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

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, right, then the quantity supplied goes up. Right? So if I can make $100,000 by doing something, wow, I'm totally in. But the demand curve is the opposite direction. That's right. 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, right? I can call a lawyer even for contingency, right?

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. This is 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? I was like, uh-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 they want to get called. It's like, hey, I have this accident or I have this issue. But what do 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 percent 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 get 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 that's. On the legal side, but what do 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. Like, 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, right?

So like 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. You know, they have an intake team of 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, he keeps raising the floor, how do I take it from this floor to the next level? And 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. Right, and 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 within 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've worked on. And here are the tactics used before that got you here. Yeah. 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 a, 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, you know, each case, here's how much money I'm spending on the case. But, like, I imagine your primary tool was 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 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 loss 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 in 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, and every problem to them looked 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 and institutions because that's where the budgets were.

For Harvey, you know, really any company, honestly, legal software company 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, right? If you're not driving outcomes for them from day one, you're out. You're not getting renewed. They're gonna curse you out. Anything they can do, they're going to come after you, right? 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 pieces 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.

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?

I guess, how do you think about data? Because I mean, this is always, you know, 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, you know, 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, you know, 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 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 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 their deny, deny, deny plan.

That's how they got smart before. Right. Because they realize 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'm...

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 GEICO's 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 or 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?

and what actually matters for them well 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 of 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. Which is why we can help them make the best decision in every single case and know when an optimal outcome has been achieved.

And it's still, I would say, it's still the attorney's responsibility to push it even further. And I think that is what I meant by data science-like work. Because 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 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, ChadGBT. 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, like, 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 affair 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 the 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 could only handle 100 cases per attorney, now I can handle 500, but in the future maybe 5,000, 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 & 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 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 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?

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. um and i used to joke it was like the tall grande venti model of software selling it's like you go to like any sas company's website this is why you know claude can clone them all so readily they all look the same it's like 79 a month 99 a month 129 a month you know tall grande venti um and it was per seat and like look at a company like zendesk which had two billion dollars of arr are.

When they were last a public company, they were taken private by Premier and Hellman and Friedman. And now they're like, uh-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, Will and Emery. 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 is 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 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. Like everything should be outcome-oriented pricing, but it's hard because there's a data deficiency, if you will, in terms of like, 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. I don't know 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, in your 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 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 said 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 big law or in-house legal. Those are just where the budgets are. So they actually can write basically a blank check for an interim period of time. And the forcing function around how much is this actually worth in outcomes to me is not known, right?

Like, I mean, you know this, like when you go fundraise, you might get hit with like an 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 C. 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 right.

Because 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 could get burned if it's like, I have to now spend 4,000 hours of attorney time. I could lose money on this, which, of course, every single firm, well, actually, as you know, 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 think? 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, what was it? Tall tall grande venti model uh 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 uh you know we're talking like a year and a half ago which is pretty funny that's

early in today's world ai times like dog years times 100 exactly um but that that is that is kind of um 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 eve 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 auto 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're like see we we've talked about how uh plaintiff attorneys like they are their supply constraint not demand constraint or many of them are because they have this infinite influx of of clients that they can't serve because the math doesn't really work in terms of you know cost versus you know cac versus ltv it's the the old-fashioned thing for any business it applies to them as well you know where where are your constraints like what 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 in our 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 Claude 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. Actually, 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 check from Geico. You know, like, has that happened end-to-end? Not yet, but we're close. 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 you 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? 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, uh-oh, these guys contacted me with this. I always need to settle, because they probably have pretty firm rules about this. They don't just randomly make it up as you go, I would assume, because 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 were working with is they would push out discovery request dates until a day before Thanksgiving or a major holiday 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 of 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 here? The tactics don't work. And like we're seeing there's so many variants of that that is happening now, which is causing defense to realize, wait, this is what happens when the other side has resources. Oh, crap. And 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 Eve to the next 10,000 firms.

Thank you. I mean, we still have so much more to go. We probably helped a couple hundred times. thousand clients a day, 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. 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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