You're on a bit of a heater, huh?
surged, but you face really intense competition. Let's go right at that to start.
“If you were building a global financial system from first principles today, you wouldn't build it”
on 50-year-old legacy rails. You'd build airwlocks. One AI native platform for global accounts, cards and payments is designed to make the entire world feel like a local market. Others are bolting AI onto broken infrastructure. But airwlocks was built for the intelligent era from day one. Stop paying the legacy tax and start building the future at airwlocks.com/all-in. Airwlocks built for the future. 350 million in what? Two or three years and I'm hearing numbers five or six hundred
million now. Tell us about the revenue ramp of the company from the moment you release the software today. The products been in market for 40 months, 50 months, you tell me. It's put on. We started company 20-way too. First year was all about building the research and the product to really kick-start a work. We built the first a text to speech model that finally could sound human.
Release it in 2023 beginning of 2023. Then it took us roughly 20 months to get to the first 100 million
“in ARR. Roughly 10 months to get to 200. Five months to get to 300. And that's how we close”
end of the last year and now we are at the 100. You're at $600 million in revenue. This is extraordinary. How many employees now because the company is obviously hit incredible valuations? But you have to fill in that valuation and you're competing at a very high level for talent. So tell us about how many employees you have now and how you maintain the culture of the company when revenue is ripping. Investors are throwing money at you showing up at your doorstep. I'm
quite literally, but you've got to run the company. You've got to build a culture. So how many employees now and how are you dealing with these competing priorities? That's the key element of
how you offer us the element of how we maintain the culture despite the quick growth is critical
and how we optimize both the interview cycle, how we are bringing people in board, how we onboard them with 600 people today. So also very quick growth on that people side. And as a company, we combine research and product. So we are building a communication platform for AI on the research side is in with everything across audio, generating speech, transcribing speech or creating speech for interactions. On the product, this is how we can complete the entirety of the customer journey
from marketing and creating assets and localizing them internationally through customer support voice agents to proactive enablement of how voice agents can help in operations, training and sales. So this requires a lot of different talent and a part of that revenue growth is actually reflection of the functions we've grown over time. So from the original team, very research, very
engineering-heavy. From the first 10 people, we had zero nutrition. Everybody is still at the company
from those core research and engineering talent building together with us. So far, we enable
“taught a company and I think the common thread and credit to my co-founder who is incredible”
researcher himself. We've been able to assemble the team that is truly excited about solving audio, solving interaction and building that research. And if they are looking for an opportunity out there and looking for a company to join and solve that we are one of the leading of the leading place to do that. And you started before AI was so impactful at making software, right? So when you were starting four years ago, five years ago, and working on this, building software
was limited to low percentage of the population of planet Earth. You know, a number of people could write code. And now here we are, you know, when from vibe, we had a no code moment and vibe coding. And now we actually have people building production code who are not developers. You have developers going 10x and token maxing. How has building software changed internally and how do you deal with making sure that the code is really high quality because people are paying you this money, but they're
going to demand really high quality product since they're spending so much money with you. Yeah, it's also true that 2022 was still the year where topics of the day were crypto and metaphors. So the building there was also the best time to start because we could actually take a little bit of time to focus on what we thought is the future. But then the way we are structured is a lot of small teams, especially across the product engineering, but also in how we think about
go to market up to my specific industries, the alcohol financial services healthcare. So every unit
Is very tightly knit together.
people teams that that that run ahead. And inside of each of those teams, the decision we took
“which is slightly different than how it's usually structured, we embedded engineers in in every place.”
And even in the places which aren't engineering, so our talent team will have an engineer, our legal team will have an engineer, our revenue engineering or go to market engineering, have engineers embedded all across. And those people have tools. One is, of course, creating automations and bringing the software inside of that team. But second is actually helping everybody else do what you said, which is make sure that people are adopting AI, but also there's a security
check for everything they deploy. Because ultimately if you're not using a lot of the coding software, a lot of the co-working software, then you're probably in the wrong spot if you're using too much of it, that is also a flag because you maybe are not doing that in the right way.
And of course, as you start bringing that into the sites of the organizations that never were
exposed, they frequently can create, but not necessarily review whether that's actually doing behind the scenes all the secure ways or everything. So that's an essential role in the in the company. Yeah, we the it's fantastic that everyone can build software until you put it into production and you have a leak, or that person leaves the company and people forget they built that software, and it's just deprecating on its own. The other thing that seems to have changed is management.
When you had 10 developers in your pod or six, you had a UX designer, you might have a pure graphic designer, you'd have a product manager, they rolled up. And then suddenly, you know, we watched over the past three years, oh, hey, this is pretty good at summarizing what happened on the call. Oh, it is actually creating action items, and it's telling us what to do next. Oh, and it's, you know, doing all the different stories in our con bond board, and
“now how do you think about product managers and management as the CEO and as the co-founder?”
Yeah, we, we, so we don't fire them all, right? We don't, we don't have any pms. Right.
Did you ever, or did you have never, you never did? I've never did. Thought it's, it's a little bit
of what you mentioned. I also before the true AI impact started. It was ideal person in that role, can code, can understand the customer, can understand the design. Of course, that's very hard to find. There is no truly that many people that are experts in any, all of those fields at the same time. So we optimize for profiles that are experts in all these, one of those fields, but understand at least one other field really well. To your point, what we are saying now, there is,
if you can do a little bit of all with AI, you can maybe step change from being an amateur to being a advanced level, maybe not an expert level. So suddenly, you are not bottlenecked on all the other functions to do your work in, in growth, phenomenal fire. We grow for engineering, the present can design experiment, ship an experiment, it's working and bringing it back. We also have the privilege where we are using a lot of our product ourselves.
So to be able to do that, ultimately, to help everybody else create voice agents. We ourselves
need to create voice agents too. So you're seeing that also in the non-traditional functions,
“even go to market, like you need to be able to create a version of that. If we are offering that”
to the customers too, and then we do, we created our inbound AI as the R agent that's in addition to the form that you fill on the website. You have an agent that you can call and people are, of course, you can give all the information a much easier and quicker way. But the second thing that happens is people also leave a lot more information, so you can get connected to the right problem and write personal a lot quicker. So we are seeing that kind of
phenomenal the time where actually using a lot of tooling makes you yourself better in your job overall, and in our specific tooling that we are solving for us. Yeah, it seems like the use case of calling on the phone and talking to a computer or previously going through voice gel, and it was incredibly arduous and painful and annoying. It made you just say operator and hit the zero button, like as fast as possible. But now it seems to have turned a corner where
talking to a human, I almost feel bad talking to a human where I'm like, "I am so sorry. I'm wasting your time with this." And the AI is just so much more precise, and the fidelity is so great that when you tell them what you're looking to do and you cut them off, you don't feel bad. You don't have to make small talk. Is that what you're seeing in your customer base in terms of the ability, in real time, to interrupt the agent, to interrupt the conversation, and just move
faster, has made consumers and companies basically embrace the technology? Yeah, it's slowly becoming that you will be asking for, "Give me an AI, agent effect." Give me an AI operator. But we are seeing
A transition where suddenly, the biggest fuel of the recent growth for us is ...
team, just doing incredible work, but then finally the product combines the reliability that's
core with the orchestration for a lot of the AI models. But also the knowledge and the integration
“to provide you the right experience. And yeah, I think it was a step-tension in the last 12 months”
and especially in the last six of how good that experience became. It's like this golden ear of consumers out there, customers, and anatica customers is coming where you're going to actually open their website and call an agent and have the agent have information from your past interactions and deliver that help. And I think we'll see this kind of interesting phenomenon combining your previous question in this where now, of course, you are reaching frequently when you have
a problem and you're asking for help. But ultimately, the whole interface will change and more
depending on how you are operating with that end-frame interface with voice being helping you in the
background find that information. It'll shift from reactive to proactive to help you get that help before you potentially ask for it. And we are seeing those examples, those examples do. It seemed to be that speech to text had a major blocker. Again, in fidelity, 10 years ago lawyers
“would put on drag and dictate if you remember that terrible software they're going to headset.”
And it seemed like the big blocker was, you felt like an idiot talking to a computer in an office, right? And so people who did quietly in their office, you know, they kind of got away with it. But now we see something very different. The whisper in the office, people very quietly talking to their computer, giving it a prompt, and talking to their agents, and now there's a ring out, you can press it. And I use a really cool product called whisper flow. I don't know if
they use 11 levels on the back end. They use, and then if you utter as well, they are doing phenomenal work. The whisper flow is just a tremendous product. And then I got a pedal. Does anybody here use a pedal on their computer, raise your hand if you're a there's one door, a few doors. Any others? Raise it high. Oh, she's half-dork. Okay, so there's about three and a half dorks here. Next year, this is going to be, do you have a pedal? I don't, I have, I have, I have,
you considered a pedal. I should consider a pedal. I love the devices that you can wear, and it's when I have the plot. It's in creative. Flood, pocket, phenomenal, like, so good. And especially in events like this, I feel if you're pre pre-empted that you're recording, of course.
But how incredible would it be to all the signal and the conversations that otherwise is a period,
maybe top, top few notes here and there to try to get signal afterwards, if you can just have that automatic refill, your specific notes and make sure you're doing your follow-ups, phenomenal. All right, so let me make the case for the pedal. Okay. I have three pedals under the desk,
“and I think we're trying to figure out what the company is, but with whisper flow, you press down,”
it turns on, and you talk, and then you let it go. And one of the annoying parts of working with an LLM is typing, and you're kind of like exhausted when you're giving it the prompts, so you stop prompting. But if you're a professional bullsh*t artist like me and a talker, this is like incredible, because when I press the pedal down, I just give a stream of consciousness now. And it turns out what these LLMs actually do really well with is taking a massive stream of consciousness,
where you just keep talking and talking and talking, so I'll give it a one to two-minute prompt, then I let go, and it has changed everything. Everything. It's, you know, like the whole experience is changing so much. It's similar version of what we see happen is, you know how you have, you want to say a thought and then you're like, okay, I actually want to change and say something else. And now you have those two context combined, and the experience you get us an answer is so much better.
Yeah. So we already see that as an experience, but even the previous example of, like people are adjusting how they speak to AI versus how they speak to human, people are... How so, yeah, how should you speak to the LLM? We saw Sergei Brent say threatened it with bodily harm. It's a very effective technique if you haven't tried it, but what are the things that are different when you're talking to the LLM?
The specific emotional example, we work with a lot of financial services companies, Revolut, Clarnau, Pagbank, and some of the frequent case, not all of them, of course, how you remind people about payment or that from the people that aren't answering, and frequently people would naturally feel ashamed of telling the real situation. With AI, people are much more open to share what actually happened and give the information,
and suddenly this emotional block of like in front of other human,
I don't want to be able to say all of that is very different.
Usually people are more snappy with AI, voice agent, it's like quick responses.
Yeah, you don't mind cutting it off. Exactly. So you're going to kind of go through to the point
“you want much quicker, which you need to change a little bit of the interaction model too,”
which is working, but we'll look in the panel and whether or not we should talk a little bit about celebrities on the platform. You have some celebrities who are on there. You also have an issue with impersonation. I know this because somebody was like, "Oh my god, I love your bulldog videos. Many people know I'm a big fan of bulldogs. I currently have three." And I said, "I'm sorry, I don't know what you're talking about," and they sent me a channel
where somebody had created a bunch of dogs telling jokes, and they made one. And I guess they were looking for a podcast, or so they used the this week in startups archive and 11 lab to create my voice and do this huge channel, and I contacted them and I said, "Oh my god, it's very flattering. How did you do this? This is like a year or two ago," and they said,
“"Oh, I used 11 labs." So I think I emailed you about it, and I'm like, "How do you protect”
against this?" In advertising in the law in the United States, I'm not sure about here in France. I'm sure they have 17 laws for this. We have one. Because you're great at regulations and less no offense. And the French guy over here is like, "Oh, Mondo, shagal." That's my angry developer. I cannot smoke in the Louvre. This is crazy. It's super interesting with this right to privacy, and I think you've got a quick education on this, because you've had a couple of people. I'm sure
I write you a legal letter. What it basically means is you can't take somebody's voice and use it to,
you know, do commerce in the world. You can use it for parity. There is fair use. I can do a Donald Trump impersonation up here if I like. We're going to take about 5% of 11 lab stock. Is it okay with
“you a bit of a Trump accounts? Sounds good, okay? And for that you have to come to the White House,”
great. Okay, thank you. Nasty guy wouldn't give 5%. Love socialism, but not America. That's the problem with the Nordics. Nasty, nasty socialism. Then I noticed when my guys wanted to clone my voice so that they could fix the ads where I mispronounce something or I do the wrong promo code. Use the code, Jake Held 20. They were like, "It's 25 dummy." And I'm like, "Okay, I have dyslexia," and then they read it. And it was like, "I'm sorry. You cannot clone Jason's voice."
And then it's like, "I have to go in there and do it." And you put a bunch of protections in there. So explain what's happening in that regard in terms of people's concerns around this. And then the other side, which is the opportunity because I think you got Jamie Foxx and some other folks actually that you paid for their voices. Yeah, the voice is identity and IP. It's like, you know, when you speak a certain way, people recognize it can feel that emotion. And you know, to some
extent, it was a, it could be a problem, could be a opportunity before. I mean, as you did in personation of the President Trump, it's, of course, similarly, something that is possible even of a human, not specifically AI. But for us, on the safeguard side, you know, over the last years, we took their all as we are leading another development. We also need to lead another of the same
right. So that's like a critical element. We do free things. One, trace everything that's generated,
so we can take action when needed. Two, now we moderate both on the voice and text level. So if you were to input something that would be commercial in nature or would try to scam someone that gets flagged, we can block it. And now free, because over the last years, we've seen the development of those models more broadly, how can we create systems for the wider world. So people can applaud a sample and get information whether it's AI or not immediately. And we do it for 11 levels, but we also do it for
other open source models. The interesting part, given that it's such a good IP and part of your, your, your, your element, it opens up new opportunity. So we partnered with Mafiumacona here on creating a world carada, rada, rada, rada, and across languages. And it's the, having not paid a lot of money for these independent films, but our 11 lab stock is juicy. Yeah, yeah, could you do it in Spanish? It's, it's a phugazia, phugazia. Yeah. But the crazy thing with the, what AI technology
open is that now the voice can be not only English, but also in Spanish and Italian and Portuguese.
You can still have exactly that element of front emotions coming through.
a good example there, but we've seen that. What do you pay these guys? What is it cost to get
“Mafiumacona? Is this like an eight figure deal, seven figure deal? You give them a little equity?”
Always depends. So like, you know, the master class, for example, is a good example where they
work with talent directly. And here you have previously started content that you would learn from. Now you have interactive content. So you have Gordon Ramsay teaching you how to, how to cook in the kitchen. You can scream at you. If you're not doing wrong, scallops of raw. So that is, that is definitely yeah. So they're doing characters now, or AI instance is using 11 labs so you can interact with them as part of your subscription. Exactly. But as a company, what we now do in this from the
beginning, we created the marketplace where people can create their voice. We authenticated. You can share it and you're money. Today we paid back over $22 million back to the community of, of, of talent. Really with, so those voiceover actors now, who got paid as hourly workers, sometimes they get a little back end if they were doing a commercial or something. Now they can spend an hour reading, create an 11 labs voice and then license it out. 100%. And then did they get to pick their
price or you picked the price? The depends on the model. We do it. We do both. So you can, you can either give it a default that lets us distribute that slightly more optimally or you can pick your voice and the use case is going to be going to be different. And like I said, opens up a set of incredible opportunities in the dynamic context and other languages. But maybe the last one on that
I like voices such a big part of identity and probably probably our most important work was actually
working with people that lost their voice due to a less, due to fraud cancer and working on bringing that voice back. So you work with Congresswoman in the U.S. Jennifer, Jennifer Wexton who lost it and wanted to continue inspire others that you can do incredible work at a spider and was the first
“speech delivered in Congress or more recently I think this was my the most heart warming story.”
There was a, there's a woman that wanted to get married, lost her voice before she could get married. Wow. And then they decided to redo the marriage together. Do the vows again? I do the vows. And you could see the whole family just for the first time hearing the vows. It was just that you could you could feel that emotions that you can see in any other in other way because the voice is such a connecting thing. Yeah. And you've done it for some iconic voices.
My understanding is the estate of James Earl Jones. I'm not sure if they did he pass. James Earl Jones alive. Can somebody pass? He'd be passed, right? Yes. But before he passed, I think he did a deal with Disney. And he said, Listen, for my family, I would like to license the Darth Vader voice for all time to Disney. They gave him some incredible deal. And then they were left with, well, how do we actually do this? Do we get a voice impersonator? But instead they
went to you, talk a little bit about that deal and how it went down. And is that what they use recently, you know, in some of the new films with Darth Vader? There's a new Darth Mall series where they have Darth Vader and did you power that? I don't know what I can say about the new things. But definitely, the big use case that did, that big, big, completely new experience was in a gaming space where, oh, yes, Fortnite. So Epic Games, not, not in the game, Fortnite
launched Darth Vader, which people and players could interact with live. In partnership with this state, in partnership with Disney. So every player, after reaching a certain stage, could have a Darth Vader interact and help you solve the missions. And we are seeing that kind of mode coming up more and more often of how you can effectively extend your likeness, your like you said, like, publicity into interactive use cases, bring it across the world up together.
So that was exactly that model. And now we are working on one of the public one's headspace. So headspace has a great meditation. Yes, this is the second greatest meditation app right behind calm, which you are in Vesteros. Oh, I am calm. I didn't realize you're right,
I did. But it was a $4 million company. That calm is incredible. I'm not even there there. They
team. But anyway, you were working with the side space. Exactly. So they are not exactly the second place. But exactly to that working part. So they are localized love the content. And calm, I think it's trying some of the interactive elements. Could you have a meditation lesson that's personalized to you, which we would love to tell. That would be amazing. And imagine just you know, many voices. David Sachs is defending Trump. Take a deep breath in, breathe out,
“breathe in, breathe out. Maybe you should listen to the voice to calm. I mean, that would be interesting.”
Let's talk a little bit about being up against some of the greatest entrepreneurs ever who want
To take your business from you specifically, Dario and in Propic, Sam from Op...
business. They've been pretty clear about it. And I think you have used the frontier models in your
“product. But you must be thinking, my Lord, am I enabling my own demise by partnering with them?”
And there's always open source models. So how do you think about your partnerships with those
type of frontier models and the fact that they want to kill your company? So on the first part, the given we create a platform, we try to provide all other lamps out there. So our customer is gonna take an untapping, open AI, open source, Google models. And that agnostic to the specific models is actually helpful because customers can make sure that they build the harness, build their agent orchestration, create a voice element of how that agent interacts with the world, how the
marketing or interact with the world, but they're not the panel anymore. So for us, that part is, it's actually good because we can provide up to the customers. On the second big part of, like, of course, the spaces overlapping, increasingly, models are platform platforms from their application. Everything is becoming a little bit more fuzzy. For us, there's still the defining piece was focusing on the one layer of how does interaction look like, how does communication look like?
And we've been able to help compete them on voice models, both on text to speech, speech to text, on the turn-taking, on music. And we, you know, here, that we research team is a set of magicians that are able to continuously do it, time and time again. And I think part of the reason is, it's on the research side. It's the architecture.meters, not the scale. You really need to change how the model operates too. You need very specific data that there's, of course, a
white set of data out there, but it's unlabeled data and where we spend a lot of time, so you build the internal team of over 1,000 contractors that label all those audio assets to make them to make them good. So it's on the research side. And then, as you think about the rest of product stack, we want to create a fully verticalized solution for that communication angle. The product understanding the right workflow and financial services is very different to
healthcare, very different to tell us. We spend all of our product team to figure out how that
works and those companies done. And then, ultimately, last piece is the ecosystem. Can you build
the widest of integrations, voices that you use templates for the agent authentication, that you can benefit from instead of starting from scratch and so far we've been, we've been
“able to create a new model for that. Certainly, though, you must be concerned about, hey, the reinforcement”
learning, the data leakage. They say they're not using your data, but they're kind of using your data. And so, do you have an open source project internally as the, like, in case of glass, we got to break this? And when do you think you'll be able to discontinue working with them if you had to? We know that some companies are continuously trying to figure out how to distill and use the data. So, that is, that is a existing problem. And we have few mechanisms to stop it, slow it down,
let's stop it. But on the open source question, or like, creating our own versions, we are looking at the closer on, like, how we could use our expertise of how to, you know, we won't focus on knowledge work. We won't focus on coding, but any interaction and how we can combine all those pieces together and make sure this is, this is great. Yeah, we want to on. So, we are spending more time there. But it's also just great to be in the arena and compete with those guys,
and, and, and, and, and, and, and, and, and, and, and, and, and, and, and, and every self and show that we can do it and do it better. Yeah, it's pretty clear in my estimation that that's where you you will wind up and the ability to make your own language model today, especially with all these great models out there that are now open source. It's going to be pretty easy for a company with your level of resources, so why wouldn't you, at least offering it as an
“option, and then I guess there's cost. I mean, you must be shipping tens of millions of dollars to the”
frontier models every year. Ship good amount. We are good partners, good partners with them,
and, but, but it's, it's, it's ultimately, you know, showing up in the value we can create to,
so, like, a lot of what we spoke at the beginning of how we can elevate ourselves as our organization, too, is definitely helpful. So, I think they, they don't tremendous work on building. It's, it's, it's almost crazy that each of us has, like, a, a touring company, like, you know, if you, if you, if you were to chat with an agent now, it feels like the touring test would be completed. It's us smart us and other human, and we hope this year we'll do the same thing for voice,
Where any conversation feels like you're speaking with another human.
it just depends on the application and, like, what question you ask, but it definitely passes. I mean, it, if we were to look at the tests that were created to define artificial general intelligence or just to define artificial intelligence, we passed all of those. These were tests
“that were created 30 or 40 years ago. We need a new set of tests right now. I think that new”
test is, like, can this be more intelligent than every single person on the planet times 10? And if we get anything less than that, we're kind of like, oh, yeah, it's not smart. I mean, these things, we're kind of there on AGI. Don't you think that we've kind of achieved it. We just haven't deployed it? I am, there are definitely the places where we did achieve it. Yeah, for sure. All right, continue to success. Let's give it up for Matthew from 11 left.
Well, that's not thanks for coming out. The AI companies building the future run on Oracle Cloud Infrastructure, training and deploying at scale on one of the world's largest AI infrastructures. The same Oracle AI platform gives enterprises access to leading models AI grounded in their own data and the security to move from pilot to production. Learn more at oracle.com/AI or experience at life at Oracle AI experience life. You're growing also at a very significant
clip exponentially. Is it exponential? No, it's not exponential. Oh, it's a 50, it's a
stay in 50 percent quarter of a quarter for the last seven quarters. 50 percent quarter of a quarter
“last seven quarters. Yeah, that's pretty darn fascinating. So I think we actually just became”
as of the close last week on Tuesday, one of the fastest enterprise company with the direct sales motion to go from one to 150, bidding Sierra with one quarter. Amazing. And so people, I mean, there's a couple of things in life that people really hate and paying lawyers is like, way up on the top of the list with your tools. Obviously, you got your contemporary in Harvey and people. It's a small company in the States. And then you also have, I guess,
clawed in other folks also want to be in your business. So this is a big prize. Two,
take, I don't know, 80 percent of what we pay lawyers for and compress it by 90 percent. Like,
what is the realistic power law here in terms of making for startups in the audience, your legal bills dramatically drop in costs. Yeah, and I'm seeing it already in the startup space. I had I had a one firm one startup that hit a million in revenue. They had closed multiple rounds of funding. Multiple, obviously, large number of employees. A decent couple doesn't employees. They didn't have a corporate lawyer. No. And I said, well, well, well, well, well, you think I had a million
dollars in revenue. Like somebody should review the contracts. And they're like, chat cheaper too, bro. Yeah. And I'm like, what about the cap table? They're like, chat cheaper. And I was like, okay, and HR and they're like, same thing, bro. And I'm like, okay, yeah, fun diligence target one day.
“Well, that's what I said. I said, hey, you know, when you do the series A, they're going to ask”
that, like, some of the stuff we review, like, do you guys have, like, IPS I'm, and so like, yeah, I'm like, how did you know to do IPS I'm each first time founders? Like, we asked chat GPT and I'm like, okay, wow, I've just turned into funk. Like, I guess. Yeah. So, so take us through what you think is happening out there. This is not uncommon, right? What I'm not talking about, but a seed stage startup operates very differently from, you know, one of the biggest banks in the
U.S. And so the way to think about the market or at least the way that we like to is, you have this enormous bucket of legal services, which today is being done manually. It's a trillion dollars every year into legal services, which is very fragmented. But the
software spend into legal technology is about 40 billion. So it means there's 4% software,
96% service, which is bananas. The software piece should be much bigger than that. And so the software piece naturally will grow into the service revenue, but also legal is a very supply constrained market. The demand for legal services is much larger than what there are lawyers or legal services available. And so many of the legal service providers are now using technology to serve new use cases, new market segments and to actually package new products. And
you will not make, what's an example of that? So an example of that is cool, actually. They started serving startup founders directly with a sort of software platform that you just log onto the
Platform.
startup material there and they've embedded workflows that reviews the contract. And what I think
is interesting by that is it starts to break this model where you charge out associates for very high hourly rates and you have a billable hour model. And actually if you look in law firms, the way that that business model works is you overcharge for the associates and you actually undercharge for the partners. I don't know if they're under charge, I mean I got a bill recently, it was 1800 an hour. But for a senior person, I think the associates were 800.
Well, the Kirkland can go up to 4,000 an hour, but the thing is when a Kirkland, so let's say, you know, 30 minutes of a Kirkland partners' time when it really matters can be worth a lot more
than that, like a lot more than that. If it's bet the company litigation or you avoid a pitfall
that would have cost at the company tens of millions of dollars. Well worth it, yeah, right,
“exactly. But the only way they know how to price that is to overcharge for the associates.”
But as you're saying, the enterprises are looking at this and they're going, huh, we're spending a lot of dollars on legal services. Let's take this in-house. Oh, really? Absolutely. I mean, we're doing this partly at LaGora. We acquired four businesses so far this year. We did the diligence in-house with our own two. And the fastest transaction with it was 12 of days from L.O.I. to closing. Because your motivation as the founder is to get
the deal done, right? The motivation of the lawyer is to not have you sue them if they f*** up the deal. Right. And to make as much money as possible, which means to drag it out. Which means there incentive is to, even if they don't say it explicitly, it is to drag it out, your incentive is to close it as quick as possible, yeah. Yeah. And so, you know, I think a lot of law firms are also experimenting with different pricing models where you do a fixed fee for a transaction
or for fund race. In litigation, you can take a part of the success fee when you win the deal,
“or win the case. And so, I think it's just very interesting how, you know, one of the biggest”
industries in the world out is being completely transformed and reshaped as a consequence of the tech. And are those law firms feeling like they're being disrupted or this is a huge opportunity? And did that switch at a certain point in time or has it switched for them? There's a lot of anxiety and a lot of fear. And, you know, these law firms are enormously
profitable and big businesses. Kirkland, I list turns around $10 billion a year. How many lawyers
do they have $45,000? Wow. I mean, per partner, they make it between $5 and $10 million every year in profits. And so, when something like AI comes along, that poses existential threats and existential opportunity. And that's actually a big part of my job to help articulate with the leadership teams that we work with because we will only be as successful as our customers are. And so, we're going to have a very unique role at the Gore as well, which is called the legal engineer. So, in the
same way that Palantir has forward deployed engineers, we have forward deployed lawyers. And their job is to sit down with the Kirkland partners and help them transform their business from a pre-AI to a post-AI world. And it's sort of like document management and PCs were, but when you're 30 years ago, when they were printing out and keeping drafts in a library and in a storage facility, and they had to sort of walk them through and handle that. Absolutely. But I think the
different is, the difference is those were mild productivity gains. This can do a lot of the work. And so, it's really reshaping what it also means to be a junior lawyer going into this occupation. What does it mean? Are those jobs going to still exist? Or a lot of the lawyers who are coming out of school, going, "Oh my God, was this a good idea or a bad idea?" The job will exist. The tasks will be different, right? And in order to have a partner-driven model,
“you need to bring people up the racks, right? And the same way as you do with software engineers.”
You need to have junior engineers so that one day you can have senior engineers, so no what they're doing. But the way to get there is very different. The way of getting there today will not be lock yourself in the physical data room, read through every single document, mark the errors, and you know, go fax it, right? And it's also no longer just looking the virtual data room a control F. It's orchestrating the agent that will be doing that work. And when you look at that work,
You have a global backdrop.
to create attorneys who can operate across borders in a way that didn't exist? And you're starting to see that, and is that something that's built into the product? So when you're doing, even in the United States, it's a state-level certification, obviously. And doing the non-compete in the Northeast is very different than doing it in California. They're not very enforceable or enforceable at all in California as people know, but they're quite enforceable if you're in Boston.
So, so talk about that, because that seems to be a place where there could be massive gains from AI. Out-of-cent. And it's really two things. I mean, the data that Legora sits on top of is on one hand side, the firms and enterprises own data. They're precedent, they're organizational data. And secondly, we do the hard work of gathering all the cases, all the legislation, all the regulatory updates for every jurisdiction in the world. And that is very painful, but once you start to do that
at scale, it builds a real data mode. And so in the system, if you are the GC of a company in California
and you just landed your first customer in South Africa, right? Legora can be adapted to the local
legislation in South Africa. And we actually had a case of this where, you know, instead of having to call a lawyer who then knows a lawyer in that region who will respond to the query, they can get an 80% accurate response immediately that they can start working off out of. And the better
“that gets, the more interesting things I believe you can do, because this data has really never been”
structured before. And there's so many people who are working with setting policy and billing regulation, and this is a enormous inefficiency in society. And Lexus Nexus has been a juggernaut and the legacy player in, you know, all the case law and regulations, they have a massive data mode.
But they only make a couple of billion dollars a year. And if you put your revenue and
Harvey's revenue together, you guys are probably already just that the two of you, you're both making hundreds of millions of dollars. So they must be looking in their review mirror at you, like the round of service wrecks in Jurassic Park and going holy sh*t. Like are they coming for our business? And then here you are in stage saying, hey, we're doing all the manual hard work of getting that information into our, what I assume is a proprietary
language model that we get to that in a second, are you going to just try and buy Lexus Nexus,
“I know it's part of a larger enterprise, or are you just going to kill it? Well, I think that some”
of the existing providers and the sort of legacy players have a really hard time pivoting into becoming a united businesses. Sure. And they have a really hard time meeting and catching up to the tempo that we run at. They can't get the talent. They don't work our hours. And they're so political in their organizations that is just hard to move. And I think at the outset of AI, many believed and made a bet that those organizations who had all the data was going to be the winners.
As we're starting to see in the market, that's no longer the case. I think there's a real opportunity for us to partner with content providers. And we're already doing this in many of this smaller jurisdictions, like in Germany, in France, in Spain. The US is peculiar because it's such a duopoly on legal research, as is West laws, the other one. West law and Lexus Nexus, exactly. But yeah, if you look at how their stock is doing, I think, they're, oh, are they getting
priced in with the AI? Well, certainly. Yeah, that's one way of putting it. Yeah, they're getting crushed.
And I would assume there's some power law here. You know, they might have an incredible breath of
you know, old case law that they scanned in and went to the courthouses and did all that work on
“sent to India to be double blind typed in, like the literally, right? That's what you have to do.”
Yeah, they would literally had two different people type in the cases, or OCR, them then check them, look for the differences. I mean, because you can't get it wrong. But today with the AI tools, the AI tools are really good at doing what they did manually. Yes. You still have to ship the books because you have to physically scan. This is very strange in the US, but West law basically has a monopoly with the American government to report on the cases. So they're not owned by
the public in a way, they're owned by a company. You guys are very good at capitalism.
Sometimes too good, but they're not too good.
other law court listener. They're trying. They're trying. That's, it doesn't work. Rather than put it this way, you cannot build a legal research solution that doesn't have all of the data. Because if you go to Wachtell and a litigator at Wachtell, the best law from in the world says I'm going to use this to, you know, go after Elon or do a billion dollar case, you better make sure you have all the cases. So it's the opposite of the power law. You
“don't just need the top 80%, you actually need all of it. All of it. Which means you have to go to”
court houses and ask them for a copy to print it out and pay them 10 cents a page? Well, there's other ways of getting it, but in practice, yes, you have to physically get the books all the way to India, you need to open them, you need to scan them, come on, you think about what's called page
citations. I never thought in in college, I would get this nerdy about legal data, but here we are.
And what's interesting is that these previous generation of databases were very much search in the database, find the case and then the lawyer does their work. Right. What's really interesting about especially the agents following the release of Opus 4.5 and 4.6 is they can now start to do really intelligent case strategy and they can actually start to combine the witness
“statements, the cases and they can really do end to end work, which is I think moving us from a world”
where AI is just augmenting to AI is actually really doing things and your job becomes the orchestrate and to manage those agents as we're seeing encoding. And so you have partnerships with I'm assuming anthropic and open AI, yes, and you spend millions or tens of millions of dollars onto it. Absolutely. And they are also competing with you on the margins. They're not competing in our product category at all, from for now. Well, from the outside, Claude has a legal offering,
which is basically a bundling of markdown skills files and a couple of integrations. And so I think
what's really helpful about that is that it illustrates to everyone how applicable AI is in law. What it also does is it drives a lot of initial usage there and then you hit the ceiling or you understand how shallow it is and then you call off. Right. So it's actually a big pipeline generator for us. So they start experimenting. We're just talking with the CEO of 11 labs about hey, building your own models is pretty doable these days and every six months it gets easier
and easier. So are you working on your own models using open source to then fork it and make your own models? Is that the future for your firm? So I don't believe in fine-tuning or building
“any general intelligence models. I think that's a total waste of time and money. I do believe in”
very narrow models for narrow use cases that you also drive a lot of scale in so you can drive both cost and latency down. An example of this for us is we have a big feature called tabular review
which is basically the number of documents times the number of prompts. So a hundred documents,
a hundred prompts, 10,000 API calls. If you make a fine-tune model at extracting contract data, it's very applicable there. But it doesn't make sounds to build a general legal intelligence model like some of our competitors are attempting. Yeah. And how do you mitigate against the data leakage issue with your customers? These are highly regulated industries with a lot of stake. So putting in this recent case you're working on in no litigation. If any of that were to
seep into a language model and then come out the other end, this is disastrous. You have a higher level of trust possibility. And compliance is our currency. And so it's actually one of the reasons why it's really hard to sell into law. There's a lot of legal AI companies and very few are making it through. And not because it's hard to build stuff, it's actually quite easy to understand where you can build value, but getting into the customer is very hard. But that's something
we cracked pretty early on. And once you're in, it's much easier to expand. So that's also one of
The driving forces behind our M&A strategy.
and weapons manufacturers with their contracts on LaGora. And we work with governments.
“Does that mean you have to put it on prem as well? We don't do on prem. Is that's on the road map?”
Or, no, I mean, you know, deploying in a VPC is very time-consuming. And it creates a lot of dependencies
which slow down your road map and the execution forward.
