This week, we welcome back Ed Walters, Chief Strategy Officer at vLex, to discuss the latest advancements in legal AI. The conversation covers the evolving role of AI in legal research, the integration of multimodal AI capabilities, and the ethical considerations surrounding the technology. With the rapid pace of innovation in AI-powered tools, Walters provides insights into how vLex is adapting and pushing the boundaries of legal technology. His perspective underscores the importance of structured legal data, security measures, and law firms leveraging their proprietary data for competitive advantage.
One of the key topics discussed is the impact of reasoning models in AI-powered legal research. Walters notes how tools such as OpenAI, Gemini, and Anthropic’s latest models are transforming legal workflows by enabling more sophisticated research capabilities. These tools allow for more human-like interactions with AI, increasing efficiency in knowledge work by reducing non-billable research time. Walters emphasizes that while these advancements are impressive, legal professionals should always verify AI-generated content, ensuring that human judgment remains the final step in legal analysis.
A particularly exciting development discussed in the interview is vLex’s recent integration of multimodal AI capabilities, enabling the analysis of audio and video files. Walters explains how this feature allows lawyers to transcribe and analyze depositions, oral arguments, and client intake interviews securely within Vincent AI’s SOC 2 Type 2 compliant environment. This breakthrough provides legal professionals with enhanced efficiency in document review and litigation preparation, reinforcing vLex’s commitment to transparency and usability. The discussion highlights how these features bridge the gap between traditional and AI-powered legal workflows, streamlining processes while maintaining high-security standards.
The conversation also explores vLex’s integration of docket alarms into litigation workflows, allowing legal professionals to generate comprehensive profiles of opposing counsel and judges. This tool enables lawyers to analyze patterns in case filings, settlement tendencies, and motion success rates. Walters emphasizes that the ability to synthesize vast amounts of structured litigation data provides firms with a strategic advantage. However, he also acknowledges the ethical implications, stressing the need for transparency in AI-generated insights to maintain the integrity of legal practice.
Finally, Walters shares his thoughts on the future of legal AI, predicting a shift toward the integration of law firms’ proprietary data with public datasets. He highlights vLex’s new initiative, Vincent Studio, which allows firms to create bespoke AI-driven workflows tailored to their specific needs. This, he argues, is the next frontier in legal tech, where law firms transition from passive AI adoption to active AI-driven innovation. As the industry continues to evolve, Walters reinforces the idea that while AI enhances legal practice, human expertise and oversight remain irreplaceable. His insights provide a compelling vision of how legal professionals can leverage AI to augment, rather than replace, their legal expertise.
- Vincent Studio Request: beta@vlex.com
Listen on mobile platforms: Apple Podcasts | Spotify | YouTube
Blue Sky: @geeklawblog.com @marlgeb
Email: geekinreviewpodcast@gmail.com
Music: Jerry David DeCicca
Transcript
Marlene Gebauer (00:07)
Welcome to The Geek and Review, the podcast focused on innovative and creative ideas in the legal industry. I’m Marlene Gabauer.
Greg Lambert (00:14)
and I’m Greg Lambert.
Marlene Gebauer (00:15)
This week, we’re joined by an old friend of the podcast Ed Walters, chief strategy officer at vLex. Ed, welcome back to the Geek in Review.
Ed Walters (00:22)
Who are you calling old?
Greg Lambert (00:23)
Yeah.
Marlene Gebauer (00:24)
Old friend, not old.
Ed Walters (00:26)
Let’s say
a friend of long tenure.
Marlene Gebauer (00:28)
Okay, because that sounds better.
Greg Lambert (00:28)
Thank
That is so true. I knew Ed before there was a Fast Case 50.
Marlene Gebauer (00:36)
That’s right. That’s right. Don’t date you’re dating yourself.
Ed Walters (00:36)
That’s true.
Greg Lambert (00:38)
Hey, good
to have you back on the show. So before we jump into the big topic this week, which is all of the news that’s dropped with the vLex and your new releases, actually, I don’t think you knew I was going to do this, but I’m going to do it anyway. Wanted to have a little banter. So one of the things that we’ve been seeing a lot from the AI tools, the
The commercial ones, OpenAI, Gemini, Anthropics and whatnot, are the launch of the reasoning models over the past few weeks, which I’ve thoroughly enjoyed. I’ve really liked diving in with the deep research and asking it questions and kind of watching it think and humanizing the whole models by saying that it’s thinking.
But I really wanted to kind of pick your brain on this and that is, know, what kind of uses are you getting out of it and are these models eking their way into some of the legal research tools as well? What’s your thoughts?
Ed Walters (01:41)
Yeah, great question. I agree. I think they’re totally fun and really the work product that comes out of them is fascinating. I also like to watch the progress and the kind of humanize, even though I know it’s phony, right? It’s like, you know, when DeepSeek inside of perplexity says, hmm, I guess I’d better pull the European Union regulations for privacy. Now I’m reading those. That’s interesting.
Greg Lambert (02:05)
You can see it scratching
Ed Walters (02:06)
Yeah,
Greg Lambert (02:06)
its beard, right?
Ed Walters (02:08)
like I know it’s phony, but I like it anyway. We’re absolutely going to see these in the legal AI tools for sure. I mean, I’ll just tell you, we’re working with them extensively inside of vLex. I don’t think it’s a big trade secret. mean, we’re…
benchmarking them against each other for different tasks. I was doing it this morning, as a matter of fact, working with our tech team. And so I think there’s a lot of promise for it. This reminds me a little bit of that jump between GPT 3.5 and GPT 4, where there was a pretty big jump in the capabilities. And a lot of people were kind of innovating around that. you know, it would surprise me a lot if we don’t
see that coming up all over the place in legal AI.
Greg Lambert (02:53)
So the thing I don’t want to see is the legal research tool saying, you want me to email you after I’ve thought about this to let you know that then I’m going to conduct my research and then email you later? So that’s.
Ed Walters (03:09)
All right.
Marlene Gebauer (03:09)
Well, I was,
Ed Walters (03:10)
But.
Marlene Gebauer (03:10)
mean, I was like, like I was thinking about like being very practical, like what’s the potential impact on knowledge work? You know, I feel like a lot of times legal research, you know, is, is not billable often. And, this may, have a big impact, in that space in terms of sort of reducing non-billable work and allowing.
researchers and analysts to sort of move more quickly regarding these types of tasks and maybe even get some more insights.
Ed Walters (03:36)
Yeah, but
I think that’s right. And let me just say, like, I think the other thing that’s interesting about it, way beyond research, right? There’s a lot of tasks that are kind of multi-step that we’ve not really been able to trust agentic AI or whatever you want to call it to complete. And there hasn’t been transparency. We haven’t been able to see the steps. But I do think that there’s interesting ways of saying, look, here’s the beginning of a
corporate transaction. I want to know everything about the opposing party. I want to know everything about the opposing law firm and lawyer. I want to look at all of the underlying documents that have led up to this. I want to do some discovery about the context of the transaction.
That would be for a lawyer or a team of lawyers to start with. And I think, you know, we’re getting to the point where these agentic tools can break it down into multiple steps, maybe use different tools or different databases. I mean, we’re looking at this inside of vLex saying you might want to look at, you know, statutes in one area, but then dockets in another area. Maybe you want the patent portfolio and, know, here’s a slice of expert witnesses that we’re going to want to do some
work on at the beginning of a litigation matter maybe and the ability to do these multi-step transactions and sort of bake that into a get me ready for litigation tool, get us ready for this corporate transaction. You know, we’ve just closed the asset purchase agreement. What are the 10 steps that our law firm does when we close a file like that?
Greg Lambert (05:04)
What you just said there made it sound like legal research is really hard.
Marlene Gebauer (05:04)
just sort of capturing that.
Ed Walters (05:10)
It is hard, but I’ll just say, I always think people, because of the heritage of Fastcase and vLex, people think of our tools and Vincent AI as like kind of a legal research only tool and work great at it, but it’s like three or four of 23 different workflows that we’re doing right now. And so I just wanna make sure, I mean, yes, I think it’s gonna be amazing for legal research, but.
Marlene Gebauer (05:12)
What?
Ed Walters (05:34)
The applications are way beyond legal research too.
Greg Lambert (05:37)
until we get AGI and then it just takes all of our workflows.
Marlene Gebauer (05:40)
That’s it.
Ed Walters (05:40)
Yeah,
it’s not emailing you, it’s emailing the client. Right.
Greg Lambert (05:42)
Hahaha
Marlene Gebauer (05:44)
It’s like, I’ll, I’ll take this. I’ll take this one.
Greg Lambert (05:46)
Yeah, sorry, I already got this. I’ll build a client separately.
Ed, Bob Ambrogi had reported on the AI Smackdown that was hosted by the Southern California Association of Law Libraries, or SCALL as we like to call them, which was held recently. And Vincent AI was reported to have…
you know, answer to the question that was posed at the the smackdown. So the test was between Lexis plus AI, which I think is protege now, Westlaw precision AI, which they branded, I think the whole concept is co counsel. Now is the is the package. So, you know, branding, guess is important. And, and vLex is Vincent AI.
Ed Walters (06:27)
Hahaha.
Greg Lambert (06:31)
Is there a different way to brand that or is it still Vincent AI? All right. Thank you. Thank you. So, but the panel of librarians still said that, know, AI assisted research is a great starting point and to use, you know, and use of traditional sources are still necessary. So why do you think that they still look at
Ed Walters (06:34)
We’re keeping it super simple. It’s just Vincent AI.
Marlene Gebauer (06:37)
like it.
Greg Lambert (06:56)
going back to the core research is VLEX trying to change that?
Ed Walters (07:01)
Yeah, well, I think that they did an awesome job in this review. I mean, not just because we did really well, but I think it was I love seeing doesn’t hurt. But I love seeing law librarians in these kind of benchmarking tests because they are so rigorous in the methodology. They really understand well how to gauge quality.
Greg Lambert (07:08)
It hurt.
Marlene Gebauer (07:08)
which always helps.
Ed Walters (07:21)
and to do that in a kind of a quantitative objective way. And so I thought SCALL did an amazing job of this. And I think that the tools were very powerful. think all of the tools did really well. think it was pretty clear from the conclusions, not mine, but theirs, that Vincent had the most depth of the answers and got some uniquely right answers that the other tools didn’t.
And as proud as I am, I’ll be the first to say, our whole team always says, these are first draft answers, not last draft answers. If you had a superstar associate in your firm, your corporate legal department, and gave them a research task, and they came back with like a just rock solid answer, you still have to go read the cases and the statutes to make sure that they say what they’re supposed to. You have to verify even the best human lawyer work.
And I think the same thing is true about these kind legal AI tools. You should trust but verify. And my hope in this is that, well, you’ve heard me say this before. I don’t think that legal matters are a single event. They’re a chain, right? And we might be able to replace the most boring or problematic or difficult links in that chain. But I always think that the last links of that engagement have to be human judgment.
And there’s no AI tool that can or should replace that human judgment at the end. And so maybe we can take the first two days of an engagement and throttle it and get an 80 % answer in the first 10 minutes, five minutes, I don’t know, but very quickly get some of the early blocking and tackling work done.
so that lawyers can do more. And maybe they bill the same number of hours, but they just do better work in that time. Maybe they don’t have to file the extension that they typically file because they’re able to really crank on that work in the first couple of days. That’s kind of my aspiration for Vincent AI. I think that’s what we’re really hoping.
Marlene Gebauer (09:05)
You
Yeah, it’s, it’s, it’s noteworthy that like Bob actually tried the test himself and he was using deep research and he said it reported very adverbially, you know, without access to paywall legal research content. And I, know, I’ve seen some, gen AI solutions that,
Ed Walters (09:16)
Hahaha!
Marlene Gebauer (09:28)
don’t have that type of behind the scenes access and then you know they perform okay but not apparently as good as deep research did and I’m curious like do you have any thoughts about how they managed to accomplish that?
Ed Walters (09:44)
well, they’re using public data sets like Justia. And so that’s great. I I think the questions I would ask are, where’s the citator? And how are they making sure that they’re pulling from the majority opinion and not the dissenting opinion?
Marlene Gebauer (09:46)
Right.
Ed Walters (09:58)
the majority opinion not a concurrence. In a Supreme Court case where four justices are joining part two and three are joining part three, but parts one and five are the majority opinion, we making sure that that part is being treated as governing law? And so this is a super hard problem. We actually created the cert citator at Fastcase and now vLex.
to help address that issue. We worked with the Judicata team when they joined Fastcase to parse the entire judicial opinion library, break out the majority opinions from the concurrences and the dissents. The first 85 % of it is pretty easy for the large language models to do. But the last 85 % is essential for lawyers. And you really have to have custom built
legal AI tools to do that. And not just any off the shelf, we’re lawyers too, tools. I mean, this is really hard. We spent, I don’t know, four years, $5 million building the cert citator. And we had, you know, the Judicata team who worked on that with us in house is like some of the brightest people who have ever
thought about legal tech. So I just want to say I have huge respect for the deep research tools. They’re amazing. I use them all the time. For legal work, the last 15 % matters and that’s the part that the Vincent AI VLex team sweats all the time.
Marlene Gebauer (11:20)
Yeah, that’s a really good distinction to raise.
Ed Walters (11:24)
And is it current, right? mean, we’re updating these things like, you know, every day. We don’t really know when the last time those models were trained or what data sets are pulling from.
Marlene Gebauer (11:34)
or when those public sites have been updated as well. So in addition to the skull testing, VALS just
Ed Walters (11:37)
Great.
Marlene Gebauer (11:43)
released their report on legal AI. And so this study is apparently the first systematic attempt to independently benchmark legal AI tools against a lawyer control group in this instance. And so they use, you know, I guess several real world tasks and they got it from AmLaw 100 firms. And apparently there were some instances where the AI outperformed the lawyers. So I’m wondering, should we be worried?
Ed Walters (12:06)
Hahaha.
Well, I mean, this was certainly true with eDiscovery and law firms made a ton of money from eDiscovery, sending young lawyers to warehouses in upstate New York and New Jersey. Strangely specific example, yes, I was one of them. And, you know, at some point software got better at that, better at accuracy, better at recall for discovery tasks than human lawyers. And
There are more lawyers in America after e-Discovery than there were before. They tend to be happier, fewer paper cuts, fewer associates quit in the warehouse in Isla, New Jersey. Stradely specific example, so I think we may be at that moment right now, like the…
Marlene Gebauer (12:47)
That sounds oddly specific too.
Ed Walters (12:57)
The big watershed event for eDiscovery was a report by Maura Grossman that said that the tools had higher accuracy and higher recall than human review, which has its own error rates. And feel like this VALS report may be one of those watershed moments. Look, I deal with lawyers all the time and law students who say,
Legal AI is great, but these tools just aren’t there yet. And when I ask like, what do you mean by that? They say, I just don’t feel like they’re quite good enough. And this is the first attempt really to quantify that. To be fair, the lawyers did great too. These are very good lawyers, but in many cases, the AI tools as a whole did measurably better than lawyers. The kind of blind,
Marlene Gebauer (13:43)
Was it areas that you would expect
that they would do better?
Ed Walters (13:46)
Yeah, sure, absolutely. Take a of documents and create an accurate summary, sure. mean, think clear that large language models will have an advantage I think lawyers did really well in complex synthesis of SEC That doesn’t really surprise me. was surprised, though, that
the AI tools as a whole did as well as they did. I’m really psyched about it. I’ll just say directly, tasks that Val’s AI were studying are not super strong tasks for Vincent AI. You know, we’re…
our strength is really this giant mass of structured legal documents for tasks like research or analyzing the legal implications of an asset purchase agreement by looking at Michigan law. And these tasks were kind of extractive. We’re gonna give you a document and then pull all of the key terms out of the document. We do fine at that, right? But I mean, our strength is really in more complex tasks.
And Vincent did great. I mean, in four out of the five areas where we were competing, we were within the margin of error or measurably better than the lawyers doing that work. And again, this was blind grading. wasn’t…
The people who were evaluating it weren’t looking at the answer key. They couldn’t see which came from which service, whether it was created by a lawyer or somebody else. The other takeaway, by the way, that I thought was really interesting was at the slowest, the AI tools were six times faster than lawyers. At the fastest, they were 80 times, not one eight, eight zero, 80 times faster than lawyers working on the same tasks.
Marlene Gebauer (15:20)
Wow.
Ed Walters (15:25)
and better and, you know, measurably higher quality answers. That’s amazing.
Greg Lambert (15:30)
Yeah. Yeah. Well, I mean, that’s the thing with technology is that you use it it makes you more efficient. If you can do the triad of better, cheaper, faster, let’s try to do that.
Marlene Gebauer (15:30)
It is.
Ed Walters (15:45)
Absolutely,
yes.
Greg Lambert (15:47)
So Ed, one of the features that you just released that I’m really excited about is the ability for vLex to do multimodal type interactions where it can analyze audio and video files, which is something that I’ve been excited about since OpenAI came out with Vision. And you could take a.
You know, take a picture of a guy standing on a ladder that’s on top of a forklift and ask what OSHA violations there are here. So, you know, and I think that really has a really good use case in litigation, probably others as well. So you might kind of give us a little bit of the details of how it works, how you got it implemented and what are some use cases that you think people can use it for.
Ed Walters (16:17)
All right.
Sure, and would you like to take a look while we discuss it? Yeah.
Greg Lambert (16:41)
You want to jump in on that
Marlene Gebauer (16:41)
Yeah.
Greg Lambert (16:42)
part, Marlene? Let’s do it. Let’s do it.
Marlene Gebauer (16:44)
Okay.
Ed Walters (16:45)
All right, so this was something that a lot of law firms and corporate legal departments were asking us for because they deal with an intake interview that they videotape where they have the audio transcript of a deposition or maybe like a, video of an oral argument as we have in this example right here.
How do we deal with that? Like you finished the oral argument, you want to report back to the client, what do you tell them? You can’t give the oral argument and take notes at the same time. Being able to take the transcript of a deposition and say, what parts of this deposition are inconsistent with the documentary evidence we have before? And you can’t deal with that if you can’t transcribe it.
There are plenty of services that transcribe audio and video, but they’re not secure, right? And so Vincent AI is SOC 2, type 2 compliant, the most secure platform certifications you can get, because Marlene told me that we had to, and we did. And so now you can deal with audio and video files in this very secure environment that meets all of your clients’ requirements as well.
Marlene Gebauer (17:39)
Ha
Ed Walters (17:48)
So this is it right here. In this example, I have uploaded kind of a long 30 minute MP4. This is a video file of an Ohio Supreme Court oral argument. It involved, you know, a judge who is reprimanded for speaking about politics in court. And so immediately when I upload it, Vincent creates a transcript.
And so we can see right away the entire transcript of the oral argument. Now I can copy that, paste it into a Word document or something. But from that, just like other places you’ve seen in Vincent AI, Vincent reads that transcript and says, what do you want to do with this? I mean, you can ask something open-ended if you want. I think this is really a strength of Vincent. It says, like, here are the kinds of things that lawyers would do.
when you have this kind of document, the transcript of an oral argument, for example, but whatever it is. And so you see these very specific suggestions, create a concise summary of the defense arguments presented by Mr. Funk on behalf of this judge focusing on the First Amendment issues, create a timeline, draft rebuttal points. And then at the bottom, these are legal questions. So if you want to do research,
and find out what the legal precedents are for First Amendment protections for judges in Ohio, you can select that. And of course, we’ll pull that from the VLex collection. What are the standards for judicial discipline in Ohio? These aren’t baked in. These are suggestions that are created by reading through the transcript of that oral argument. And so you can see when I create a timeline,
you know, it puts it in a nice table. I can download that table in Excel. This is new. So in the last column, it says source, and the source is from the transcript. And if you mouse over the site, it’ll show you what in the transcript created that element in the timeline.
But if I click it, it will open the transcript and jumped right to the part of the transcript where that came from, allowing you to verify for yourself that should be in the timeline or not. And let me just say one thing about this. So I’m pretty excited about this individual element. A highlight of Vincent in the past was the transparency of it.
being able to see what sources go into making an answer, have hyperlinks to them, open the statute, open the judicial opinion, open the regulation, confirm it for yourself. This allows you to do that same kind of transparency with documents that you upload. So if you upload 100 documents and say, analyze all the legal risks in these documents.
They can create a table or a list and have the citations to those documents. These are all from the same one, but in that case, you would have like the name of the document and the place where that risk was identified. And you can mouse over it and see where it comes from or click on it and jump right to the spot in that document. This creates that same kind of transparency that Vincent is known for with primary law.
but that transparency extends to documents that users upload, which is really nice. And in this case, like a transcript or an oral argument or something.
Greg Lambert (20:57)
Now, I know one of the things I think right now what it’s doing with the video is that it is extracting essentially the transcript and using the text. Do you see in the very near future that it can go just directly off of the video itself so that it’s not just essentially creating text out of the
out of the voices, but can leverage some of nuances that are in the actual images of the video itself. Because that’s something I think we’re not quite at yet, but hopefully getting to.
Ed Walters (21:38)
Yeah, I love that idea. And what I imagine is like maybe the top of the frame being the video and the bottom being the transcript or the top being the audio and the bottom being the transcript. And when you jump to the point where the written transcript exists, you’ll jump to the same point in time in the audio or video file so you can listen to it and hear it for yourself.
Marlene Gebauer (21:58)
Very cool.
Greg Lambert (21:59)
It’s
It’s interesting times.
Marlene Gebauer (22:01)
Very cool, very cool.
Ed Walters (22:01)
It’s amazing. So this is
part of the winter 2025 release of Vincent AI. We’re moving to a kind of a seasonal release schedule and there’s just so much in these. When we launched autumn 24, there was like a lot in that release. In the winter 25 release, similarly, there’s a lot going on here. People who subscribe to Vincent get all of this for the…
included at no additional cost. It’s included in the price of the subscription. I mean, it’s a pretty startling upgrade. And I’ll just mention like all of the benchmark tests and everything that were done, the SCALL and the VALS AI benchmark were before we launched winter 2025. So there’s all kinds of new skills and abilities in Vincent now too.
Marlene Gebauer (22:49)
So another part of the Winter upgrade, I guess, is vLex is now integrating docket alarms litigation data to produce litigation workflows, which is really great, I think. mean, it’s like we’ve been focused for so long on transactional workflows in Big Law and innovation there. So I think it’s nice to see.
As a former litigator, I think it’s nice to see litigation get its due. in using these workflows, what are the ethical considerations lawyers need to be aware of? And also, I don’t know if you can show those or not, but if you can, great. We’d love to take a look.
Ed Walters (23:13)
Hahaha.
Yeah, happy to. So let me just say, first of all, thank you, because I think that the docket alarm materials are so helpful. It’s a gold mine, right? There’s so much information in the complaints and briefs and pleadings and motions before judges. the docket alarm collection is more than 860 million docket sheets, briefs, pleadings, motions.
Marlene Gebauer (23:31)
Mm-hmm.
Ed Walters (23:46)
And each individual document is great. You can use it as a precedent if you’re about to file something. It solves the blank sheet of paper problem. But in the aggregate, it’s so useful. The information here about individual lawyers or judges or law firms or parties. If a party never settles, that will…
be something that you see in their docket filings. It’s not going to be a judicial opinion or something, right? There’s not going to be a statute that you can conjure up that says Google tries its cases instead of settling them. you can see that in the docket information. And so one of the cool things about it in this winter 25 release is that we have released a whole bunch of new AI workflows that leverage
this docket information. I think this is unique. I don’t know of anyone else who has legal AI tools that are building on top of this kind of giant volume of structured data. And the other thing that’s cool about it is you can ask open-ended questions. Like, show me all of the data protection cases that deal with children.
There’s not a flag and pacer or something or in California dockets that mention whether the case involves children, but you can find that with AI. And so in this case, I asked, me a profile of a lawyer. And Vincent in docket alarm, or VIDA as we call it, went into the docket databases and found a bunch of the cases litigated by this lawyer. Not like one document.
It’s not like pulling the complaint. It’s pulling the entire docket for the case. Some of these cases aren’t even completed, right? And so we have a complete summary of this case.
what her role was, the status of the case, the background of the facts, what happened in the motion practice, what the outcome of the case was, how complex it was, experts were in the case. And if I click on it, you go straight into that full docket in Docket Alarm. So you can see for yourself, you can run the timeline to sort of see what happened in this case. I mean, these are amazing. This is really cool.
And then, so this pulls like, you know, lots of these major cases for this lawyer and summarizes them all and then rolls them up into an answer and says, here are the types of cases this lawyer has handled, False Claims Act, RICO, securities litigation. Here’s how effective she is in her motion practice. Here’s the average case duration. Here’s the most significant cases. Here are the major clients who she’s worked for.
Marlene Gebauer (25:42)
That is.
Ed Walters (26:06)
So this is, I don’t know, it’s not the first time we’ve profiled lawyers ever, but this took like maybe 10 minutes, right? And so it’s almost crazy not to do this at the beginning of a case. Like, why wouldn’t you want to know everything about the opposing party, about the law firm who works on the case, about the individual lawyer who’s going to be first chair?
Marlene Gebauer (26:13)
Right, right.
Ed Walters (26:27)
I think of it almost like shepherdizing the lawyers and the judges and the opposing parties before you start a case.
Marlene Gebauer (26:35)
that it’s gonna offer you insight in terms of your litigation strategy. How familiar is this person with the type of claims that are being raised? Do they settle, do they not settle? All of those things are gonna influence how you approach it and how you advise your client.
Ed Walters (26:51)
And I’ll just point out, I didn’t run like a Boolean terms and connectors search here. This is the way you would ask like a research associate a question and Vincent figures out, says like, here’s the kinds of things I would want to pull together. I think this is the most agentic of the winter 25 workflows. It’s doing like 50 different things behind the scenes and then bringing them all back together.
and then summarizing them in this beautiful, comprehensive, fact-based report.
Marlene Gebauer (27:20)
I feel like you could sort of use this in combination with other things in doing vLex and sort of, know, put together a package and sort of deliver that as a product, you know, as opposed to just kind of answering a question.
Ed Walters (27:30)
It’s a great insight. I think this is one of the ways forward for law firms, by the way. If their work becomes more efficient and the number of hours dips a little bit because of that efficiency, why don’t we do more for clients and refill the bucket? Let’s create new products for corporate legal departments that would be super helpful for them, that they would want to see. They would want the extra information and the insights.
Greg Lambert (27:30)
Yeah.
Ed Walters (27:55)
that we can create. these are products that we can create inside of law firms and make even more money.
Greg Lambert (28:03)
Yeah. And Ed, one of the things, do you mind just going back real quick to the one you did with the Illinois lawyer, hers? So I just wanted to read that because the actual prompt was just please profile Illinois white collar litigator and in this case, Lisa Knoller being the name. You want to see what she’s up to these days,
Ed Walters (28:09)
Sure.
She’s a friend from law school, so I picked on her.
Marlene Gebauer (28:26)
So she’s okay
Ed Walters (28:26)
She’s
an excellent litigator.
Marlene Gebauer (28:27)
becoming famous.
Greg Lambert (28:30)
I’m just wondering, know, we’re seeing a lot of tools, like, I think perplexity was kind of the leader in this of also being able to essentially search the internet as well. I’m curious, do you see at some point that you could augment some of these and just say, you know, also go out and search the web and augment the information, or do you think there’s.
issues with that, at least at this point.
Ed Walters (28:58)
I love that idea. I mean, especially if it’s from like a firm website or something, I think that would be super useful. I wanna put guardrails on it because the information we’re using is all public documents. It’s all verified, it’s all been filed in courts. There’s a little bit more verification I would wanna do on the public web.
I’m not going to start pulling YouTube comments and threads from Reddit or something. I would just say with it. but I do think that there is the potential to weave those kinds of agentic workflows into these products where you have guardrails, where you can verify.
Marlene Gebauer (29:19)
Hehehe.
Greg Lambert (29:22)
That’s where all the juicy information is, Ed. Come on.
Marlene Gebauer (29:22)
I don’t know, you might be able to find some stuff in there.
Ed Walters (29:37)
But at the very least, there is such a goldmine of information in these kind of publicly filed documents in state and federal courts. The big data implications when you combine it with AI allow you to ask very simple questions and get quantitative, very specific, well-substantiated information back.
Greg Lambert (29:57)
Well, thanks for walking us through that. So since we’re talking about security and making sure that we’re verifying the right information and we’re being careful with it, you had talked earlier about vLex becoming SOC 2 Type 2 certified. You’d already had, I think, the ISO 27001.
Marlene Gebauer (29:58)
Yeah, that’s
Greg Lambert (30:20)
And so, you know, what does that mean for your users? Does that mean that we can now put our information into Vincent and feel that that’s safe? you know, did it help you? Yeah.
Ed Walters (30:33)
In a word, yes. I mean, yes.
So we’ve had these very good security practices all along. I think that’s table stakes. It’s very, very important. It takes a little while for SOC 2 to complete the certification to validate that you are doing everything correctly.
Marlene Gebauer (30:43)
Yeah, I agree.
Ed Walters (30:53)
SOC 2 Type 2 is like one of the highest security certifications you can have. Law firms have to have it for their own internal systems. And what it means is that lawyers, law firms, corporate legal departments can rest assured when they upload documents.
whether it be something for an &A transaction to do due diligence or collections of documents they’re working on litigation, or if you’re uploading a contract draft or drafted a complaint or something.
they can be assured that that is never used to train AI, it’s not being sent out on the public web, it’s being kept within the secure environment for that law firm. And at the end of the session, all of it is scrubbed. So you don’t have to worry about…
know, data breaches or something, the information put into Vincent AI is kept in the highest security vault you can possibly have. And so I love having the certification. think that’s very useful. I think there’s a lot of law firms who trust us in the first instance, but their clients insist that you have to have that kind of third party validation, which I totally understand and I don’t blame them.
Maybe one other thing I would love to call out for this release, although I’m a little sheepish about it. So I think we’ve done a pretty good job of launching things instead of announcing a roadmap. It’s a pet peeve of mine with legal tech products when they say, you know, today we’re announcing version two of this thing. It will be released at some point, you know, in the next six months.
Marlene Gebauer (32:20)
It’ll
be released in six months. Yeah.
Ed Walters (32:23)
Yeah, or like, you
know, here is the next generation of our tool. This is a PowerPoint that shows you what it might look like at some point in the future. Yeah, yeah. Right. Look, and I get it, you know, I shouldn’t knock them too much, but I think at least the vLex team has done a very good job of building first.
Greg Lambert (32:31)
Here’s a wire frame. Here’s a slick advertisement of something that we’re thinking about doing.
Ed Walters (32:46)
and then announcing it and releasing it. All this stuff is live. Everything I’ve shown you has been live in the platform for several weeks. The best firms in the world are already using it to get a leg up. So this last part, I am just a little shy about. I’m announcing with our team, Vincent Studio.
and we’re opening the beta to it right now. Anyone who’s interested can send an email to beta at vlex.com for consideration for Vincent Studio. That puts the firm’s own ideas, their own tiles on the home screen. And so I would just say like the Vincent Studio is a makerspace.
for the world’s most innovative law firms to create their own workflow tools. They can use VLex data, they can use VLex tools, but then use their own expertise, their own use cases, their own data if they would like to, or their own AI tools. But they can do it all in the secure environment. And instead of us saying, know, we’re gonna send you a copy of the, you know, Texas code.
you can just use the Texas code inside of vLex, which we’re updating every day and build on top of that. And so when people build these tools, their workflow tools will appear on the home screen right next to ours.
And there will be like a collection of the firm’s workflow tools that leverage the firm’s expertise. If a firm has a particular strength in oil and gas or securities offerings or venture proffers or something, then they can use that expertise and the firm’s own documents supplemented with ours.
and create their own workflow tools on this home page. I think that’s cool. And we’ve had a lot of law firms come to
and say, I would love for you to create something that’s very highly bespoke to us. And I think our response has been, look, we can’t build everything that every law firm wants to do with AI.
but we will co-develop it with you. We’ve got this brilliant team of people at vLex Labs who are really good at product specification management and design, and they know all the tools, all the APIs inside of our house, all the data sets.
So this is an opportunity for law firms to create their own legal data tools. One thing I love is I think that there’s a lot of cool innovation projects inside of law firms. There’s really good ideas. Sometimes I’ve heard like even some firms are taking their new associates and having not quite a hackathon, but like kind of an idea-a-thon where they pitch an idea for a new tool.
I would love it if the winning project were submitted into the Vincent Studio Beta. And they would then, by winning, have the opportunity to work with our team and to build it in the real Sometimes I feel like the law firm innovation initiatives will have like 90 % of what they need. That last 10%, like you don’t want to update
the US code every day. That last 10 % is something that we can help with. Maybe it’s last 40 % or I don’t know how much of it is going to be from the firm and how much is going to be from us. if we can help firms get those innovation projects over the line using our expertise and our data with some code development in Vincent Studio, I think that’s going to be a real winner. I’m excited about that.
Greg Lambert (35:40)
Yeah.
Yeah.
Interesting. Cause I, know like yesterday I was working with a, with a group of attorneys and one of the, one of the projects that they had pitched was, uh, like they’re there. These were, uh, finance folks and, and like UCC three, which I didn’t even know about was, was, was a thing. Um, shows, it shows where I am. Um, but you know, very important. No, what?
Ed Walters (36:21)
Ha ha.
Did you know there was a UCC2? Just want
Greg Lambert (36:30)
No. my God. I just remember when it was “U” So,
Marlene Gebauer (36:30)
Hahaha!
Ed Walters (36:31)
to make sure we’re catching you up. Yes.
Marlene Gebauer (36:36)
ha ha
Greg Lambert (36:40)
but you know, but one of the things that was kind of holding back that project was the fact that, well, yeah, you know, we can create like a KM system that will have this, but as with most KM systems, as soon as you develop it, it’s already, you know, it’s already becoming obsolete.
So I can see where something like this would be really, really interesting for those types of groups, for KM projects where it’s very important to keep things up to date and know as they change. So I think this is brilliant idea.
Marlene Gebauer (37:15)
Yeah, I mean, and you know, as long as it is easy for them to use, that’s the key. Yeah.
Ed Walters (37:15)
Thanks very much.
I think that’s really the strength of AI.
The old way we did this, the kind of Boolean terms and connectors searches where you get back like thousands and thousands of irrelevant results and maybe not even all of the important ones. feel like that Boolean searching maybe isn’t dead but certainly shouldn’t be the default anymore. If you can ask the questions in very clear language.
have the machine refine it.
Greg Lambert (37:46)
You know the hair on all the law
librarians back of their necks just stood up and you said that,
Marlene Gebauer (37:49)
I was gonna say we’re gonna get a whole bunch of comments on this.
Ed Walters (37:53)
Yes, but I also know that a lot of that hair was lost in Boolean searching. really feel like that is one of the strengths here, being able to ask the question like you would ask a colleague. And as you remember from the Autumn 24 release, there is this feature inside of Vincent called prompt assist, where it will read
Marlene Gebauer (37:59)
Turn white.
Greg Lambert (37:59)
That is true. That That is
true.
Ed Walters (38:17)
the question as you typed it and said, hey, you know, there might be a different way of phrasing that, or it looks like you’re asking two questions. Do you want to answer one both? You might get a better answer if you break this up into a couple of different things. I think that’s amazing. I think that’s really useful. And instead of getting back like, you know, no results found because you misspelled a word, having to come back and say,
You you misspelled this word. And by the way, there’s a bunch of expressions about this that you don’t even need to worry about. They’re kind of related in you know, AI sense, and we’ll just go find them for you.
Marlene Gebauer (38:50)
Well, I want to change topics before we wrap it up. We just saw in the news, recent news that Rev Ventures, which is a corporate venture capital fund funded by RELX has invested in Harvey. And I’m curious since you are a futurist and a big thought leader in.
in the space of legal technology, what message do you think that’s sending to the legal tech industry?
Ed Walters (39:15)
I don’t know about a futurist, but maybe I’m a gossip. I don’t know. I’m fascinated by this question. I would love for you to ask that question to somebody at Reed Elsevier or Harvey. It’s very hard from the outside to see what might be involved in that.
Greg Lambert (39:20)
Aren’t those really the same thing?
Ed Walters (39:41)
I assume that RELX is also investing a ton of money in Lexis’ tools as well, I hope. So maybe this is like spreading your chips around or something. I don’t know, it’s kind of hard to say.
Marlene Gebauer (39:54)
Yeah, maybe.
Greg Lambert (39:54)
Well,
are they giving you any money Ed?
Ed Walters (39:58)
Rev? No. is not an investor in vLex.
Marlene Gebauer (40:00)
Rev.
Greg Lambert (40:08)
right, well, Edward, the crystal ball point, and I know we asked you just a few months ago your crystal ball vision of the future, but what do you see as driving change over the next year or two? And what do you think the industry is going to look like?
Ed Walters (40:26)
Yeah, I’m cringing thinking about what I might have said the last time you asked me this. Some accountability here. So let me just say this. One thing I’m… Right, so let’s establish that I was completely right with my predictions last time you asked, as always. Let me just say, this is a little bit self-interested, but I’m observing it in the world.
Marlene Gebauer (40:30)
We should have looked that up before we did this.
Greg Lambert (40:32)
Yeah.
Marlene Gebauer (40:37)
It’s good we didn’t look it up Ed so you can just say whatever.
As always.
Ed Walters (40:52)
One thing that’s really important right now in legal tech is how defensible people’s positions are. Things are changing so fast. There’s so many new companies coming in. The foundation models are getting better. kind of bigger players, the platform players in legal AI are constantly expanding their offerings. And I think one of the biggest questions for the next couple of years is, you know,
are these tools defensible? Are people building something that, know, co-counsel couldn’t just release as a feature or that couldn’t be coming out in the next version of OpenAI’s tools? You know, and so it’s gonna be really hard, I think, for point solutions or, you know, companies who have like a single product offering.
to be able to defend that territory when the foundation models are getting so much better, so much faster. And I think it’s been part of our strategy at vLex. Like we said, when we merged with Fastcase and vLex, that the foundation models would become something of a commodity. Do we care whether we’re using Claude, Sonnet 3.7 or GPT
DeepSeq or something, we don’t really know at some level whether that’s gonna be a differentiator. But structured data is absolutely a differentiator. Like it took Fastcase and vLex, vLex around the world, Fastcase in the US, like 25 years of boiling the ocean to build that database. And there’s so much that happens behind the scenes to keep it updated to…
build the cert citator to make sure that we’re pulling the right parts of judicial opinions, that we’re updating statutes with recently passed acts. It’s insanely hard. I mean, that’s something that you can’t just roll into the next version of Gemini. something that you can’t just throw a lot of money at and build in any short amount of time.
And so I do think those differentiators in the market are going to remain important. That was our thesis two years ago when we merged. And I think it’s maybe even more true now. If I can make a slightly controversial prediction.
Marlene Gebauer (42:52)
Please. We like those.
Greg Lambert (42:53)
Those are the best kind.
Ed Walters (42:55)
I think that there’s not going to be any solid middle ground for improvement of the kind of general foundation models going forward. jump from GPT-4 to 4o the jump from, you know, kind of 3.4, 3.5 of Claude to 3.7, these are all relatively linear.
The makers of these models seem pretty confident that we’re gonna achieve artificial general intelligence or AGI sometime during the next four years and I’ll just say like I’m pessimistic about that So either that’s going to happen and all bets are off everywhere or There’s gonna be a kind of a plateau, you know, we run out of words
There’s not enough words to get like that kind of step improvement in the models. And the ability of the foundation models kind of plateaus a little bit. And that’s okay. That doesn’t crash the market or anything. There’s all kinds of stuff that they can do better. There’s a million great products people can continue to build on top of those foundation models. Even if the models don’t improve, like the products built on top of them can continue to get better.
But I think the kind of continuous improvement we’ve seen over the last couple of years might be hard to sustain. It might either plateau or go completely vertical within the next couple of years.
Greg Lambert (44:12)
Interesting. Yeah. we’ll see. Because I do think, you know, I listened to interviews. There’s one of the, guy that runs Anthropic that I listened to this morning. And he was basically saying that there, what did he, what did he say? a, in a finite number of time units, we are going to release this, this new model, but, cause they just released three, seven.
which was a step up and they’re saying they’re adding internet, which I said was a miscalculation on their part for not adding that in right now. But he was pretty certain that their four, he predicted would be a huge leap forward was coming out soon. So it’s going to be interesting to kind of see what happens and what that means if it’s
a significant leap or if it just means we’re adding that video functionality that we talked about earlier. That’s big leap, right?
Marlene Gebauer (45:11)
Mm-hmm.
Ed Walters (45:12)
Well, maybe my last thing can be very practical, which is I really do think that law firms and corporate legal departments have significant untapped data assets. And I think the KM departments are going to show amazing gains in the next couple of years. I think the combination of public data with private data.
is going to be amazing, maybe in Vincent Studio, maybe through our integration with iManage. But I think the combination of that proprietary, unique, differentiated law firm or corporate legal department data and the insights of the huge public data set, know, inside of vLex and Thomson Reuters and Reed Elsevier, if they open the walled garden, I think could be incredible.
And so we’re putting big bets there on the I-manage integration on Vincent Studio to try to build that next generation of applications.
Greg Lambert (46:05)
And Ed, while you were talking, I looked it up and apparently we did not ask you a crystal ball question the last time you were on. So, but I looked up, I looked up the time before, which was when you were on with Sonja Ebrom And you predicted that I would be wearing a Louisiana State University jacket at AA, double L and which was true. So you were spot on that.
Marlene Gebauer (46:12)
Didn’t? What happened?
Ed Walters (46:14)
So I got nothing wrong.
which came true. I’m
Marlene Gebauer (46:28)
And he was right. was right. He was right. See, he was right.
He was right. Well, Ed, thank you so much for joining us on The Geek and Review. It’s been really great having you on the show. And I think you’re one more closer to the tiara. He would. He
Ed Walters (46:34)
batting a thousand in the crystal ball.
Hahahaha!
Greg Lambert (46:48)
Yeah, you would look good in a tiara, I’m sure.
Ed Walters (46:52)
I would wear it.
Marlene Gebauer (46:54)
And thanks to all of you, listeners, for taking the time to listen to the Geek in Review podcast. If you enjoy the show, share it with a colleague. We’d love to hear from you on LinkedIn.
Greg Lambert (47:03)
Yeah, or Blue Sky. We’re on there too. Yeah, I need to start putting that in the outro. So, Ed, we’ll make sure that we put things on the show notes, but what’s the best place for people to reach out and learn more about what’s going on at VDLex or Connect with You?
Marlene Gebauer (47:04)
Or blue sky. Yes. Yes, I know I will.
Ed Walters (47:19)
You can find me on bluesky at EJ Walters and You can find all of this information on the vLex website at vLex.com forward slash Vincent and We have a ton of documentation there all the announcements and if you want to reach out for Vincent Studio beta@vlex.com
Greg Lambert (47:45)
All right, and is that just, is that anybody or is that current subscribers? Okay, all right, I know what I’m doing right after this call.
Ed Walters (47:49)
That’s anybody.
Marlene Gebauer (47:52)
Me too.
Ed Walters (47:52)
Hahaha!
Marlene Gebauer (47:53)
And as always, the music you hear is from Jerry David DeCicca who has dropped a new album. So go out and check it out.
Greg Lambert (47:59)
Yeah,
I ordered mine yesterday. So thanks, Jerry. All right, thanks guys. Bye.
Marlene Gebauer (48:02)
Awesome. All right,
bye.