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The Geek In Review
Max Junestrand and Ilona Loginova: How Cleary Gottlieb & Legora Are Redefining Legal Work
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- [00:00]
A
Hi, I'm Marlene Gabauer from the Geek and Review, and I have Nikki Shaver here from Legal Technology Hub. Nikki, you have some really important news about an agent's map, right?
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B
That's right. So some of you listening will be aware of our general market map for generative AI and legal tech. We actually just released our map of agentic AI products and legal. So anyone following along to your podcast, Marlene knows by now that agents have been a really hot topic in late 2024 into 25. And LTH has just had what we call our Agents Week, which just meant lots of different kinds of content dedicated, dedicated to this trend, including an excellent article by Stephanie Wilkins diving into the definition of agents, a timeline of major agentic announcements in legal tech, and our map, which shows already over 100 products in legal that now include some form of agentic AI. It's a lot.
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C
It is a lot.
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B
I know. It's moved very quickly. Access it all on www.legaltechnologyhub.com and look for it as well on LinkedIn. It's an interesting one to be able to show, especially if you're doing some strategic analysis of the market or want to show internally at your firm or legal department how things are changing and how quickly things are evolving in the market.
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A
Yeah, that's going to be an incredibly useful tool for everybody. So thank you for that.
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B
It's a pleasure.
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A
Welcome to the Geek in Review, the podcast focused on innovative and creative ideas in the legal industry. Marlee. I'm Marlene Gabauer.
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D
And I'm Greg Lambert. And this week we're exploring the intersection of legal practice and artificial intelligence with two real pioneers in the field. So we have Max Junestrand, who is CEO and founder of Lagora, and Ilona Logvinova. See, I knew I'd mess that up. Ilona Logvinova, who is Director of Practice Innovation at Clear Gottlieb. So, Max and Ilona, welcome to the Geekin Review.
- [02:21]
E
Thank you so much.
- [02:22]
C
Thanks, Marlyn.
- [02:24]
A
Yeah, we're super happy to have you on. I know we've been trying to schedule this for some time, so I'm glad we finally have made it happen.
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E
Likewise.
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D
Yeah, apparently they've been pretty busy.
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A
Yeah, you know, I think they have been a little busy, so. Because, you know, on May 1st of this year, Cleary Gottlieb announced a strategic partnership with Lagora. And Ligora is an AI platform designed to transform the way which legal teams collaborate, review and draft documents. This collaboration follows a successful pilot program in 2024 and aims to fully integrate Legora's AI driven services across the firm.
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D
Yeah, and Max, for just for people, listeners who may not be familiar with the work you've done, do you mind giving us some background about Lagora and what it's meant? What is meant by Logora being referenced as an AI first legal workspace? What does that mean?
- [03:22]
C
Yeah, I mean, absolutely. And I think me and Elona are also coming up on the one year anniversary since we started talking and got the partnership in place. So it feels fantastic to be here. I mean, look, we started building in the intersection between AI and law, pre GPT, I like to say, before AI was cool. And I guess it took a lot of technical sort of paradigm shifts to actually get the technology in a space where we could derive real sort of useful use cases and information from it. And in the last two years it's been frankly an exceptional time to build in the space. And the use cases and the things that we've built I think can be roughly sort of put into three main buckets. We built a general assistant that ties into a lot of different capabilities. We built a large sort of tabular review, scaled contract review system and then also plugin into Microsoft Word. And then all these three things come together in the platform. What we mean by collaborative is not only sort of collaborating between lawyers in the same team, but also with clients. Because I think this technology is drastically shifting what it means to actually be sort of a leading law firm in the way that you can provide value to your clients and also what it means to do knowledge work. And as you look to what kind of the future lawyers work will look like, I think that is a very collaborative space between both human intelligence and machine intelligence and freeing up what a lot of this sort of mundane, repetitive, low level tasks are so that you can do more fun things with the time you have.
- [04:58]
E
I couldn't agree more with that. If I can just chime in quickly. You know, our managing partner, Michael Gerson Zhang, is really forward thinking in these areas. And we actually wrote an article together, you know, some months ago, I think it was about eight months ago. And it was really about this concept of hybridity, right. This concept of the. The kind of convergence of human and machine intelligence and what that means essential, especially in the practice of law. And so Max mentioned that we just hit our one year anniversary. That's absolutely right. Right. So we announced this partnership recently, but we have been collaborating for some time in the background and behind the scenes and really the thesis around that is that we want to merge collaboratively, we want to merge machine capabilities and emerging technologies into the practice of law, directly embedding it into the way that lawyers work. And so, you know, Michael has been talking about this for some time. We're really excited to progress this perspective. And so this is an exciting step forward in that, in that journey for us.
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A
So let's take that a little further. Alona Clery has been very proactive in integrating AI into its operations, including the most recent acquisition of Springbok AI. So how does the collaboration with Lagora align with and advance Clery's broader AI and innovation strategy?
- [06:10]
E
Yeah, I love this question. So we have a multi pronged strategy in a very real way, right? So on the one hand, we are working with vendors and you know, I say the word vendors, I actually really don't like that word because I do see Max and his team as a partner, they're not just a vendor, right. And that was, that was one of the first things that really attracted us to Lagora is that kind of perspective. So we are working with providers of technologies, right, and forming partnerships with capabilities that are on the market. But at the same time we realized that to really advance and you know, to use the words of a McKinsey senior partner that I used to work with, you know, really embedding AI into the brain and spine of our organization, we understood that we needed to have our own data science capabilities internally. And what's really exciting is that it's not just building our own AI internally, right? That's matter specific or that's, you know, specific for any engagement. We are now merging those two prongs of our strategy. So Max's team can work with our Springbok team internally, right? For, for additional nuance. And that extends to our other, you know, our other capabilities that are available in the market too, where we are partnering as well. And really exciting because, you know, for, for, for those relationships where they are startups, right, and they're not yet at the growth stage phase, there is that ability to design, partner and do more. And even at the growth stage phase, right, there's that opportunity to do more with companies that are growing quickly, their capabilities are expanding. And you know, I have this perspective that we're looking at our partnerships sort of in the way that venture capital will look at relationships, right? It's not really, it's not just about choosing a, choosing a vendor, it's really about seeing where that company is going, right? And that's what we're Investing in, we're investing in the journey and the roadmap and the opportunity and, you know, the scope of what's possible. And so with that. Right. The opportunity to design partner is really powerful. And now that we have a capability like Springbok internally, that opportunity is magnified because we can take more advantage. So that's been really exciting for us.
- [08:14]
C
Just to add a little bit on that. I mean, I, from the very beginning viewed AI as almost like this vector on which you can compete on. And I think there are ways to do it phenomenally well and there are ways to do it not so well. And just in the short time that I've gotten to know both the sort of Springbok team from the Clery side as well, it's. We have the same capabilities and sort of tools, but the way that you leverage them are, can be vastly, vastly different. And I also think that there are many opportunities where it's like one plus one equals three, especially when you look to start to connect these systems. I think legal tech historically has suffered from a lot of silos where systems weren't as interconnected and there wasn't a lot of sort of, well, collaborativeness in terms of building the best user experience. And that's something that at least I've been sort of personally very thrilled about building together with the team.
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E
I'll just jump on that really quickly because Max has talked about this interoperability point before. So the collaboration and interoperability point, I think it was on a panel that we did together or a legal tech meetup hosted by Clery where Max joined the panel. And it really, really resonates with me. I think that really is the point to focus on right now because we're seeing so many vendor capabilities spring up. Right. We're seeing so many silos in terms of emerging capabilities. It is so important to figure out how it all works together on the strategist side. Right. It's really on the technical side and that's really where Max and his peers come in. And that's what's so important. So that, that focus is really important for us.
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D
Yeah, Ilona, I know law firms themselves structurally are at a disadvantage primarily because, you know, we're, we're a year in, year out budget. Yeah, there's, there's not like a, maybe a five year plan, but being a partnership, you know, it's really the legal part of it is just year to year.
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E
Yeah.
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D
And so having these types of situations where one, you know, one example, you bring in a group as A develop a development team and then you also then align these partnerships with your outside folks for. For this as well. I mean, I think a lot of us would love to have been a fly on the room, you know, fly in the wall in the room when someone first pitched this idea. How did you convince partners at a law firm to take this type of journey with you.
- [10:41]
E
Without revealing too much of the secret sauce? I will say what you're saying is.
- [10:46]
D
You had photos on everybody and they just had to come along with you, Right?
- [10:50]
E
Well, I will earnestly say that I give a lot of credit to our leadership team for having the vision to really appreciate how important this is. Right. And I think historically we see this at Clery, where Clery X was founded several years ago. And the perspective behind the founding of Clery X was to essentially understand that ALSBut are emerging in the industry as disruptors and we ourselves can have an organically developed ALSP that is part of our firm. Right. But also acting independently so that we can essentially discover that version of disruption internally rather than experiencing it externally. And I think that was an early demonstration of, you know, the forward thinking approach of the firm from a technology perspective. And then as the technology, the technology matured, Right. I think it really wasn't until this last year that we saw what Genai could really do for legal. And so once we started seeing it, which I think started happening last spring, really roughly around a year ago, when the technology started getting much better and really the accuracy started improving tremendously, that's where we really saw how powerful it could be as an embedded agent. Right. And what kind of accelerator and growth platform it can be. And so that was essentially the vision. Right. And understanding that other professional services firms, you know, also experience a similar arc. And their arc was several years. And we've seen this across consulting and across financial services. Right. Where they do have tech that's much more heavily embedded in the work that they do. And so legal, as another vertical of professional services, another sector in this space, that it just adds credibility knowing that historically other areas have other services have done this too.
- [12:31]
A
I'm curious, Ilona, how do you deal with sort of the constant newness of things that are coming out and basically staying committed, the path that you've chosen when, you know, when a lot of this new stuff is kind of thrown at you and you know, possibly even the attorneys and other people that are outside the team, you know, how do you manage that?
- [12:58]
E
I was talking to a friend in the industry yesterday. She's, she's. A wonderful thinker in this space. J. Some of you may know her. And she said, you know, change is inevitable, but suffering is optional. And I think that's so true. Right. And I just. I don't subscribe to suffering. I think that. I think change has to be a constant. You have to accept that. Right? And so, in the words of Wayne Gretzky, great Wayne Gretzky, you have to ski where the puck is going, right? So you have to go in the direction of travel, not just with the direction of travel. And that's always the perspective that I've tried to take in this space. And again, our leadership team, I think, has a similar approach. So if you're thinking about it that way, right, if you're going towards where everything is headed, then there's really no friction because you're in the same. Right. You've got tailwinds, and you avoid the headwinds. I think the headwinds come when you're trying to fight something that is coming and you're trying to sort of resist it. And that's the challenge with innovation, when there's resistance towards something that's coming. But, you know, if you're really trying to get ahead of it. And this was the case in my last role, too, at McKinsey. Right. We were always trying to think, stay ahead of the curve. We were always trying to learn something new every day and trying to understand and digest things that were around the corner. That was actually the motto of our team. Try to look around the corner every single day. Then you can really just get comfortable with being uncomfortable all the time, and then it's all great.
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C
You know, I was thinking just.
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D
Just real quick before we forget about Jay. Jay was on our show, I think, 300 episodes ago.
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E
Yeah, there we go. Yeah. She's an OG in the best way. Yeah.
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D
Yeah. Sorry, Max, go ahead.
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C
No, that's messy. No, but I just wanted to say, I mean, Alana, we've also had a lot of conversations around this from. From the. Both, I guess, technical perspective, but also adoption perspective. Because, Martin, I think what you're touching on is not only is this sort of, you know, technical prerequisites and, you know, space changing almost every month. So is, you know, how we equip our lawyers with the best technology. And I think we even had the situation where I think we ran out of Zoom seats because there was a Max cap of, like, a thousand people who could be on the onboarding call. And so we probably made some. We made some extra money for Zoom Because Cleary had to upgrade their, Their, their license.
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A
That's got to be a first. That's gotta be a first.
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C
I think that was the first. That was the biggest.
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A
So many people wanting to be on a zoom call.
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C
Yeah, yeah, yeah.
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E
No.
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C
And I think from a technical perspective, we've also tried to look across the corner all the time and you see things like MCP and sort of agents finally becoming. How should you put it? Production ready. And to relate that back to our latest product release, which is workflows. You could build workflows in a hundred different ways. And I think there's a way to build it that would have made a lot of Sense back in 2015. And there's a way to build it that makes a ton of sense for 20, 25 and ahead. And I think there, we've at least been willing, and I think clearly as well, given that they sort of picked to work with us very early on to take some bets on where the puck is going. And as that then starts to unfold, it's easy to pat yourself on the back, but then you immediately start to get hungry for, you know, what's next. And how can we be even more ambitious here? Because I do think that this is also a question of ambition. You can say AI is something we're going to do. We're going to check the box and we'll have a talk track for it with our clients. Or you say this technology is like fundamentally going to change the business of law. We're going to lean in and transform the way we do business. And that's what we've seen in this case.
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E
Just add to that too really quickly, Greg, because I think this is a really important point, and I get asked a lot about the process for the selection of vendors and what the, you know, sort of what the calculus is and how we identify vendors that we work with, the ability to navigate what's next and to embed that into the readiness of the work that you're doing and really into the data science. That is an enormous part of our calculus in terms of figuring out who we work with. And this impressed me early on, you know, when we started discussions with Agora, just understanding that they are always very eager to look at what's around the corner and build that in. And I think when you're dealing with AI, I don't see how you can evaluate something with more important focus or priority, because AI is constantly improving. Right. And so that has to be built into your analysis.
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C
I guess the thing you, I guess the thing you want to pick for is actually the slope and rate of change, because I think it's really easy to say that, okay, we've got this graph and you're going to pick on the Y intercept, but if you. If you zoom out a bit and you actually see, oh, here we've got a curve which is, you know, exponentially increasing, that's probably the way better bet. Just to Elona's point around earlier, about picking, like a VC fund, you want to pick the startups with the highest growth, not necessarily the highest, you know.
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E
Yeah, excellent, Clay.
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D
Yeah. Well, I want to extend the sports metaphor just a bit and borrow from Mike Tyson, which is, you know, everyone's got a plan when they enter the ring and it all goes out the window as soon as you're punched in the mouth. So I wanted to talk about you, Max. You had talked about the workflows and the agentic AI framework that you set up. So, Ilona, you know, as Cleary begins actually deploying this, so it comes off of, you know, the drafting board and actually into production. How do you take a look at that and balance the, you know, hopefully the efficiency gains, but also maintain that lawyer oversight and watch out, you know, make sure that you're also compliant as well.
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E
Yeah. So this is a big question, right? And it encompasses a lot of different. A lot of different parts of the firm. So I think, first and foremost, as an AI lawyer, right, this is the first time in my career that I'm not practicing, but I'm coming from a background of being a technology lawyer and thinking about governance constantly. Right. And AI governance infrastructures. Responsible AI is really important. It should be a co pilot. It should never be a replacement. But I also think of this in an anthropomorphic way, right? Just humanizing AI. So the way that we're leveraging AI, the way that we're working with AI, it should be no different than working with more junior associates, Right. Or anyone that we're overseeing in the matter. Of course, when we're working, we should always be exercising proper oversight and especially as we get into the realm of agents. So I love that you brought that up. Right. I think the future. The future state thesis is that essentially everyone will, can and should be a supervisor to a series of digital agents who they're working with. Right. So everyone, in effect, will have a supervisory role, and those will probably, probably be hybrid teams of digital and analog workers. Right. Digital and human workers. And so we will have to just constantly be exercising that supervisory oversight. And we are trying to embed that as, as a practice as much as we can across the organization through learning and training. And upskilling it will have to be, you know, it's, it's change management. But I also think it's just a point of evolution in the way that we practice and in the way that we approach our work and how we see technology as a partner in the way that we're working.
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C
And I think to add onto this, LLMs actually allow us to check work at scale. So before you used to have the staircase of like, okay, you know, the junior associate reviews it, the senior and then the partner, and then it goes out. But what we've started to do to a very large extent is build out evaluation data sets, so evals where we actually check the performance of a workflow on an historic deal, for instance. So you have the input and then you have the sort of manual created output from the last deal. And then you allow a system like Ligora to generate an output as well. And then you compare so the old human created output versus the Legora created output. And you can use both a human and an LLM as a judge to score how good the AI generated output is versus the traditionally made output. And you can run that test hundreds of times on each use case to see a very clear pattern in terms of accuracy, precision, and recall, which I think gives a lot more confidence to taking these use cases into live deals and into production. And here's also where I think that there's a huge opportunity, and me and Alona and the team have seen this already, for outside teams and firms to collaborate much more, because what you don't want to have is teams like us relying on open data sets that doesn't have anything to do with the real work that elite law firms are delivering.
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A
I wanted to maybe go a little dive a little deeper into the weeds on the workflows and. Because, you know, I wonder how that, that, that is going for you. Because, you know, oftentimes when you're breaking down workflows, you know, oftentimes the people whose workflows you're, you're trying to, to mimic, they're not even aware of all the little micro steps that, that take place. And so I'm curious, you know, if you've experienced any of that and how that, how you've, how you sort of dealt with it.
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C
Yeah, well, I'm very opinionated about, you know, how we've built it versus how I think you shouldn't necessarily have built it. So the Workflow automation has existed for years. There's a ton of great open source frameworks, including N8N, for instance, where you kind of have this input box which has a little arrow, and then the output of this box becomes the input of the next box. And then you have conditional statements, so if them, et cetera, and you tie them together with a bunch of APIs and different capabilities to create kind of very well followed custom instructions, if you will. And I think that was the way that you built things before you had LLMs which could handle issues. So as issues come up on the fly, they're able to take, you know, well informed decisions. And so the way that we thought, you know, let's build workflows, they're much more of a sequential instruction to an LLM that then gets to break down the task and say, okay, Marlene, you just told me that you want me to first read through all the documents, then extract the meaningful terms, then run a risk analysis based against this company's historic data and write me a report. So it's like a four step thing you want me to do. And then the LLM or the agent has access to a planning layer and an execution layer. And so it kind of creates this plan and then executes on that plan. And what you basically have is you have an LLM that's calling on a bunch of tools in the correct order. And the exciting thing is you can even give this agent access to a tool that's called Ask the Human for Help. Right. So if the LLM is unsure, it can prompt you and say, hey, Marlene, I'm not sure what I should do here. Could you give me some input? And then you guide it in the right direction. So it's, to Elona's point, much more of a supervisory role that the lawyer and attorney takes on in terms of guiding the LLM to do the right work. And as you build, you know, one workflow like this, it might take a couple of minutes to run, but you could also build them, you know, quite large, which means that they take a longer period of time to run. And if you include things like deep research, which sometimes takes you out minutes, you could totally imagine a world where instead of sitting up till 3am Sort of crunching the late, you know, the last data room findings, you just kick off a couple of these workflows when you go to bed, and then you wake up in the morning and then, you know, they come back to you with all the responses. And this is a drastically different take on how to build this than some of the alternative solutions in the market.
- [24:53]
D
I don't know. I know these lawyers. They're still going to be up to 3am doing something else. They're going to fill that time.
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A
I want to switch topics a little bit and start focusing more on funding. So, Max, first off, congratulations on the May 21st Series B led by Iconic and General Catalyst, bringing your valuation to 675 million and adding some board members. That's great news.
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C
Thank you very much.
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A
Absolutely. So how do you think this funding is going to accelerate your product roadmap, you know, especially with the new workflows and you know, how are early adopter films like adopter firms like Clery involved in shaping those features?
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C
Well, I'll be very honest. I mean, we raised 35 million the year before and I think we had only spent about 5 of that, so we were already running at maximum pace. But it was a good time to raise more fundings and we really wanted to bring both Iconic and GC on board. I think they're great partners. I think to Alona's point earlier, like, the. This space here and the amount of things you can do is just enormous. Like you've got this universe almost stretching out ahead of you in terms of things you just want to go and build. And so when you raise money like this, you start to think, okay, can we be even more ambitious and instead of settling over here, can we maybe go out and build an entire feature set around that? And I think that's what we started doing with things like workflows, where instead of building the. Because, look, the way we build workflows is not the local maximum of today. If you want to maximize the performance today, you would actually build it in a different way. But it totally maximizes the output of the LLMs within this framework for where the development of the LLMs are going. So as soon as a new model comes out, it actually drastically improves everything we have. And as you expand the number of tools that our agent has access to, it can do even more interesting things. And it sort of scales very exponentially to the point you said around like co designing and actually building things together. I think it's both my biggest blessing and curse that, you know, I don't have a legal background but a technical one. And so you're very naive to the fact that I know how to bring this technology into market very well. But all the nooks and crannies we need to figure out together. I'm not the type of product leader that goes into a Dark room and comes out six months later with this sort of eureka idea, but rather it's, you know, talking to Elona over lunch and saying, hey, we've got this crazy idea about connecting Ligora to Outlook and we think, you know, we think we're going to build it in this way. Can we make an MVP and throw it out to a couple of lawyers? And working with firms like Clery, where you have frankly a quite large group of fee earners who are so interested and who are leaning in to the point where as soon as we give them something, they ask for more and they push us to ship, develop and keep that really high velocity. We get the most energy out of building things that gets used and that solves problems. And I think adoption has historically been a large problem in law firms when it comes to tech. And frankly, we've not seen that as a problem, at least within our work so far.
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E
Yeah. And I think that's a testament to the ease of the technology. Right. And the way in which it works. I always say, you know, if it's not Instagram, I don't want it. And what I mean by that is, you know, I don't think anyone ever had adoption issues with Instagram. Right. If anything, people can get to it fast enough and that's because it looks and feels good and there are features about it that are attractive. And so you're, there's a stickiness to it and you want to go in and explain how to use the filters and how to figure it out. And I think similarly we've seen that with Lagora. Right. People want to be in the platform, they want to explore and they want to understand how to use it in their workflows. And it grew very organically and the rollout has been very successful so far.
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D
Well, speaking of that, I know, Max, that we talked a lot about the workflows, but you've gotten quite a bit of praise for having a very user friendly ui, as Alana was pointing out. And you know, you've. And it's not just Clery that you've won over. You've had other firms like Goodwin that you've been working with as well. So how do you kind of pull together the success stories, the return on investment emerging out of what you're doing with these firms in order to pitch to the next firm?
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C
Well, I think to your earlier point about design, it has to be Scandinavia Design. That's the answer to all our success. Right. It's our entire engineering and product team is based in Stockholm. And so, you know, I can't give them enough credit for making my job really easy pitching it. And I think to the point around roi, there's a lot of different aspects to it. Right. I think the first thing, if we agree that AI is a vertical that we're going to compete on, and you'll have some firms doing it incredibly well, and you'll have some firms not doing it so well at all, and getting to the point where you're playing in the major leagues, that's going to take investment. And it's really simple to take a specific task, see how we can transform this task using LLMs, and make some calculation around time saved or turnaround improvement or quality improvement. But it's hard to do this across every possible task that AI can solve across the entire firm. And so I do think you need to be quite controlled in the sense of how you measure this when it comes to actually driving this back to the business model. We're for sure seeing an increase overall in terms of fixed fees arrangement and also saying, here is a $300 million budget and we wanted to deliver as much work as you can within that bucket. And then it's kind of up to the firms to be as efficient as possible, because if they're efficient, they actually make a higher margin. So I think the way that AI is going to play out in big law, we're only seeing the sort of early, early days of it, but it's for sure not stopping. Right. And when it comes to working with more kind of leading firms across the. Across the globe, we've had a very clear mission from the beginning. And it's to what Elona said earlier, like, how do we combine machine intelligence with human intuitiveness and drive? And I'm not sure if I've shared that in a podcast before, but the founding reason for Leia, as we were called back then in the very early days, was actually a lawyer friend to one of the co founders who spent, I mean, first of four years studying law, and then four months during a summer just summarizing Swedish court cases. And that wasn't why he studied law at all. And so I do think we have this huge difference between where we are and where we want to be. And I couldn't be more sort of thrilled, passionate, and just excited about getting to build in this moment in time because it is a paradigm shifting.
- [32:12]
A
Alona, I'm very happy to hear that everybody's very excited about the AI solutions that your team is bringing to the table. And everybody wants to try things. But I am sure that there is work and strategies behind the scenes to get people on board. So what are some of the strategies that Clery's employed to ensure sort of that seamless integration of Lagora's platform across the different practices and regions? And how do you measure the impact on client services?
- [32:51]
E
Yeah, these are all big questions. I mean, I think the answer to the first is really easy. Adoption was very easy for us. It showed early success, right? Our pilot was small.
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A
It seems to be so different than what you hear from other places. So that's why I'm like, there must be something you guys are doing.
- [33:07]
E
Secret sauce. Yeah, I think, I mean really, the. And this was my belief, you know, coming in the door last year, I think you have to start with the high value scalable user cases, right? So when I came in the door and we were forming our strategy really last year, a few months earlier than where we are right now, it was about what brings the most value to the most lawyers across the firm, right? To the greatest number of colleagues across the firm. And the answer had to be a broad based chatbot like functionality right at the time. And use cases expanded from there. And so a broad based platform had to be the first answer. And from there you could address more so specific verticalized use cases that are high value for certain practices, but maybe not for others. And so starting with a very simple thing, right? If you look at success for Google, right, Early success for Google, why was it so successful? Because the only thing that you can do on this webpage is just search, right? There's one bar. And this was Marissa Mayer's genius at the time because there were so many complicated tentacles in the back end in terms of, of how the tech worked and everything that it did. But the front facing UX and ui, right, was just one search bar where the only thing that you could do is the thing that you had to do, which is just search and type in a question. And so my ingoing thesis was you have to make it easy, you have to make it accessible. It has to be pretty, it has to look and feel good. And I remember when we had, you know, when I reached out to Max and we had our first demo, it just, it looked and felt good, right? And it's a very simple analysis. But I practiced as a lawyer for very many years, right? I know how hard it is and I know that this is a grind. This profession is not easy. It takes focus, dedication, commitment, right? A lot of stamina and a lot of Self discipline. And so having something that feels good is really, really important. And injecting humanity into the way that we're practicing is really important. And so I started from those very basic principles. And so for that reason, bringing something in that was aligned with those principles, I think enabled that success. And we saw that early on that, you know, with something that felt like chatgpt or felt like Google and felt good to use, the adoption was easy from there. And of course, you know, we have other tools that we're bringing in the door. And with Springbok, we're working with AI, you know, in different ways and building more bespoke solutions. But the idea is similar, right? It has to be of value and it has to be accessible. And I think starting with something where you see early success also enables that trust with AI because there is, you know, some level of trepidation there, right? This is, this is new. So you have to start with something that is just much more accessible than, you know, much more specialized solutions. And starting there can then enable that journey onwards towards the more complicated solutions. That's, that's really the answer there. And in terms of how we're measuring success, I mean, we're working a lot with usage analytics, right? We're analyzing on the back end, we're doing a lot of practice specific enablement, a lot of specific sessions across the firm. And Lagora is a phenomenal implementation partner for us. Right? We're doing a lot of sessions together and you know, we, we do a lot of sessions together around the world in terms of our teams and just making sure that we are equipping our teams with, with what they need to know, answering questions, right? We're tracking usage analytics on the backend. We know who's using what and where. I also give a lot of credit to our infosec and Risk team, who helped us set up a lot of kind of the infrastructure on the back end to allow us to, number one, acknowledge what that data is. And the Lagora team built it for our specifications and then we can then understand that data and leverage it to get even better adoption.
- [36:49]
D
Yeah, one, let, let me pull on the, the measuring of success thread here just a little bit more because success may mean different things to different people. And so I'm just wondering, how do you actually create so that, you know, okay, now, now we've implemented a workflow that has cut, cut down the work in half. But how do you do that success without having the detriment against being ahead of the game that, that May not be a matter that the attorney wants to cut the time in half or. And then the client may also have a different measure of success. So how do you kind of pull everyone together so that you understand what it is that the goal is for the firm in implementing these types of tools?
- [37:39]
E
Yeah, that's a really important question. And it comes up constantly. And I'm so happy that you asked that specifically, because really, the value proposition of embedding AI is around data level. The human mind can only process and analyze so much data at a time. But. And it, and it's finite. But AI is infinite, right? In its capabilities, or, you know, finite, depending on context, Windows and processing and things like that, right? There is, there is affinity to it. It's not infinite, but there is a much broader spectrum across which you can measure and evaluate data. And so that, that perspective is really powerful. That through embedding AI, we have a much broader spectrum of data enablement by which we can analyze our advice and really enhance the client service that we're providing. Because take a corporate deal, for example, if you're analyzing the last 4, 10, 15 precedents in a manual way, that's very different than analyzing or reviewing those 50,000 precedents or whatever it is. A thousand precedents, 100 precedents, that's just a much bigger, broader spectrum of analysis that you can do. And then the human expertise can be that much better, that human expertise layer. And that's the value proposition for our clients. So, yes, we are moving faster, in a sense, by embedding AI, but we are also enabling a broader spectrum for analysis. Right. And critical thinking and really thinking about what is the best result for our client, because we are incredibly client centric. For us, this effort is all about our clients. It is about client delivery, making sure that it is best in class. Right. And leading with the emerging standard of excellence, which we believe is necessarily embedding AI. But that, that's the whole exercise. And you know, historically, we've seen, we've seen tech that makes things go faster, right? Email is very different than snail mail, right. Or writing things by hand. And we've seen that evolution in the legal industry over the last number of decades, but the work has not decreased, the work has increased. And I think what we'll see over the next few years is that everything will start to move faster across the board. Processing speeds will be faster, analytics will run faster. Right? And so we, we just have to figure out how to calibrate to that change while leveraging the right amount of data. Embedding AI and providing the best in class client service. And that's what we're working on every day.
- [39:59]
C
Yeah. And I think in some ways to maybe add to that, I'm over the take that every piece of work that AI can do, it will do. And so if you sort of think about the axis of complexity, we're at a low level today, but this is increasing. And I think here the positioning of being, you know, an elite leading law firm in a lot of different practices actually sets you up quite nicely to leverage this technology. Because AI is not coming for the sort of full end to end antitrust matter, but it's coming for simple work or pieces of tasks within a broader ecosystem of a delivery. And here I think we got to recognize that you got to be quite process minded. And I think both me and Alona have a background at McKinsey where you often come in and you see a process and you say, okay, where in the process does AI have the biggest uplift? Let's go deploy it there and let's sort of snooze a bit on the low leverage use cases because that doesn't sort of swing the deal here.
- [41:05]
A
Well, Max and Alono, pull out your crystal balls because we've come to the end of the interview for the crystal ball question. So we usually say in the next couple years, but it could be less time than that. If you think that that's the case, you know, what do you feel are the major changes that, you know, you think are going to happen in the legal tech landscape and you know, how are your organizations preparing for those?
- [41:32]
C
I'll go first. So I mean within the legal tech ecosystem, let's stay there. I'll bring it back to this idea of the silos right today when you open up your phone, you probably use five apps every day and not that many more. But the number of legal tech tools that we expect lawyers and attorneys to leverage are ever increasing. And I think you'll see a huge consolidation, maybe not in businesses, but in UIs. So instead of having to go to every separate piece of software to deliver a small piece of work, you will leverage agents and LLMs and software to go into these other pieces of software, connecting to them and deliver a more end to end piece of work. And I think this is happening faster than what many people think.
- [42:28]
E
Yeah, I agree with all that. This is actually my favorite question. I love this topic so much, the futurism piece of it. So I think it's two things. I think it's AI, nativity right to Max. I think things will start to be AI native in the sense that AI will start to move from the front end of applications, of programs, of tools, right to the back end infrastructure as being a core driver and engine of those tools. But I think from there it gets much more sexier and much more interesting. And we haven't quite addressed this directly yet, but I think it has to be thought about, and I'm certainly thinking about it. I just saw in the news that the first screen free laptop has been introduced. So essentially a keyboard with just goggles, right? Or glasses, where you can essentially use your goggles as your UX and digital environment. And that is so cool because this constantly think about the fluidity of moving from digital to analog and back and forth, right? And I think from an internationalism perspective, a hybrid perspective, right? From being able to experience your digital environment more closely, being connected to people on Zoom, right there, I think we're getting much closer to just interconnectedness, collaboration. You know, there's so much that's coming by way of technology that will enable collaboration, you know, and just acceleration in the work that's being done and the way in which people are working and the way in which people are interacting with technology that it is just phenomenally fun to think about. And it's not just about thinking about it, Right. It's about engaging with it because we have to understand that the this is coming. And so what does that mean for the future of work in terms of workspaces? Right. How are our conference rooms going to be set up? Is it going to be a table in the middle? Is the whiteboard going to be on the wall? Or is there going to be something in the middle of those rooms where we can experience something in the middle altogether? Because we'll all be wearing goggles in that room and interacting with people across the world. Right? So all of these things that we can think about that feel futuristic and like we're in the Jackson, but it's actually maybe like 18 months away or two years away or even less than that. And that is so, so interesting to think about. And I think we have to start thinking about it now because it's already coming.
- [44:34]
C
Will Cleary be the first firm doing a transaction in goggles?
- [44:38]
E
Is that a. I mean, you know, we'll have to see. I'll keep you on the edge of your seats, but, you know, nothing's impossible.
- [44:46]
D
All right, well, Max Junstrand and Max from Lagora and Ilana from Cleary Gottlieb I wanna thank you both for finally connecting with us and doing this interview. This has been fantastic. Thank you.
- [45:02]
A
Really good.
- [45:02]
E
Thank you so much. Thank you for having us.
- [45:04]
C
Thank you very much, Greg. Thanks, Martin.
- [45:06]
A
And thanks to all of you, our listeners, for taking the time to listen to the Geek in Review podcast. If you enjoy the show, please share it with a colleague. We'd love to hear from you on.
- [45:15]
D
LinkedIn and Bluesky and Lona. We'll start with you. We'll put links on the show notes. But if listeners want to learn more about CLE Clear Ex and the innovations that you're doing there, where's the best place for them to look?
- [45:30]
E
They can certainly look on our website. They can also reach out directly. I'm very happy to follow up.
- [45:36]
A
And Max, if listeners want to learn more about Lagora or connect with you, where should they go?
- [45:43]
C
We're available@legora.com and my email is maxegora.com we are hiring a lot of lawyers across New York, London and Vietnam.
- [45:53]
A
Everyone.
- [45:54]
C
So if you're an attorney who wants to move into the legal tech space, we'd love to hear from you. And it's frankly the most exciting of times to be building in this space.
- [46:04]
D
It's a bonus for the listeners that stuck it out all the way to the end.
- [46:10]
A
And as always, the music you hear is from Jerry. David Jicca. Thanks so much, Jerry.
- [46:15]
D
Thanks, Jerry. All right, thanks again, everybody.
- [46:19]
F
Had to go to bars the salt of the earth on the way to a hood set the devil's bashful bar hey, hey, don't take me away I could walk home by the North Star But I fail to notice that still daylight time the devil's back on ball the devil's back on ball and the devil's back from the ball.