools. According to a survey by LexisNexis, 67% of in-house counsel said they expect their law firms to use these tools. (legaldive.com) Meanwhile the ACC-Everlaw data show that 64% of respondents expect to bring more legal work in-house because of generative AI. (everlaw.com) In short, clients are signaling change and may drive pricing shifts, even though many firms aren’t ready.

One more factor is the measurement gap. Even when AI is deployed, law firms struggle to track and demonstrate savings to clients. AI might reduce time on a task but still require review, validation, or supplemental work by senior lawyers—so billable hours don’t fall as expected. The SSRN article “How the Billable Hour Can Survive Generative AI” argues that hours may drop but other factors (rate, staffing, utilization) change to offset that drop. (SSRN) Thus efficiency gains aren’t automatically visible or bill-reducing.

Looking ahead, AI’s role may push pricing models to evolve. Several thought-leaders suggest the billable hour’s grip is loosening. For instance a Thomson Reuters article on “Pricing AI-driven legal services: The billable hour is dead, long live…” observes that generative AI may accelerate shifts to flat fees or output-based billing. (Thomson Reuters) Similarly, research from Wolters Kluwer points to 67 % of corporate legal departments and 55% of law firms expecting AI-driven change to the billable hour model. (Wolters Kluwer) The inconsistency across firms means we are in transition rather than arrival.

In sum, AI is real, law firms are adopting tools, and some work is faster. But the core obstacle to billable-hour reduction is structural: the business model built on hours, inconsistent deployment of technology, lack of measurement/discounting mechanisms, and a client-driven push for change from outside. Until law firms coordinate practice-wide workflows, redesign billing, and reflect AI-driven efficiencies in their invoices, clients will continue to ask “where’s the savings?” and firms will nod and say “we’re working on it.”

Well… on the bright side, at least we didn’t say “It depends.”

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:

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[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

Jack Newton knows how to command a stage. ClioCon 2025 opened like a Vegas tech revival, complete with light shows, Clions (Clio employees) marching up to the stage, keynote hype, and a CEO convinced that lawyers are about to enter a “new era of intelligent legal work.” And for the first time, he wasn’t talking to solos and small firms. He was looking straight at Big Law.

After seventeen years of building a platform for the other 80% of the legal market, Clio is moving upmarket with a new product, a billion-dollar acquisition, and a not-so-subtle claim that the incumbents have gotten too slow, too siloed, and too expensive. The message was clear: the cloud kids are all grown up and ready to play with the enterprise crowd.

From Record to Action

Newton’s pitch was simple: “systems of record” are over. The next generation of legal tech will be “systems of action.” Instead of storing what lawyers have done, Clio wants to automate what happens next. Deadlines, drafts, client updates, billing, intake. All of these handled or at least initiated by an AI assistant that never takes a vacation or forgets a date.

It’s a clever reframing of what AI actually means in practice. Less magic, more workflow. The idea isn’t to replace lawyers but to replace all the boring, repetitive steps between thinking and billing. Whether that translates in firms that already juggle iManage, NetDocuments, Elite 3E, and a few thousand customized applications is the question.

Enter Clio Operate

The headline for big firms is the launch of Clio Operate, built on the bones of the acquired ShareDo platform. Newton called it “Clio Manage’s big brother,” designed for firms with 200 to 1,000+ lawyers. The promise is configurability, enterprise-grade permissions, and firm-wide governance that keeps multi-office operations aligned.

That’s all fine. But enterprise lawyers don’t buy promises; they buy controls. Does Operate honor existing ethical walls? Does it integrate cleanly with your DMS? Can it scale to thousands of concurrent users without melting down? Those questions didn’t make it into the keynote slides, but they’ll decide whether Clio Operate becomes a serious enterprise contender or just another mid-market flirtation.

The $1B Bet on Data

Clio’s move from practice management to platform only makes sense if it controls the data that feeds the AI. That’s where the vLex/Fastcase acquisition comes in. It’s a billion-dollar swing that instantly gives Clio something close to global legal data parity with Lexis and Westlaw.

The new structure looks like this:

  • vLex and Fastcase content become Clio Library.
  • Docket Alarm becomes Clio Docket.
  • Vincent AI stays the brain behind the curtain.

Newton’s claim is that by grounding AI in real legal data, Clio can eliminate hallucinations and build something smarter than generic large language models. Maybe. But the bigger question for large firms is how Clio plans to keep that data segregated from confidential firm context. You don’t want your client memo accidentally “enriching” the Clio Library.

Clio Work and the AI Hub

Then came the showpiece: Clio Work, a new AI workspace priced at $199 per user per month. Newton positioned it as the bridge between the “business of law” and the “practice of law.” It pulls matter context from Manage or Operate, fuses it with Clio Library’s legal data, and lets Vincent draft, analyze, and reason alongside you.

It’s a fascinating idea, and at that price point, Clio is deliberately poking the research giants. They’re betting firms will trade legacy precision for workflow speed. Whether the AI can produce consistently reliable, citable output is still unproven. The demo audience saw smooth integration and accurate citations; what happens in a real case file under privilege pressure is another story.

AI Teammates Everywhere

Clio also re-skinned its products around the idea of “AI teammates.”

  • Manage AI: Extracts deadlines, drafts client updates, and even prepares bills.
  • Grow AI: Handles intake, conflict checks, and scheduling.
  • Draft AI: Turns old documents into templates with auto-built client questionnaires.

It’s the kind of automation you’d expect to see in an internal R&D lab at a large firm, except Clio is promising it out-of-the-box. The danger is obvious: an AI that acts faster than your review process. The benefit, if the governance is right, is hours shaved off every case. The line between those outcomes is thin and paved with risk management memos.

Money Machines: Clio Capital and Pay Later

Then came the financial add-ons: Clio Capital, which lets firms borrow through the platform, and Pay Later, which lets clients pay in installments while the firm gets paid upfront. Both ideas make sense for small practices chasing cash flow. For large firms, they look more like compliance puzzles waiting to happen.
Trust accounting, disclosure rules, and client consent all get messy fast when your practice management system starts behaving like a lender. It’s creative, but it’s also an ethics exam question in the making.

The Enterprise Reality Check

Newton’s presentation hit all the right notes—speed, integration, AI intelligence, and global reach. But large firms will judge on different metrics. Before anyone in Big Law gets seduced by the sizzle reel, Clio needs to show:

  • Single-tenant architecture and regional data residency.
  • Immutable AI logs and human-review checkpoints.
  • Deep, tested integrations with iManage, NetDocuments, Elite, and Intapp.
  • Compliance documentation that satisfies outside counsel guidelines.

That’s the difference between a good demo and an enterprise deployment.

Collapsing the Stack

What Clio is really chasing is control of the full workflow. The “intelligent legal work platform” is an attempt to merge research, drafting, intake, matter management, billing, and payments into one continuous experience. It’s the same logic that made Microsoft 365 unavoidable in the corporate world. Once everything lives in one suite, leaving becomes painful.

For Big Law innovation teams, that’s the strategic decision ahead: integrate with Clio’s ecosystem or build around it. Either way, the gravitational pull is growing.

Final Verdict

Jack Newton’s keynote was less a product launch than a statement of intent, along with a much-too-long-for-an-hour-keynote list of new resources and goals. Clio doesn’t want to be the friendly cloud alternative anymore. It wants to be the operating system for legal work, from solos to global firms.

There’s real substance in what they’ve built—the vLex acquisition alone gives them credibility they’ve never had before. But the enterprise market is unforgiving. It doesn’t reward charm; it rewards uptime, compliance, and control.

If Clio can deliver those without losing its speed and accessibility, this keynote might be remembered as the moment the cloud-first company that spent 17 years focused on small law finally cracked Big Law. If not, it will be another well-produced reminder that ambition and enterprise infrastructure rarely fit in the same demo.

 

This week we are joined by Anusia Gillespie, Enterprise Lead at vLex and debut novelist, as she shares her unique vantage point on the intersection of legal technology and the human side of law. Anusia traces her journey from commercial real estate finance attorney to global innovation leader, with roles at Harvard, UnitedLex, and Eversheds Sutherland, all driven by a mission to help lawyers by rethinking the systems they work in. Along the way she discovered that business-of-law blind spots, like a shocking embezzlement incident early in her career, revealed deeper structural issues that inspired her focus on system change.

Anusia describes how legal tech adoption often falters when lawyers’ reactions—especially negative ones—are misunderstood. Far from being a setback, she sees strong reactions as opportunities to engage skeptics and convert them into champions. She shares a vivid example from her current work at vLex, where an initially frustrated lateral partner became one of the firm’s most enthusiastic adopters after receiving attentive support and seeing immediate client impact.

The conversation pivots to Anusia’s new novel Soul Toll, which blends contemporary and fantasy storytelling to examine the personal cost of high-performance legal culture. The book’s central metaphor, the “soul toll,” measures the tradeoff between meaningful work and draining obligations. Through her protagonist Ember, a high-achieving lawyer on a seemingly predestined path, Anusia explores how professional ambition can be engineered and how easy it is to let subtle daily tolls overwhelm the soul. Her goal is to give lawyers and other readers a practical framework for assessing that balance in their own lives.

As AI reshapes legal work, Anusia argues that lawyers need both the courage and the space to “fight for their light,” a phrase she uses as both a personal mantra and a rallying call in the novel. She emphasizes that the industry’s relentless pace will not slow down on its own, so lawyers and firm leaders must deliberately set boundaries and create pauses to prevent burnout. The discussion also explores how technology can relieve drudgery while prompting a new definition of professional competence that values human insight as much as efficiency.

Anusia closes with a challenge to law firm leaders: confront the mindsets shaped by the billable hour and empower lawyers to think beyond six-minute increments. From her perspective, real change begins in how lawyers structure their time and measure success. Whether she is leading enterprise strategy at vLex or writing visionary fiction, Anusia keeps a single purpose in view—helping lawyers build healthier, more sustainable careers. Listeners can find Soul Toll on Amazon and connect with Anusia on LinkedIn to continue the conversation.

Order Soul Toll today on Amazon

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

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

Transcript:

Continue Reading Fighting for Your Light: Anusia Gillespie on AI, Legal Innovation, and the Soul Toll of Law