Why AI Could Turn Small Law Firms Into Billion-Dollar Businesses

Historically, plaintiff law really didn't need more than a cell phone, email address. That was kind of it. No software really solved the core problem, which is labor constraint. Most people think of AI as like, oh, you're going to fire everybody and cut costs. And it's like, no, actually, like if I use EVE, I make a lot more money for my firm. People can't pay $500, $600 an hour on a blank check for however long the case might take. What EVE is aimed to do is really handle that whole thing end to end. One firm in L.A. went from managing about 100 clients per attorney to 500. Wow. That is a type of thing that is possible. Why is EVE better than just kind of like raw intelligence? If you drop Albert Einstein into a law firm today, he will not be productive for quite some time. That is a general problem that EVE is solving. And why won't that person be productive? Well, it's due to a number of things. One is millions of people have legal problems that lawyers simply can't afford to take on. And AI could change the economics. In this episode, A16Z general partner Alex Rampell sits down with EVE founder and CEO Jay Madeshwaran to discuss how AI could expand access to legal representation. Jay explains how EVE handles work from client intake through settlement, allowing some attorneys to manage five times as many cases without simply adding more people. They also discuss what happens when AI agents start handling thousands of steps across a case, why lawyers could spend more time on actual advocacy, and what the legal system might look like when agents increasingly negotiate with other agents. Hi, everyone. I'm Alex Rampell, partner at Interest and Horowitz. And I'm very happy to be here with Jay from EVE, co-founder and CEO. And everybody knows a lawyer, right? Everybody knows law. But most people, I think, especially in Silicon Valley, when they hear law and legal, they kind of think about corporate law. Like really big, supposedly white shoe, I guess is the term, law firms where you go to Harvard Law School and you bill $2,000 an hour. But there's like another side of law, which actually is bigger, more distributed. And I guess we would call that plaintiff law. So like every time you drive on 101, you see all these billboards. And maybe kind of talk about what is EVE? What form of law and legal AI do you focus on? And maybe a little bit about the industry in general, because I feel like most Americans are familiar with it, but they don't necessarily realize, and especially for people, I think, here in Silicon Valley, they've heard of Wilson-Sincini, but they haven't heard of Morgan & Morgan. And Morgan & Morgan is probably a lot more profitable than Wilson-Sincini. But like, what is plaintiff law? And also kind of maybe explain EVE in your own words. Absolutely. One, thank you for having me here, Alex. Always fun to talk about EVE. What EVE is, is legal AI for real people. People like you, me, not institutions, not in-house legal, not the people that already have all the resources. But how do we actually provide legal services to people that otherwise can't afford it? And this is how the plaintiff law industry really came about. Because what ended up happening was, you talked about how Wilson-Sincini might charge $2,000 an hour, and that's really the business model. Lawyers' times are expensive, and you're trying to point lawyers towards more and more expensive time. And the same is true for most lawyers. They have a lot of bills to pay. And today, legal work, the more work you put behind it, you can represent your facts better. You can get a better outcome. That is the state of world we live in today. To account for this, lawyers understand people can't pay $500, $600 an hour on a blank check for however long the case might take. So the plaintiff industry came about on working on contingency law. So what this means is, they only get paid when they win the case for the client. And this is what's allowed them to even have any sort of leveling playing field with people versus institutions. And what Eve is aiming to do is really handle that whole thing end-to-end of how do you represent a client all the way from the very first call to getting them a settlement? How do you do that end-to-end thing purely with AI? And give that to the lawyers to then amplify the outcomes that can actually provide. And that's what Eve is doing. And think about giving David a slingshot to take down Goliath. That's what we're doing. So what I find fascinating about this is you really, I kind of think about econ 101, where you have a supply curve that goes up into the right. And what does that mean? Because remember, there's price and quantity. So here's quantity and here's price. So as the price goes up, then the quantity supplied goes up. So if I can make $100,000 by doing something, wow, I'm totally in. But the demand curve is the opposite direction. So price and quantity go this direction. So the demand, the number of the units that I want, actually, this is quantity, this is price here. So price goes down, quantity demanded goes up considerably. And if I think about applying this to law, like what if I have $1,000 of damages? I can call a lawyer, even for contingency. They might not want to take my case because if they take a third of the outcome, it's like they want a bigger case and it's going to require a certain amount of work. And AI really, it kind of liberates these market failures to a certain extent. Because you mentioned kind of giving David a bigger slingshot. A lot of times, David just, well, number one, if I have $1,000 of damages, I certainly can't pay $1,200 an hour for a lawyer. So I'm out for that, we'll enter contingency law. The problem is that the settlement might not be big enough. So the lawyer might want to serve me, but he or she has paralegals that they have to pay and so on and so forth. But if the software can do the work, now the market opportunity is so much bigger. You can actually deliver justice for a lot of people that otherwise, they weren't priced out of it. Because how are you priced out of contingency, but it's not really in the interest of a lawyer. They want to serve a thousand customers that they get, but they can't, they have to focus on the biggest ones to the detriment of the smaller ones. Because again, it's kind of to the right of that equilibrium point. I don't know if you agree with that or how you think about that. That is exactly right. I think that is the actual market problem we have today, which is if you go back to first principles, if you're a person, you deserve a great lawyer to represent your case. And you usually only need a lawyer when your back is against the wall. The best of us, the worst of us comes out this time and we don't have the skill sets to represent ourselves. That's why this whole profession exists. That's why the legal system is about third of our government. It's for this reason. And today what's happening is because lawyers still need to get paid, it's still bottlenecked on legal work. Today if a lawyer doesn't make at least 5,000 fees off a case, they do not take it on. That is the market dynamics today. And even at 5,000, they're losing money on a lot of cases. They're really banking on few cases paying out very large. They're not even guaranteed to win, period. That's exactly right. So they already take that on. That's the contingency aspect. That's exactly right. But it's kind of like, even if I win, I lose because my costs of carrying the case are going to be higher than the actual potential outcome, even if I win. That's exactly right. I mean, think about like most people here have been in a car accident, fender bender of some sort. If it's below the deductible, no lawyer in America will touch that case. It's just not economically worth it, even if the deductible is $3,000, $4,000. To an individual, that is a difference between a paycheck being gone versus not. And there's no representation they can get for that. And the reason is actually from their side, we have to understand from their side too. So let's say you've been getting harassed at work and your employer could stop it. In the hospitality industry, let's say you could tell your customers, hey, don't harass my employees and change processes to make that happen. Today, that doesn't happen because when that person gets calls, the lawyer on the other side has to pick up a call, feel that call. That's about 30 to 45 minutes of work. And then after that, go do legal research because in employment in America, pretty much everything's at will. And you have to tie a problem to like a protective clause of some kind. It's called causes of action. So you have to tie it to a cause of action. And that work requires them to go spend 10 hours to go research your case law, research the facts, go back and forth and ask them more follow up questions to see if they qualify. And while they spent all that time, they might still realize, hey, this doesn't even make me $5,000. So that is why 96% of cases on the labor and employment side, for example, gets rejected. So you can never find anybody to represent you unless you come out of pocket. And many people don't have money to come out of pocket. That's exactly right. So you just kind of take it unless something really egregious happens. And that is the current state. And it's all bottlenecked on legal labor. And this is what Eve is meant to do is to how do you now take that 10 hours is now immediate with Eve. A call comes in, Eve actually answers the call and automatically uses his insights on the law firm to know whether or not this is a case the lawyer has to take on or not and then hit the ground running with a demand or the initial preliminary work done. And that completely changes the economics of that type of case. And we're still at the very beginning stages. What's happening is Eve is getting more and more capable of handling outcomes end to end over a very long horizon. These cases take six months, a year to launch and through them probably a thousand actions back and forth that are happening. And as accuracy of Eve is getting higher and higher, this long horizon becomes possible. So the more this becomes possible, even more complicated work gets more ties down to a constant case. So now all these people without representation get representation. And if you really ask yourself, like, how many times in your life, if asking for legal help wasn't a friction point, would you have asked it? That number is way higher than we think. Yeah. So it's a funny story. It's a true story. I was in Blue Bottle, a little coffee shop in Los Altos, and I was explaining Eve to somebody probably nine months ago. And I was explaining it because most people think of AI as like, oh, you're going to fire everybody and cut costs and it's all about cost savings. And it's like, no, actually, like if I use Eve, I make a lot more money for my firm. And it's not because I'm cutting costs. It's like I can take on more cases. It's actually revenue expansion. So I'm explaining this as an outsider investor can, so not as well as you probably would. And at the end of this, I mean, we were talking about many topics, but Eve came up and this guy comes up to me. He looks a little angry. He has a big dog. And I'm kind of afraid of big dogs. And he's like, what was that company you were talking about? It's like, oh, is he going to get mad? He's like, I'm a trial attorney. I want to try it. Oh, great. So I got you a new customer there. Thank you. But the whole point is that you expand the revenue opportunity, but maybe kind of walk through like, what do the dynamics because everybody is driven on 101 or I-95, I-95 is the corridor that goes from Florida all the way up to Maine or something, you know, up and down the Eastern seaboard. And it's like, I've driven almost all of that. And it's like, I feel like half of the ads are for trial attorneys, plaintiff law. So they're obviously advertising there because you want, they want to get called. It's like, hey, I have this accident or I have this issue. But what are the economics look like? So like, I spend all this is why, again, I think Eve is so fascinating because I have to turn down 90% of the leads that I'm getting, I assume, right, or like, what are the numbers look like? I spend money on a billboard. I spend lots of inbound. How many of those turn into cases? How many of those cases turn into revenue? Maybe kind of like a before and after, because you are, you're not a cost savings play for lawyers. You're a revenue expansion play for them. That's from the legal side. But what are the economics look like for a law firm? That's exactly right. When most people drive by, they see the face and they forget about the people behind them and the amount of work every single call actually takes. That's what happens today. That's what Eve is there to help with. And the math on the law firm side is very simple. The more people you represent, typically speaking, the more money you make. But because you can take on more people and you honestly are denying and not taking on many cases because they're too expensive to take on, the demand from their perspective is not really constrained. It's really the supply of labor. Do I have enough people inside to actually service that problem? And to make things more complicated, different firms here are in different realms of problems where the bottleneck keeps shifting. So a small firm might just have one attorney that has a case manager or some sort of office manager that feels initial call and just notes it down. And then the lawyer then responds back in their free time. They're kind of running chaotically, running around. And then there's a next level, which is they find a way to systematize it. They have an intake team, like a call center somewhere that intakes it. And now that becomes a new bottleneck. So now when you increase your marketing spend, let's say you looked particularly attractive in that billboard and a lot of people are calling in, suddenly now that team is overwhelmed and you're limited again by how many people you can represent. And this is the daily challenge these small businesses are dealing with. They're small businesses. They're not massive enterprises. They want to represent individuals. And everyone here went to law school, not business school. They want to be there for the people. So we're basically consolidating all of that into the EVE platform such that they are getting pulled in only for what they need to, right? Like their lawyer insights, their particular insights on how do they take this case, EVE keeps raising the floor. How do I take it from this floor to the next level? That is where I believe really all lawyers spend time, talking to their people and helping get client outcomes. Well, and this is kind of the market failure point to a certain extent, which is I could serve all 5,000 leads that came in if only I could hire a paralegal for 12 cents per hour, right? Or whatever the token cost of it, but it's like, I can't. So I would just, there's no labor market that could actually function. But with AI now I can. I mean, do you have anecdotes of just like kind of before and after it's just like, you know, like the hair club for men, it's like, you know, here I am before, here after I have a nice head of hair, but like, what's that for kind of your best customers that you work with? I imagine the revenue transformation is pretty significant. Yeah, one firm in LA went from managing about 100 clients per attorney to 500. Wow. And that is that is a type of thing that is possible. And they went to their credit. They worked really hard to achieve this. They utilized Eve up to the max of all the way from intake, take fielding the call, doing qualification, automatically removing all the relay problem that they have of passing things from one attorney to another, to a case manager. All that is now handled with an agents in Eve and all the way to settlement where it's actually briefs before they go to a mediator discussion that actually tells you here's what you need to focus on. Here's what the settlement outcome should look like for cases like this that we worked on. And here are the tactics used before that got you here. And that is what the future looks like. It's truly moving the case forward continuously and you're helping making it do a better job than it could do by itself. That is I think the future of law, right? Where you as a lawyer are really going to look more like almost a data scientist and engineer, engineering something to be better and better. And that is a shift the top law firms on Eve mentally kind of go through. Yeah. Well, I kind of think of if you look at your average law firm where they don't really know AI, and actually like this is kind of an interesting kind of take on the world of AI-enabled applications in general, like what was the software stack for law before? Well, if you're a big firm like Wilson-Sincini, probably the most important thing is like your time tracker, right, because you're billing by the hour. If you're in contingency law, it's like, well, your time matters, but you're not billing your customers on that. You probably need to have like a, you know, each case, here's how much money I'm spending on the case. But like I imagine your primary tool is Microsoft Word and there wasn't, and this is how like VCs would have like gotten this industry wrong before, which is like, oh, well, the software market for plaintiff law is small. They all buy Microsoft Office. Yeah, Microsoft Office is kind of expensive. So therefore, like the software spend is like in the tens of billions of dollars a year or something, you know, seemingly comically small. But wait a minute, the outcomes that they deliver is in the hundreds of billions of dollars a year. They can't deliver more outcomes because they're really constrained on labor and they can't hire labor for 12 cents an hour because it doesn't exist. So it turns out the software market is kind of like this shadow labor market and it's like massively bigger than anybody would have expected. And like, it's always just a weird thing because it's like, you can't say the software market is small because you're a legal software company, but people know Harvey or they know like corporate laws or like, you know, e-discovery tools that have been around. But I imagine like, what was the main software stack before Eve entered? Was it just Microsoft Word? Or like, what was in order for me to go into business? I graduated from law school. I want to be in this particular subsector of the field. What was my software stack? You know, this is the unfortunate thing about plaintiff law and institutions is, historically, plaintiff law really didn't need more than a cell phone email address. Honestly, even Microsoft Word, some people on the solos would not buy it for cost reasons, other reasons. No, it's because if you think about it, you actually don't do that much redlining. It's a trust boundary situation, right? So your one side is kind of opposition to the other side, so you're not really collaborating in the same way that you are when you're doing contract review or something along those lines. So that was kind of it. And no software really solved their core problem, which is exactly what you mentioned. Their labor constraint. That is the core of how they do anything at all. And because they have labor and they're good at managing their labor, they found a way to solve every problem to them look like solid labor. And that's how they've grown up. And as a result of that, what ended up happening was a lot of resources on software went towards defense institutions because that's where the budgets were. For Harvey, you know, really any company, honestly, legal software companies today, vast majority of them are on the defense side because that's where the budgets are. And that's what's easy to build for, easy to get money for. And on the plaintiff side, these are small businesses that are watching their pocketbooks every month. If you're not driving outcomes for them from day one, you're out. You're not getting renewed. They're going to curse you out. Anything they can do, they're going to come after you. And that's what's made things so difficult. But what we realized is, well, their core problem is we know what their incentives are. They want to represent more people. They want to win. And we can do that now. You know, there's once the beauty of software today is once you do a task manually, even tasks that include crunching new piece of data and transforming it, that's kind of what AI is really good at. You can now encode it as a process. That is a fundamentally new shift that has never happened before. That's what they were trying to do with people operations, but never worked because every single case is still different enough that you can't do it. It's still bottlenecked on hiring smart enough people to be able to handle it. And now one smart person can actually handle, like we talked about, 500 different cases of very different facts, very different situations, and how do you even keep that in your brain? Like, it's hard, right? But now you don't have to. And I guess one of the things that a lot of founders are thinking about right now at the application layer is like, uh-oh, maybe I'm roadkill from the big guys, right? Like the labs that produce the intelligence, maybe they're going to go tackle MySpace next, and I'm toast. And there are many ways of defending against that, but defending kind of sells it short because if you're able, like if you have a network effect or if you have data that actually nobody else has, you can deliver better outcomes. So, you know, who cares if everybody uses ChatGPT or Claude behind the scenes or on their own? But maybe talk about like, I'm sure you've thought about this a lot. You know, why is Eve better than just kind of like raw intelligence? And how does it get better, because it does, the more practitioners that use the product? Yeah, we're betting on these models getting better and better. And our value is exactly that. You know, if you have 1,000 Albert Einsteins to work with to do litigation or, you know, the best attorney ever to do every single task, we would take it. The problem is if you drop Albert Einstein into a law firm today, he will not be productive for quite some time. And that is a general problem that Eve is solving, right? And why won't that person be productive? Well, it's due to a number of things. I think one is in plaintiff law, the vast majority of data is actually non-scrapable. About less than a percent of cases actually settle and get turned into case opinions. Vast majority settle pre-demand or pre-litigation. And some even before that, right, where it's actually just a negotiation of, hey, this is how I was wronged. Please fix it. And to make that concrete, it's like I'm in a car accident. I'm not at fault. You know, the adversary, if you will, like the other side's insurance company is like, oh, you weren't that hurt. We'll give you a dollar, right? They always try to like deny, deny, deny. Like rule number one of an insurance carrier is deny. Rule number two is deny. You know, it just goes on. Those are all the rules of insurance carriers. So now I hire a lawyer to actually get what I'm owed because I actually am injured and my car is actually totaled and they just don't want to pay me. You get a settlement. It doesn't go to case. It doesn't go to actual trial. But you know, right, that GEICO actually did pay $29,000 and that's very, very useful information, I assume. That's right. Because insurance is the one that's dealing with 100,000 different law firms. So they have the shared community. They know all the cases, but because it's sharded across all the different local firms, they don't know exactly GEICO's every single move. That's exactly right. And you know, they even have ominous sounding software like Colossus, which tracks, you know, they try to basically say a broken thumb. This is how much we think it's worth, which is a hard thing to do. From their defense, like it's a hard thing to do, but they are doing that, but also saying this is how much we can get away with giving them away for. And irrespective of that individual's actual need of their particular situations, and that's what the legal system is meant to fix. That's what it's there for. And what now is happening is, and this is the interesting bit and the challenge, is if you go and Google, how do you write an amazing demand letter against State Farm for soft tissue injury cases? Like that today exists nowhere. Even for a new paralegal that is joining a plaintiff firm, this is something they have to learn. And on top of that, it gets more complicated because when you're in local jurisdiction, the local environment, like the court systems, your opposing counsel, they all behave a little differently. And that context matters too. So what Eve is doing is it's turning this, historically, incredibly difficult to utilize multi-attribute, multi-dimensional information that is basically what is the best thing I can do at this particular moment to improve the outcome of the case. And that same question is repeated thousands of times during the case. And a human brain is just not capable of kind of keeping all of that in mind. But AI is, right? And that is the type of data we help build for law firms, and they're seeing the immediate value from it. And the first place where they see value is, of course, intake. Who do I even take on? Who am I good at representing? And maybe you start there and keep getting better. Right. And I imagine, because these aren't giant firms, right? Like if I'm a lawyer in New Jersey with a four-person, four-attorney practice, and over there there's another lawyer in Arizona with a seven-attorney practice, but their counterparties tend to be State Farm and Geico and whatnot at the limit, it's actually fine to share information. So I guess, how do you think about data? Because this is always hard for companies when you're getting off the ground. It's like, no, this is my data. But there's also, there's a give to get, I assume. It's kind of like, I work with a dental AI company, and it's like, well, the dentist in Iowa can't serve patients in Florida, but they want to learn from the collective actions of each other. But I guess, how do you think about just data sequestration and whatnot? Does that ever become an issue, or how do you think about using it? We've largely followed the rules of engagement that already exist in this industry, but we've amplified it with software. That's kind of our stance, right? So the rules of engagement is, for their own cases, they want to be very private. Like that is important by law, it's attorney-client privilege, and we don't train on that data ever, right? However, what attorneys also do is, to share this knowledge, they actually travel, they attend CLE, and they share tactics with each other on how they went up against State Farm's X and Y defense, because State Farm repeats that defense across the board, right? And not picking on State Farm, anyone is fair game here, but that is what they're already doing. So we hire our own attorneys and track success rates of cases for our platform, and we want to help. If you're using Eve, you should have more success. That's what we track. And we have this product called Auditor, which actually analyzes every single case through every single page overnight and looks for situations that a perfect attorney would catch every time. And across the board, unfortunately, vast majority of cases have, almost every single case has missed information, right? And now that's no longer a thing, yeah. And maybe talk about the future of where things go, because on the one hand, I can imagine a world where it's like, one of these days Geico is going to get a little bit smarter and they're probably going to like, you see, they're deny, deny, deny plan. That's how they got smart before, right? Because they realized it is an adversarial system. Like, you know, I lost my house in a fire and I'm going to claim I had a Picasso in there. And then they're going to think that I'm claiming that I have a Picasso. They're just going to deny the claim, deny, deny. Like, so each party is kind of fighting each other, but they're going to get superpowers. I mean, you see this playing out a little bit with Muse and all the consumer agents, where I want a reservation at this restaurant that's impossible to get, and they have a human answering the phone. I can DDoS them now that I have to pay one penny per hour or something. And then eventually they're going to realize that they're getting DDoS and they're going to prevent that. So, you know, I guess on the one hand, like, how do you think about, you know, your adversaries here, not your adversaries, but like your clients' adversaries, how are they adapting to a world where it's like, you know, it was great for GEICO where they could say, hey, you have $2,000 of damages. The consumer's like, yeah, I did have maybe $2,500 of damages, but it's like they never really had to worry about that before because of the quantum. And now, unfortunately for them, but fortunately for the Davids of the world, like people that are actually aggrieved and have been victims, now they can fight back and you're powering that. So that's kind of one thing. But also you mentioned long-horizon agents because, you know, what does the practice of law look like when a lot of the stuff can actually be done by AI? I think you framed it as like the attorneys are almost like the data scientists of the future. But, you know, maybe talk about like, what does the adversary or the adversarial process look like? You know, what are the skate farms and GEICOs using potentially as a result of you entering the scene? But also like how, big, big question, but how does law evolve and emerge just given that, you know, you're kind of manipulating words and finding facts and doing all this kind of stuff where like the humans are not as important? They obviously have an important role of shepherding the case to completion, but like what does the AI do versus not do? Yeah, I mean, ultimately, my framework for thinking about this is ultimately when you have an individual, they're going to need representation. Whether that representation, like who does the work on the representation, you can assume it's 99% AI, maybe 99.9% AI. There's always going to be that little bit that is the human touch, right? And we do believe that people are going to make a positive difference to the outcomes of the case. And that is exactly what. you have, right? So like what do you have on the on the defense side or really institution side is what's always happened, which is they have more resources, they have more money, they have more time, which is actually another weapon they have, which is quite powerful. Individuals are in in debt to pay their fees. And that is a very powerful tool they have. And that is that is a strength they're working with. And they're trying to rely on centralization and standardization. On the defense side, you have a attorney that is fighting your case, and pushing them to get to litigation. And I think that is going to be what happens. I think a lot more cases are going to have teeth. And all the routine back and forth, I think is going to happen through agents talking to agents. I think that's, you know, it's crazy future world. But I think that's where we're headed to. And the difference maker is what does the attorney understand about that client, that set of facts, and their local environment of who they're going up against locally in that law in that defense firm. And they're using that insight to make a difference for their client. And I don't think that ever goes away. It's, it's, in fact, something we're seeing already, where many customers on Eve are actually choosing to spend more time on the trial work. Yeah, because it actually enables that previously, going to trial took down an entire firm, right? Suddenly, you're just spending all your time doing trial, trial prep, interviewing juries, you want things to settle. Exactly. It's more of a settlement motion. That's exactly right. And instead, I think things are going more into real advocacy. How do I actually make our point known? How do I you know, my client is against back of the wall. They're doing bad things, they're doing good things. How do I represent them in what actually matters for them? I imagine this is kind of the data science side of what you're doing as well with this giant data set that's probably never been accumulated before. Because as you mentioned, all these things, it's so bespoke. There's no like communal repository for like all the settlement amounts. But like, I've seen this with litigation finance a little bit where if I'm a lawyer, if I'm a trial attorney, and I'm not getting paid by the hour by you, my client, well, where do I pay myself and my staff and my office rent and everything else? Well, there are companies that will show up and say, I will fund this case. That's right. Right. And I'm funding this case, because I'm counting on you winning it. And like, they'll do all sorts of clever things, like here's the judge. And here's this, like they're using data. So outside of I think those guys have been very data science forward. But historically, like this data just like never really lived anywhere. And now that it does, you can make smarter decisions as an attorney. I'm like, do I take it to trial? Or do I accept the settlement? Or do I push back? Oh, Geico offered me $12,000? Should I push back and fight for 15? Should I, you know, take it to trial and try to win 100? Like, how do I make those decisions? That's exactly right. That's which is why we can help them make the best decision every single case and no one optimal outcome has been achieved. Yeah. And it's still I would say it's still the attorney's responsibility to push it even further. Right. And I think that is what I meant by data science like work because right, they're using the power of software to do work you never even thought to do to improve the outcome. And I mean, where do you think this is a very broad question, of course, but like, where does the legal system go? I was having some some trouble with Wells Fargo. And I'm like, you know what, I've tried like for four hours to do this, I'm just going to sue them. So I went to Codex, you know, Chad, GBD, I was like, Sue Wells Fargo. Four hours later, it had sued Wells Fargo, it actually found a process server. I got the notice of certainly we're going to court, but you know, the date is in February, like another kind of similar vein is happening with patent law, where before it's so much work to go file a patent. Now it's less work to file a patent. But you still have the USPTO, which is the bottleneck. So I guess I mean, if you were to prognosticate, like, where does the legal industry go? Now that AI is becoming table stakes, and you're delivering, you're part of that table, obviously for plaintiff law. But if you think about the entire practice of law in general, like, how does it change? If you were to fast forward five years, what does it look like? What's similar? What's different? Most likely, I think it's inevitable that you're going to have to create systems where not everything goes to the court system. And this already is a framework that is used in law, right? Like, I mean, for some types of Veterans Affairs cases that goes through a different committee, for even labor and employment, that goes through EEOC, in a lot of cases before it goes through. And, you know, employers have figured out different ways to mediate and have arbitration that doesn't necessarily go through the court system. And this is the framework that actually naturally evolves. And I expect that to happen more and more. And I think the tweak that's going to happen is that for some pockets of it, we're probably going to go through some version of like ADR, automated dispute resolution, where AI enabled mediators or central parties that have a neutral view of both sides are going to use AI to really speed up how they come up with judgment. And I don't think that judgment will really be replaced. But what they will get is a set of facts that shows, historically, here's how this happened, here's how this happened. And it's up to them to remove the biases that might exist. And I think we're just going to spend more and more time on that side of things. And do you think the small law firms get bigger? Because that would be the other thing. It's like, if I can only handle 100 cases per attorney, now I can handle 500. But in the future, maybe 5000. You know, why do I limit my office to like a very, very small New Jersey location? Maybe I should go more broad. And you're going to have kind of larger, almost like corporate like law entities. And like, I think the biggest trial attorney firm is Morgan and Morgan. Is that right? And they have billions of dollars in revenue, but your average firm is quite small. But you could imagine powered by Eve. And with all the changes that we're talking about, it's like the small firm could actually become a billion dollar revenue business. It's kind of like venture outcomes versus kind of like what you would call a lifestyle business. You were a VC once upon a time, you know that term, somewhat pejorative term for like, you make profits. But how do you think, like, is that a reasonable take that like some of these small guys can actually I mean, obviously, you can't go public as a law firm for now, maybe in Arizona or something you can. But how do you think there's a chance for some of these local mom and pop stores, if you will, to become very, very large institutions? I think the transformation that's going to happen is a lot of these law firms are going to look more like software companies. I think they're going to finally participate in the software revolution that's been happening for the last 30 years they've been left out of. Right. And if you if you kind of deep dive, you'll understand why. Let's say you have a $25,000 settlement, the attorney gets maybe a third of that. Let's call it 8,000 for simplicity. And, you know, like, all that 8,000, about half of it goes towards labor spend, 30% goes to marketing, and the rest, maybe as profit, right? Like that, that's kind of the business as it exists today. Because of that business, it is so difficult to reinvest back into servicing your next client better. Right? Like, the only way you can really do that is by hiring a better attorney today, right? What changes is, now they can actually accrue a database and data set that is unique to them, that gets them results that is better than their competitors for a subset of law. Right. And this is kind of specialization. And historically, this industry already been through that. You know, like 30 years ago, there was a, you know, your neighborhood lawyer that handled everything, you know, from employment cases to IP to what have you. Exactly, exactly. And now what we have are specializations of practice areas, you have someone that's really good at IP, someone that's good at employment, and now it's getting even more specific, right? Like someone that's good at, let's say, nerfing bird defects, or something along those lines. And I can anticipate that to go even another level, where now, someone could get really good at soft tissue injury cases that involve x and y fact patterns. And it advertising for those cases might be a lot more cost effective than some other larger firm like Morgan & Morgan, just showing their billboard everywhere. So get good at something locally and then expand just across the entire country because you have such high competence around that one field. That's exactly right. And we're so I think we're gonna see that type of specialization. And I think we're also going to see the opposite, where some of the large, we're also working with some on the scale of Morgan & Morgan, like some of them actually are coming together. So those ones that got us big, are actually going around buying other law firms, because they realized with Eve, they can very quickly consolidate what used to be a very painful reintegration process now can be done on exactly what the client wants, which is, hey, the client wants a legal outcome. And Eve is made just for that. Yeah. So by doing that, they get to largely work away from a lot of the change management, work, workforce changes, operation changes, because Eve handles a lot of that for them, they can speed up their time to making that acquisition worth it. Well, the funny thing is that there's this movement underway to outcome oriented pricing. So like software, SaaS used to be per seat per month. And I used to joke, it was like the tall grande event team model of software selling. It's like you go to like any SaaS companies website, this is like, you know, Claude can clone them also readily, they all look the same. It's like $79 a month, $99 a month, $129 a month, you know, tall grande event team. And it was per seat. And like, look at a company like Zendesk, which had $2 billion of ARR, when they were last a public company, they were taken private by Premier and Hellman and Friedman. And now they're like, Oh, how many seats do you need, like maybe zero, we need to deliver outcomes. So everybody in the software world is kind of like in a lot of AI companies, like we deliver outcomes, we charge for outcomes. The interesting thing is that the form of law that you focused on, was always outcome oriented from the very beginning. But you have other types of law that are not outcome oriented, where I guarantee all the clients would much, much, much prefer that it was outcome based. Right? I mean, sometimes it's tricky. Like I have a trust in a state attorney at McDermott, well in Emory, she's very, very good. She's like, so expensive. Like, I guess my outcome, the outcome is my death. So I don't know if I want that. But you know, you would prefer to just say like, there was a fixed cost. But there's often this data, you know, in their defense, the reason to charge by the hour is not so much to rip off the client, but there's data asymmetry between what I want in my head, and how I articulate it, maybe the the scope of the project is changing over time. But you know, other forms of law, I would argue they probably should look more like plaintiff's law, they should have outcome oriented pricing as well. Right? Or like immigration law, that should be outcome oriented, but like everything should be outcome pricing, but it's hard because there's a data deficiency, if you will, in terms of like, how will I win this case on behalf of the defendant? But I guess like, how do you think other forms of like, you could probably expand well beyond plaintiff law? And if you agree with me, but like, how do you think about just like law in general changing? Because I kind of feel like plaintiff's law was like ahead of everything that we're seeing right now. It's like everybody wants outcomes, nobody wants to pay for the ingredients or the inputs. This was the only kind of field probably of business, where it's like it was always outcome oriented, but kind of shouldn't other parts of law work that way? That is our exact belief as well. Right? So like the hard part has been, it is hard. You know, when you're on the defense side, or even the plaintiff side, the question around a new case, is it 10 hours of work, 100 hours of work? In many cases, you really don't know until you take it on. And for plaintiffs, that is why we had to go so deep into each practice area into achieving outcomes. And you know, we were doing what is now coined long horizon agents like last year, that's just what was needed to drive results. And now it's getting better and better to actually drive legal outcomes. And ultimately, I think what is needed for democratizing of law is from a set of facts, you need to know how much compute resources you need to arrive at a outcome. And that happens through both aggregation of and better usage of data, and better usage of actually running the compute to achieve set outcome. And so we're doing both, right? So like, that is why we're laser focused on outcomes. And we want to drive outcomes. And eventually, this David versus Goliath thing is happening everywhere. You know, it's not just in, in, you know, big law or in house legal, those are just where the budgets are. So they actually can write basically a blank check for interim period of time. And the, the forcing function around how much is this actually worth and outcomes to me is not known, right? Like, I mean, you know, this, like when you go fundraise, you might get hit with like a 100k check, what is the exact outcome of that? You know, like, it's very hard to know what the value of this, but that is the only way they can price today. Right. And that's because they don't know what the expected value of their work actually is. Well, that's the asymmetry as well. It's like, I don't know, it's like, okay, you need to hire a lawyer for your series. See, man, what does that mean? Well, it could be like, very, very simple, it could be very complicated. So it's very hard to have a flat rate. That's wrong, because they can get burned in, but they can't get burned in the low direction, right? It's like, I charged you $25,000, I spent an hour on this, but they can get burned if it's like, I have to now spend 4000 hours of attorney time, I can lose money on this, which of course, every single firm they are, we will actually like, as you know, in corporate law, these are loss leader products. And then you try to make it up on the M&A or IPO or something, but obviously a little bit different than plaintiff law. How do you guys charge? How did you because I imagine you had a it's not like on day one, when you started the business, you knew exactly what you were going to charge for like, what type of customer I imagine your thinking has evolved on this as well. Absolutely. So I mean, from actually, weirdly enough, from day one, we started probably with the, with the, you know, was a tall, grande, grande venti, venti model. That's, that's what we started with, because we didn't know any better. Right. And then as we dug into it, we realized like, what they care about is outcomes, what they care about is how do I serve more clients. So that actually forced us to be outcome based from very early days. Now we're talking like a year and a half ago, which is pretty funny. That's early in today's world. AI time. Like dog years times 100. Yeah, exactly. But that that is that is kind of what happened to us. Right. And There's so much room to grow where now that, you know, we talked about that, that value diagram of a third goes to attorneys, half of that is labor, that is half they don't have to spend anymore, right? So how do you actually turn that into something more useful? And that way, the best way to get more useful work is actually to spend it weirdly on more tokens and more, more work that you can do to make more money for your firm, right? And that is kind of the cycle we're in today. And a lot of the market dynamics that is helping us is exactly this. Like we actually believe the billable hour model, I don't think it's going to die completely, but I think it's going to be on the way of the seat based pricing model, where for some subset of law, that is probably the best way you can charge for the work, because it's very difficult to know value until an outcome many, many years later. But for a lot of it, that's not true anymore. You know, for a lot of it, you actually know what the outcomes are. And you should be able to take your work down to an amortized amount and deliver that back, right? And that is what we are betting on, right? And this is why we focused on delivering legal outcomes from day one, end to end, and doing that in such a way that it is as simple as a lawyer saying, here's this client I got in, give it to Eve, Eve will pull you in when you're needed, and you're good to go. We've talked about how plaintiff attorneys, they are supply constrained, not demand constrained, or many of them are, because they have this infinite influx of clients that they can't serve because the math doesn't really work in terms of CAC versus LTV. It's the old fashioned thing for any business. It applies to them as well. You know, where are your constraints? Like what kind of holds you back from growing faster? I mean, you're obviously growing incredibly fast. What are your rate limiters? What do you need as inputs to grow faster as an output? You know, it's really fascinating because a lot of the legal benchmarks, like even benchmarks that you share publicly, that Anthropic, OpenAI, many of whom we're working very closely with are working on, care a lot about like almost single outcome, right? Like here's a task. Did it kind of do mostly okay? And the world is now moving into agentic work. For us, the only thing that ever mattered was the agentic outcomes, right? So like now that is getting more and more. The end outcome here is today, we're still at the point with technology and processes where there's still a decent amount of human touches needed per case. But by doing more and more work, we've been drastically reducing that month over month. And in our industry, we need to do that per case type, right? So like for every single case, we're learning that like a science, like how do you actually resolve this case? And how do you build a mini attorney brain that is capable of crunching all these data points to that resolution and driving it across the board and working with all the tools they have access to, including cloud and whatnot, to drive that outcome? And that is a really hard problem, right? So we're largely limited by engineers at this point. Like we have a limitless number of things to do to drive this forward. And the other fun part is we have demand. The moment we are able to deliver on, let's say, moving vehicle accident cases end to end, the amount of value that gets unlocked for the world from that is in the hundreds of billions of dollars. And that's just one subtype. That's a great question. Have you had a fully autonomous end to end case? It's like answer phone, onboard client, you know, get out, get check from Geico, you know, like, has that happened end to end? Not yet, but we're close. That is what that is why we need the engineers, right? So like to put things in perspective, a single case has probably 10,000 back and forths, 10,000, something like that. Because here's how you think about it, right? A client comes in, let's say it's a PI case. Now we have medical records. So now you have to actually outbound call insurance companies and healthcare companies to get hold of the records that the clients already had. Right, so like that is actually that takes two weeks today. And with Eve outbound agents, where we actually have voice AI that can do the outbound call. And funnily enough, that's an area where we're already seeing agents talking to other agents and learning how to get past each other, which is hilarious. And that is like one step that's needed, right? And then from there, you have to then create a document and actually have a conversation with the other side. So all of this are tasks we are completing end to end. So today, there's a little bit of touch required where someone makes an outcome better or does something a little better. But exactly what we're building right now is how do you actually drive this whole thing end to end? Yeah. And we are seeing early signs of that where it's actually live in some customers. And have you seen going back to the defense side and their colossus of information? Have you seen their reaction just in general change? So as an example of that, it's like, oh, these guys contacted me with this. I always need to settle because they probably have like pretty firm rules about this. They don't just like randomly make it up as you go. I would assume they're dealing with this tens of thousands of times, if not more per year. So if I'm Geico, it's like, oh, you demanded this much. Well, my first attempt is going to settle here. But like if their costs go down, maybe that changes. Right. So have you seen any change in reaction of your, you know, not your counterparty per se, but of your client's counterparties? I would say largely still the defense side very much still works on an hourly business model. So they haven't quite caught up to the same pace as our attorneys. So like there's a lot of, I guess, pricing asymmetry here. What defense used to do for this one law firm that we're working with is they would wait. They would push out discovery request dates until a day before Thanksgiving or a major holiday. Right. And then send discovery there because they would know the person would go on vacation and be stuck with all this workload over that vacation. And they wouldn't do a good job at it or would rush it. And now what they use, because it's such a repeated tactic by them, they created an agent on Eve to respond the same day. So the next time this came through, like they responded immediately with the responses and the defense were like, what is going on? Yeah, the tactics don't. And like we're seeing there's so many variants of that that is happening now, which is causing defense to realize, wait, is this this is what happens when the other side has resources? Right. Oh, crap. Right. And that's that's what's fun to see. Well, Jay, this is a fantastic conversation. I learned a lot. Didn't realize there were 10,000 touches every time you went through a case, but really fascinating and delighted to be your partner and bring you to the next the next 10,000 firms. Thank you. I mean, we still have so much more to go. We probably helped a couple hundred thousand clients today and we have hundreds of millions to touch. And I would love to be making a difference in their life every day. So if that's of interest, please come join Eve. Awesome. Thank you. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts and Spotify. Follow us on X, A16Z and subscribe to our substack at A16Z.substack.com. Thanks again for listening and I'll see you in the next episode. As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax or investment advice or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. 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