What Happens When Both Sides of a Case Use AI?
- AI could make previously uneconomic plaintiff cases worth taking. Eve CEO Jay Madheswaran says lawyers generally need at least $5,000 in fees to accept a case, while 96% of labor-and-employment cases get rejected. Automating intake, qualification, and legal work could unlock that demand; Alex Rampell’s framing is “revenue expansion,” because firms can represent more people.
- One Los Angeles firm increased capacity from about 100 to 500 clients per attorney. Madheswaran credits intensive adoption across intake, handoffs, and settlement preparation. Rampell calls this a “shadow labor market”: the opportunity extends beyond historical legal-software spending into work that previously required additional employees.
- The defensibility argument rests on workflow context and legal information absent from public datasets. Madheswaran says fewer than 1% of cases produce opinions, leaving settlement outcomes and effective tactics largely inaccessible to general models. Even Albert Einstein dropped into a firm “will not be productive for quite some time”; Eve supplies context while, he says, never training on privileged client-case data.
- Small firms could become much larger businesses through specialization and consolidation. On a $25,000 settlement, Madheswaran estimates roughly $8,000 in attorney fees, with half consumed by labor and 30% by marketing. He expects proprietary datasets to help firms look “more like software companies,” expanding narrow expertise nationally or integrating acquisitions faster.
- Outcome pricing fits contingency law, but broader adoption requires predictable delivery costs. Eve shifted away from its initial “tall, grande, venti” subscription approach after learning that customers valued additional clients and outcomes. Madheswaran expects savings to fund more compute and legal work, while preserving a hedge on hourly billing: “I don’t think it’s going to die completely.”
- Stronger plaintiff firms could change defense tactics and reshape how disputes are resolved. One customer answered holiday-timed discovery requests the same day using an Eve agent, defeating a workload-pressure tactic. Madheswaran expects routine exchanges through “agents talking to agents” and, in some areas, automated dispute resolution that assists human judgment.
- Fully autonomous case resolution remains a development target. Asked whether Eve has completed an entire case without intervention, Madheswaran answers, “Not yet, but we’re close.” Cases involve “probably 10,000 back and forths”; engineers are the constraint, and his claim of hundreds of billions of dollars in vehicle-accident value depends on delivering that end-to-end capability.
1. Labor costs exclude clients even when lawyers charge on success
- Madheswaran’s starting point is “legal AI for real people”: contingency firms collect only when clients win, making representation possible without an open-ended $500–$600 hourly bill. More legal work can improve outcomes, but someone must finance that work. Eve aims to cover the path from the first call to settlement, “giving David a slingshot to take down Goliath.”
- Rampell’s market-failure example is a client with $1,000 of damages: a lawyer taking one-third cannot cover the necessary paralegal and attorney work. Contingency removes the client’s upfront bill without making the case economical. As Rampell puts it, “even if I win, I lose,” because carrying costs can exceed the potential return to the firm.
- Madheswaran says lawyers do not take cases yielding less than $5,000 in fees; even at that level, many lose money, with a few big wins carrying the portfolio. His example is a fender bender below the deductible: even if that deductible is $3,000–$4,000, “no lawyer in America will touch that case.” For an individual, he notes, that can mean a lost paycheck.
- In employment law, he describes a 30–45-minute intake call followed by roughly 10 hours researching whether alleged misconduct fits a cause of action. Only then might counsel discover the case cannot produce $5,000; he says 96% of labor-and-employment cases are rejected. Eve answers calls, qualifies prospects against the firm’s criteria, and can begin a demand or preliminary work immediately, changing that screening equation.
2. Revenue expands when the whole workflow gains capacity
- Rampell’s central distinction: “if I use Eve, I make a lot more money for my firm,” because it can accept more cases. “It’s actually revenue expansion.” Madheswaran describes bottlenecks moving from a solo attorney returning calls to an intake team overwhelmed by successful marketing; automating one task is insufficient if work simply piles up at the next handoff.
- One Los Angeles firm increased its load from about 100 to 500 clients per attorney, Madheswaran says. He credits the firm with working hard and using Eve “up to the max”: intake, qualification, agent-managed handoffs, and mediation preparation, including settlement outcomes and previously successful tactics. He pictures the lawyer as “almost a data scientist and engineer,” improving a continuously advancing process.
- Historically, he says, a plaintiff practice needed little more than a cellphone and email; some solos avoided even Microsoft Word. Software had not solved the labor constraint, while institutional defense buyers attracted development budgets. Rampell calls the opportunity a “shadow labor market”: outcomes run into hundreds of billions of dollars, so historical software spending understates the addressable work. His 12-cent-an-hour paralegal is a hypothetical illustrating labor AI could supply.
3. Private case knowledge makes general intelligence useful
- Rampell’s application-layer challenge is direct: why won’t ChatGPT, Claude, or their developers absorb this business? Madheswaran welcomes better models, but “if you drop Albert Einstein into a law firm today, he will not be productive for quite some time.” Intelligence still needs the firm’s working context and the information required to act effectively.
- Madheswaran says less than 1% of cases actually settle and get turned into case opinions; most settle before litigation, leaving essential information outside scrapable public data. Rampell makes it concrete: knowing GEICO actually paid $29,000 on an injury claim matters. An insurer dealing with 100,000 firms sees patterns fragmented plaintiff practices cannot. Rampell points to insurers’ Colossus software as an existing information advantage.
- For Madheswaran, the missing knowledge is practical: an effective demand against State Farm for soft-tissue injuries, the local courts, and opposing counsel’s behavior. His organizing question is “what is the best thing I can do at this particular moment?” That decision repeats throughout a case; Eve is meant to make the context usable at every step.
- Rampell presses on sharing data across separate firms. Madheswaran distinguishes privileged cases—“we don’t train on that data ever”—from tactics attorneys already exchange through continuing legal education. Eve hires attorneys and tracks case success; its Auditor reviews every page of every case overnight for issues an ideal attorney would catch. He says “almost every single case has missed information,” explaining the value of comprehensive review.
4. Stronger plaintiffs change tactics and expose court bottlenecks
- Rampell’s pushback is that insurers and defense firms will acquire AI “superpowers” too. Madheswaran accepts a world where 99%, maybe 99.9%, of representation work is AI, while retaining a human difference in client understanding, local relationships, and advocacy. Institutions still have money and time as weapons. He thinks routine exchanges will become “agents talking to agents”; some Eve customers already spend more time preparing for trial.
- One observed change is tactical: a defense firm repeatedly sent discovery just before Thanksgiving or another major holiday, expecting the plaintiff team to rush or sacrifice vacation. The plaintiff firm created an Eve agent that answered the same day. Madheswaran’s reading of the defense reaction: “this is what happens when the other side has resources.” He says defense still largely bills hourly and has not matched plaintiffs’ pace.
- Rampell’s court-capacity concern comes from his own Wells Fargo dispute: after four hours of frustration, he told Codex/ChatGPT, “Sue Wells Fargo.” He says four hours later it had filed the suit and found a process server, but the court date was in February. Lowering the cost of initiating legal work leaves adjudication as a bottleneck.
- Madheswaran thinks it is “inevitable” that more disputes move outside courts, extending existing channels such as veterans’ committees, the EEOC, mediation, and arbitration. In “some pockets,” he expects “ADR, automated dispute resolution,” using AI-assisted neutral parties to assemble historical facts and accelerate decisions. He does not think judgment itself will be replaced; people must still address biases that might exist in those comparisons.
5. Software economics could support specialists and rollups
- Rampell asks whether a firm handling 100 cases per lawyer, then 500, perhaps eventually 5,000, could become a billion-dollar business. Madheswaran thinks firms will look “more like software companies.” On a $25,000 settlement, he estimates roughly $8,000 for the attorney: about half goes to labor, 30% to marketing, and the remainder may be profit. That structure makes reinvestment difficult when improvement means hiring a better attorney.
- The prospective change is a proprietary dataset that improves results in a narrow field. Madheswaran expects specialization to deepen from employment or intellectual property into soft-tissue injuries with particular fact patterns. Targeted advertising might then beat Morgan & Morgan’s broad billboards. Rampell draws out the expansion path: get good locally, then take that competence nationwide; Madheswaran agrees.
- The opposite path is consolidation. Madheswaran says customers on the scale of Morgan & Morgan are buying other firms because Eve can shorten integration around the client’s desired legal outcome. By handling operational and workflow changes, the platform reduces painful reintegration and can accelerate the point at which an acquisition becomes worthwhile.
6. Outcome pricing requires knowing what delivery will cost
- Rampell notes that contingency firms already sell the outcomes SaaS vendors are now trying to price. Madheswaran admits Eve initially copied the “tall, grande, venti” subscription model: “we didn’t know any better.” Customers cared about serving more clients, forcing an early shift toward outcome-based pricing, roughly a year and a half before the conversation.
- Rampell’s defense of hourly billing is information asymmetry: clients may not articulate their needs, and scope can change. Madheswaran agrees that a new case might require 10 or 100 hours before anyone knows. His broader requirement is to infer, from the facts, how much compute an outcome needs—through better data and better execution—so legal work can be priced and delivered more predictably.
- Madheswaran’s hedge matters: “I don’t think it’s going to die completely,” he says of the billable hour. Some legal work reveals its value only years later. Elsewhere, predictable outcomes permit amortized costs, and labor savings can fund more tokens and more useful work. The intended cycle is better outcomes and more revenue, with savings reinvested in serving clients.
7. End-to-end autonomy remains an engineering problem
- Asked what limits growth, Madheswaran says benchmarks grading whether one task went “mostly okay” miss the problem. Eve needs reliable outcomes across long-horizon workflows, built separately for each case type. There is still “a decent amount of human touch needed per case,” although he says that is falling month over month. The main constraint is engineers.
- Rampell asks the essential test: has Eve autonomously answered the phone, onboarded a client, and obtained the insurer’s check end to end? “Not yet, but we’re close.” Madheswaran estimates a single case involves “probably 10,000 back and forths.” Earlier, he describes matters lasting six months to a year, making reliability over extended sequences central.
- His concrete example is medical-record collection: outbound calls to insurers and healthcare providers take two weeks today, he says. Eve’s voice agents make those calls, sometimes encountering other agents and learning to get past them. Record collection, document creation, and opposing-party conversations are being automated, but some human intervention remains; early versions of the broader workflow are live with customers.
- Madheswaran says completing vehicle-accident cases end to end would unlock value in the “hundreds of billions of dollars,” conditional on delivering that capability. He says Eve has helped “a couple hundred thousand clients” so far, against an aspiration to reach hundreds of millions.
Full transcript
Historically, plaintiff law really didn’t need more than a cell phone and an email address. No software really solved its core problem, which is the labor constraint.
Most people think of AI as, “Oh, you’re going to fire everybody and cut costs.” And it’s like, “No, actually, if I use Eve, I make a lot more money for my firm.”
People can’t pay $500 or $600 an hour on a blank check for however long the case might take. What Eve is aiming to do is handle that whole thing end to end. One firm in LA went from managing about 100 clients per attorney to five.
Wow.
That is the type of thing that’s possible.
Why is Eve better than just 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 Eve is solving. Why won’t that person be productive? It’s due to a number of things. One is—
Hi, everyone. I’m Alex Rampell, a partner at Andreessen Horowitz, and I’m very happy to be here with Jay from Eve, co-founder and CEO. Everybody knows a lawyer, right? Everybody knows law. But most people, especially in Silicon Valley, when they hear “law” and “legal,” think about corporate law: really big, supposedly white-shoe law firms, where you go to Harvard Law School and bill $2,000 an hour.
But there’s another side of law, which is actually bigger and more distributed. I guess we’d call that plaintiff law. Every time you drive on 101, you see all these billboards. Maybe we can start with what Eve is. What form of law and legal AI do you focus on? And maybe tell us a little about the industry in general, because I feel like most Americans are familiar with it, but they don’t necessarily realize it. Especially for people here in Silicon Valley: they’ve heard of Wilson Sonsini, but they haven’t heard of Morgan & Morgan, right? And Morgan & Morgan is probably a lot more profitable than Wilson Sonsini. What is plaintiff law, and how would you explain Eve in your own words?
1. Legal AI for Real People
Absolutely. First, thank you for having me here, Alex. It’s always fun to talk about Eve. What Eve is, is legal AI for real people—people like you and me, not institutions, not in-house legal teams, not the people who already have all the resources. How do we provide legal services to people who otherwise can’t afford them?
That’s how the plaintiff law industry really came about. You talked about how Wilson Sonsini might charge $2,000 an hour, and that’s really the business model. Lawyers’ time is expensive, and you’re trying to point lawyers toward more and more expensive time. The same is true for most lawyers. They have a lot of bills to pay, and they need to make money. Today, the more work you put behind a legal matter, the better you can represent the facts and the better the outcome. That’s the state of the world we live in today.
To account for this, lawyers understand that people can’t pay $500 or $600 an hour on a blank check for however long the case might take. So the plaintiff industry came about by working on contingency. That means they only get paid when they win the case for the client. This is what’s allowed them to have any sort of level playing field for people against institutions.
What Eve is aiming to do is handle that whole thing end to end: 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 work purely with AI and give it to lawyers to amplify the outcomes they can provide? That’s what Eve is doing, and we’re really arming—think about giving David a slingshot to take down Goliath. That’s what we’re doing.
2. The Labor Bottleneck
What I find fascinating about this is, I kind of think about Econ 101, where you have a supply curve that goes up and to the right. What does that mean? Remember, there’s price and quantity. Here’s quantity, and here’s price. As the price goes up, the quantity supplied goes up.
Mm-hmm.
Right? So if I can make $100,000 by doing something, wow, I’m totally in. But the demand curve goes in the opposite direction.
That’s right.
So price and quantity go this direction. The number of units I want—actually, I should say, this is quantity, and this is price here. As price goes down, quantity demanded goes up considerably.
If I think about applying this to law, what if I have $1,000 in damages? I can call a lawyer, even on contingency, but they might not want to take my case, because if they take a third of the outcome, they want a bigger case, and it’s going to require a certain amount of work. AI liberates these market failures to a certain extent. You mentioned giving David a bigger slingshot. A lot of times, David just—well, number one, if I have $1,000 in damages, I certainly can’t pay $1,200 an hour for a lawyer, so I’m out.
Enter contingency law. The problem is that the settlement might not be big enough, so the lawyer might want to serve me, but they have paralegals to pay, and so on. But if the software can do the work, the market opportunity is so much bigger. You can actually deliver justice for a lot of people who otherwise weren’t priced out of it—but how are you priced out of contingency? It’s not really in a lawyer’s interest. They want to serve the 1,000 customers they get, but they can’t. They have to focus on the biggest ones, to the detriment of the smaller ones, because it’s to the right of that equilibrium point. I don’t know if you agree with that or how you think about it.
That is exactly right. I think that is the actual market problem we have today. 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, right?
Right.
The best and worst of us come out at that 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 one-third of our government. It’s for this reason.
Yeah.
Today, what’s happening is that because lawyers still need to get paid, the work is still bottlenecked on legal labor. Today, if a lawyer doesn’t make at least $5,000 in fees off a case, they don’t take it on.
Yeah.
That is the market dynamic today. Even at $5,000, they’re losing money on a lot of cases. They’re really banking on a few cases paying out very large amounts.
Because 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. Think about how most people here have been in a car accident, a 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.
Right.
Even if the deductible is $3,000 or $4,000, to an individual, that’s the difference between a paycheck being gone and not. And there’s no representation they can get for that.
Right.
The same thing applies, and the reason is that we have to understand it from their side, too. Let’s say you’ve been getting harassed at work and your employer could stop it. In the hospitality industry, for example, 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 calls, the lawyer on the other side has to pick up and field that call. That’s about 30 to 45 minutes of work. Then they have to do legal research because, in employment law in America, pretty much everything is at will, and you have to tie a problem to a protected class of some kind. That’s called a cause of action. You have to tie it to a cause of action, and that work requires them to spend 10 hours researching your case law and the facts, going back and forth to ask follow-up questions, and seeing if you qualify. After all that time, they might still realize, “Hey, this doesn’t even make me $5,000.”
Yeah.
So that is why 96% of cases on the labor and employment side, for example, get rejected.
So you can never find anybody to represent you.
You can’t.
Unless you come out of pocket. In many cases—
That’s exactly right.
—people don’t have money to come out of pocket, so—
That’s exactly right.
—it just never happens.
That’s exactly right. So you just take it unless something really egregious happens. That is the current state, and it’s all bottlenecked on legal labor.
Yeah.
This is what Eve is meant to do: take what used to take 10 hours and make it immediate. A call comes in, Eve answers it and automatically uses its insights about the law firm to determine whether the lawyer should take the case. Then it hits the ground running, preparing a demand or doing the initial preliminary work. That completely changes the economics of that type of case, and we’re still at the very beginning stages. Eve is getting more and more capable of handling outcomes end to end over a very long horizon.
Yeah.
These cases take six months or a year to launch, and there are probably 1,000 actions back and forth along the way. As Eve’s accuracy gets higher and higher, this long horizon becomes possible. The more this becomes possible, the more complicated cases can be handled. Now all these people without representation get representation.
Yeah.
If you really ask yourself, how many times in your life would you have asked for legal help if it weren’t a friction point? That number is way higher than we think.
3. Expanding Law Firm Revenue
Yeah. So, it’s a funny story. This is a true story. I was in Blue Bottle, a little coffee shop in Los Altos, explaining Eve to somebody probably nine months ago. Most people think of AI as, “Oh, you’re gonna fire everybody and cut costs, and it’s all about cost savings.” But actually, if I use Eve, I make a lot more money for my firm, and it’s not because I’m cutting costs. It’s because I can take on more cases. It’s revenue expansion.
I was explaining this as well as an outside investor can, so not as well as you probably would. We were talking about many topics, but Eve came up, and this guy comes up to me. He looks a little angry, and he has a big dog. I’m kind of afraid of big dogs, and he says, “What was that company you were talking about?” I thought, “Uh-oh, is he gonna get mad?” He says, “I’m a trial attorney. I wanna 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. Maybe walk us through the dynamics. Everybody has driven on I-95. I-95 is the corridor that goes from Florida all the way up to Maine or something, up and down the Eastern Seaboard. I’ve driven almost all of it, and I feel like half the ads are for trial attorneys, plaintiff law. They’re advertising because they want you to call: “Hey, I have this accident or I have this issue.”
But what do the economics look like? This is why I think Eve is so fascinating: I have to turn down 90% of the leads I’m getting, I assume, right? What do 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 walk us through a before and after, because you’re not a cost-savings play for lawyers. You’re a revenue-expansion play. That’s from 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 forget about the people behind it and the amount of work every single call actually takes. That’s what happens today, and that’s what Eve is there to help with. The math on the law firm side is very simple: the more people you represent, typically speaking, the more money you make.
But you can take on more people, and you’re honestly denying and not taking on many cases because they’re too expensive to take on. The demand from their perspective isn’t really constrained. It’s really the supply of labor.
Yeah.
Do I have enough people inside to actually service that problem? To make things more complicated, different firms are in different realms of problems where the bottleneck keeps shifting. A small firm might have one attorney and a case manager or some sort of office manager who fields the initial call and notes it down. Then the lawyer responds in their free time.
Right.
They’re running chaotically, running around. Then there’s the next level, where they find a way to systematize it. They have an intake team, like a call center somewhere, that handles intake, and now that becomes a new bottleneck. When you increase your marketing spend—say you look particularly attractive on that billboard and a lot of people are calling in—suddenly that team is overwhelmed, and you’re limited again by how many people you can represent.
Right.
This is the daily challenge these small businesses are dealing with. They’re small businesses, not massive enterprises. They want to represent individuals, and everyone there went to law school, not business school. They want to be there for the people.
We’re basically consolidating all of that into the Eve platform, so they’re pulled in only for what they need to do. Their lawyer insights and their particular insights on how to take a case—Eve keeps raising the floor. How do I take it from this floor to the next level? That’s where I believe all lawyers should spend time: talking to their people and helping get client outcomes.
Well, this is kind of the market failure point. I could serve all 5,000 leads that came in if only I could hire a paralegal for 12 cents per hour, or whatever the token cost is. But I can’t.
Mm-hmm.
So there’s no labor market that could actually function, but with AI, now I can. Do you have anecdotes of a before and after? Like the Hair Club for Men: “Here I am before, here I am after. I have a nice head of hair.” What does that look like for your best customers that you work with? I imagine the revenue transformation is pretty significant.
One firm in LA went from managing about 100 clients per attorney to 500.
Wow.
That’s the kind of thing that’s possible. To their credit, they worked really hard to achieve this. They used Eve to the max, all the way from intake—fielding the call, doing qualification, automatically removing the relay problem of passing things from one attorney to another—
Right.
—to a case manager. All of that is now handled within agents in Eve, all the way to settlement, where it actually briefs you before you go to a mediator discussion. It 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.
That’s what the future looks like: truly moving the case forward continuously, while you help it do a better job than it could by itself. I think that’s the future of law, where you as a lawyer are going to look more like a data scientist and engineer, engineering something to make it better and better. That’s a shift the top law firms on Eve mentally go through.
4. The Legal AI Advantage
Yeah. I think of it this way: if you look at your average law firm where they don’t really know AI, this is an interesting take on the world of AI-enabled applications in general. What was the software stack for law before? If you’re a big firm like Wilson Sonsini, probably the most important thing is your time tracker.
Mm-hmm.
Right?
That’s right.
Because you’re billing by the hour. If you’re in contingency law, your time matters, but you’re not billing your customers for it. You probably need to know, for each case, how much money you’re spending on it. But I imagine your primary tool was Microsoft Word.
This is how VCs would have gotten this industry wrong before. They’d say, “Oh, the software market for plaintiff law is small. They all buy Microsoft Office. Microsoft Office is kind of expensive, so the software spend is in the tens of billions of dollars a year,” or something seemingly comically small. But wait a minute: the outcomes they deliver are in the hundreds of billions of dollars a year. They can’t deliver more outcomes because they’re constrained by labor, and they can’t hire labor for 12 cents an hour because it doesn’t exist.
It turns out the software market is kind of like this shadow labor market, and it’s massively bigger than anybody would have expected. It’s always a weird thing, because you can’t say the software market is small when you’re a legal software company. People know Harvey, or they know corporate law or e-discovery tools that have been around. But what was the main software stack before Eve entered? Was it just Microsoft Word? What did I need in order to go into business? I graduated from law school, and I want to be in this particular subsector of the field.
What was my software stack?
This is the unfortunate thing about plaintiff law and institutions: historically, plaintiff law really didn’t need more than a cell phone and an email address. Honestly, even Microsoft Word—some people in solo practices wouldn’t buy it for cost reasons—
Typewriter?
Other reasons. No, it’s because you actually don’t do that much redlining. It’s a trust-boundary situation, right? One side is in opposition to the other side.
Right, right, right.
So you’re not really collaborating—
Yes, yes.
—in the same way that you are when you’re doing contract review or something along those lines. So that was kind of it. 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. Because they have labor and they’re good at managing it, they found a way to solve everything. Every problem looked to them like something to solve with labor, and that’s how they’ve grown up.
As a result, a lot of resources in software went toward defense institutions, because that’s where the budgets were. For Harvey, and really any company—honestly, the vast majority of legal software companies today are on the defense side, because that’s where the budgets are.
Right.
Right? That’s what’s easy to build for and easy to get money for. On the plaintiff side, these are small businesses 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. They’ll do anything they can to come after you, and that’s what’s made things so difficult.
But what we’ve realized is that we know their core problem and their incentives: they want to represent more people, and they want to win. We can do that now. The beauty of software today is that once you do a task manually—even tasks that involve crunching new pieces of data and transforming them, which is what AI is really good at—you can 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 it 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 handle it. Now one smart person can handle, like we talked about, 500 different cases with very different facts and situations. How do you even keep all of that in your brain? It’s hard, right? But now you don’t have to.
One of the things a lot of founders are thinking about right now at the application layer is, “Uh-oh, maybe I’m roadkill from the big guys,” right? The labs that produce the intelligence might tackle my space next, and I’m toast. There are many ways of defending against that. But “defending” kind of sells it short, because if you have a network effect or data that nobody else has, you can deliver better outcomes.
Who cares if everybody uses ChatGPT or Claude behind the scenes, or on their own? You’ve thought about this a lot: why is Eve better than raw intelligence? And how does it get better as more practitioners use the product?
We’re betting on these models getting better and better, and our value is exactly that. If you have 1,000 Albert Einsteins to work with on litigation, or the best attorney ever to do every single task, we’d take it. The problem is, if you drop Albert Einstein into a law firm today, he won’t be productive for quite some time. That’s a general problem Eve is solving.
Why won’t that person be productive? There are a number of reasons. In plaintiff law, the vast majority of data is actually non-scrapable. Less than 1% of cases actually settle and get turned into case opinions.
Right.
The vast majority settle pre-demand or pre-litigation, and some even before that, where it’s just a negotiation of, “Hey, this is how I was wronged. Please fix it.”
To make that concrete, it’s like I’m in a car accident and I’m not at fault. The other side, if you will—the insurance company—is like, “Oh, you weren’t that hurt. We’ll give you a dollar,” right?
That’s exactly right.
They always try to deny, deny, deny. Rule number one for an insurance carrier is deny. Rule number two is deny. It just goes on and—
That’s right.
Those are all the rules of insurance carriers. So now I hire a lawyer to get what I’m owed, because I’m actually 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 a case, it doesn’t go to an actual trial, but you know—
That’s right.
—right? GEICO actually paid $29,000. That’s very useful information, I assume.
That’s right, because the insurance company is dealing with 100,000 different law firms.
So they have the shared community—
So they have—
They know all the cases, but because—
Exactly.
—it’s sharded across all the different local firms, they don’t know exactly GEICO’s every single move.
That’s exactly right. They even have ominous-sounding software like Colossus, which tracks things. They try to say, “A broken thumb, this is how much we think it’s worth,” which is a hard thing to do. In their defense, it is hard to do. But they’re also saying, “This is how much we can get away with giving them,” irrespective of that individual’s actual needs or particular situation. That’s what the legal system is meant to fix. That’s what it’s there for.
Right.
What’s happening now—and this is the interesting bit and the challenge—is that if you Google, “How do you write an amazing demand letter against State Farm for soft tissue injury cases?” that information doesn’t exist anywhere today. Even for a new paralegal joining a plaintiff firm, this is something they have to learn. On top of that, it gets more complicated because, in a local jurisdiction, the local environment, the court systems, and your opposing counsel all behave a little differently. That context matters, too.
What Eve is doing is turning this historically incredibly difficult-to-use, multidimensional information into an answer to the question: what is the best thing I can do at this particular moment to improve the outcome of the case?
Yeah.
That same question is repeated thousands of times during a case, and a human brain just isn’t capable of keeping all of that in mind. AI is. That is the type of data we help build for law firms, and they’re seeing immediate value from it. The first place they see value is intake: who do I even take on, and who am I good at representing? Then we can start there and keep getting better.
I imagine these aren’t giant firms, right? If I’m a lawyer in New Jersey with a four-attorney practice, and there’s another lawyer in Arizona with a seven-attorney practice, their counterparties tend to be State Farm, GEICO, and so on. At the limit, it’s actually fine to share information.
How do you think about data? This is always hard for companies when they’re getting off the ground: “No, this is my data.” But there’s also a give-to-get, I assume. I work with a dental AI company, and the dentist in Iowa can’t serve patients in Florida, but they want to learn from the collective actions of each other. How do you think about data sequestration? 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 amplified them with software. That’s our stance. For their own cases, they want the information to be very private. That’s important by law: it’s attorney-client privilege, and we never train on that data.
Yeah.
However, attorneys also share knowledge. They travel, attend CLEs, and share tactics with each other about how they went up against State Farm’s X and Y defense, because State Farm repeats that defense across the board. I’m not picking on State Farm; anyone is fair game here, but that’s what they’re already doing.
We hire our own attorneys and track success rates of cases on our platform. We want to help. If you’re using Eve, you should have more success. That’s what we track. We have a product called Auditor, which analyzes every single case, through every single page, overnight, and looks for situations that a perfect attorney would catch every time.
Across the board, unfortunately, the vast majority of cases—almost every single case—have missed information. And now that’s no longer a thing.
5. How AI Changes Legal Practice
Yeah. Maybe talk about the future and where things go. On the one hand, I can imagine that one of these days GEICO is going to get a little bit smarter. You see their “deny, deny, deny” plan. That’s how they got smart before, right? They realized it’s an adversarial system.
I lost my house in a fire, and I’m going to claim I had a Picasso in there. They’re going to think I’m claiming I had a Picasso, so they’re just going to deny the claim. Deny, deny. Each party is kind of fighting the other, but they’re going to get superpowers.
You see this playing out a little bit with Muse and all the consumer agents. I want a reservation at a restaurant that’s impossible to get, and they have a human answering the phone. I can DDoS them now, when I have to pay one penny per hour or something.
Mm-hmm.
Eventually, they’re going to realize they’re getting DDoS’d and prevent that. How do you think about your clients’ adversaries? How are they adapting to a world where it was great for GEICO to say, “Hey, you have $2,000 of damages,” and the consumer says, “Yeah, I did have maybe $2,500 of damages,” but they never really had to worry about that before because of the quantum?
Now, unfortunately for them, but fortunately for the Davids of the world—people who are actually aggrieved and have been victims—they can fight back, and you’re powering that. That’s one thing. But you also mentioned long-horizon agents. What does the practice of law look like when a lot of the work can be done by AI? I think you framed attorneys as almost the data scientists of the future.
What does the adversarial process look like? What are State Farm and GEICO using, potentially as a result of you entering the scene? And, as a big question, how does law evolve when you’re manipulating words, finding facts, and doing all this work where humans aren’t as important? They obviously have an important role in shepherding the case to completion, but what does AI do versus not do?
Ultimately, my framework for thinking about this is that an individual is going to need representation. Who does the work on that 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, and we do believe people are going to make a positive difference to the outcomes of the case.
What you have on the defense side, or really the institutional side, is what’s always happened: they have more resources, more money, and more time, which is another quite powerful weapon they have.
Yeah.
Individuals are in debt to pay their fees, and that is a very powerful tool they have. That’s a strength they’re working with, and they’re trying to rely on centralization and standardization. On the defense side, you have an attorney who is fighting your case and pushing them to get to litigation.
I think a lot more cases are going to have teeth. All the routine back-and-forth is going to happen through agents talking to agents. It’s a crazy future world, but I think that’s where we’re headed. The difference-maker is what the attorney understands about that client, that set of facts, and the local environment—who they’re going up against in that defense firm—and how they use that insight to make a difference for their client. I don’t think that ever goes away.
In fact, it’s something we’re seeing already: many customers on Eve are choosing to spend more time on their trial work.
Yeah.
Because it enables that. Previously, going to trial took down your entire firm.
Right.
Suddenly, you’re spending all your time doing trial work, trial prep, and interviewing juries.
You want things to settle.
Exactly.
It’s more of a settlement motion—
That’s exactly right.
—rather than the default.
Instead, I think things are moving more toward real advocacy. How do I actually make our point known? My client has their back against 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 also the data science side of what you’re doing, with this giant data set that’s probably never been accumulated before. As you mentioned, all these things are so bespoke. There’s no communal repository for all the settlement amounts. I’ve seen this with litigation finance a little bit. If I’m a lawyer and I’m a trial attorney, and I’m not getting paid by the hour by you, my client, where do I pay myself, my staff, my office rent, and everything else?
There are companies that will show up and say, “I will fund this case.”
That’s right.
Right? They’re funding the case because they’re counting on you winning. They’ll do all sorts of clever things, like, “Here’s the judge, and here’s this.” They’re using data. I think those guys have been very data-science-forward. But historically, this data just never really lived anywhere.
Now that it does, you can make smarter decisions as an attorney: Do I take it to trial, accept the settlement, or push back? GEICO offered me $12,000. Should I push back and fight for $15,000? Should I take it to trial and try to win $100,000? How do I make those decisions?
That’s exactly right. That’s why we can help them make the best decision in every case and know when an optimal outcome has been achieved.
Yeah.
I’d still say it’s the attorney’s responsibility to push it even further. I think that’s what I meant by data-science-like work, because—
Right.
—you’re using the power of software to do work you never even thought to do, to improve the outcome.
Where do you think the legal system goes? I was having some trouble with Wells Fargo, and I thought, “You know what? I’ve tried for four hours to do this. I’m just going to sue them.” So I went to Codex, you know, ChatGPT, and said, “Sue Wells Fargo.” Four hours later, it had sued Wells Fargo. It actually found a process server. I got the notice of service. We’re going to court, but the date is in February.
A similar thing is happening with patent law. Before, it took so much work to file a patent. Now it takes less work, but you still have the USPTO, which is the bottleneck. If you were to prognosticate, where does the legal industry go now that AI is becoming table stakes? You’re part of that, obviously, for plaintiff law. If you think about the entire practice of law, how does it change if you fast-forward five years? What does it look like? What’s similar, and what’s different?
Most likely, it’s inevitable that we’re going to have to create systems where not everything goes to the court system. That’s already a framework used in law. For some types of Veterans Affairs cases, matters go through a different committee. Even labor and employment cases go through the EEOC in many instances before they go to court. Employers have also figured out different ways to mediate and have arbitration that doesn’t necessarily go through the court system.
Right.
This is the framework that naturally evolves, and I expect it to happen more and more. The change is that, for some pockets of the system, we’ll probably use some version of ADR—automated dispute resolution—where AI-enabled mediators or third parties with a neutral view of both sides use AI to speed up how they reach a judgment.
I don’t think the judgment itself will really be replaced. What they’ll get is a set of facts showing, historically, here’s how this happened and here’s how that happened. It’ll be up to them to remove any biases that might exist. I think we’re going to spend more and more time on that side of things.
Do you think small law firms get bigger? If I could only handle 100 cases per attorney, now I can handle 500, and in the future maybe 5,000. Why limit my office to a very small New Jersey location? Maybe I should go broader.
You’re going to have larger, almost corporate-like law entities. I think the biggest trial attorney firm is Morgan & Morgan. Is that right? They have billions of dollars in revenue, but your average firm is quite small.
Mm-hmm.
You could imagine that, powered by Eve and with all the changes we’re talking about, the small firm could actually become a billion-dollar revenue business. It’s kind of like venture outcomes versus what you’d call a lifestyle business. You were a VC once upon a time. You know that term: it’s a somewhat pejorative term for making profits. Is that a reasonable take—that some of these small firms can actually become very large? Obviously, you can’t go public as a law firm for now. Maybe in Arizona or something you can. Do you think there’s a chance for some of these local mom-and-pop stores, if you will, to become very large institutions?
I think the transformation that’s going to happen is that a lot of these law firms are going to look more like software companies. They’re finally going to participate in the software revolution that’s been happening for the last 30 years and that they’ve been left out of. If you dive deep, 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. About half of that goes toward labor spend, 30% goes to marketing, and the rest maybe is profit. That’s kind of the business as it exists today.
Yeah.
Because of that business model, it’s so difficult to reinvest in servicing your next client better. The only way you can really do that is by hiring a better attorney.
Right.
What changes is that they can now accrue a database and dataset that’s unique to them, and that gets them better results than their competitors in a subset of the law. This is specialization. Historically, the industry already went through that. Thirty years ago, there was your neighborhood lawyer, who handled everything from employment cases to IP to whatever.
Right. DUI.
Yes.
Yeah.
Exactly. And now we have specializations in practice areas. You have someone who’s really good at IP, someone who’s good at employment, and now it’s getting even more specific. Someone might be good at, let’s say, nursing, birth defects, or something along those lines. I can imagine it going another level, where someone gets really good at soft tissue injury cases involving specific fact patterns. Advertising for those cases might be a lot more cost-effective than a larger firm like Morgan & Morgan just showing its billboard everywhere.
Right. So get good at something locally and then expand across the entire country because you have such high competence in that one field.
That’s exactly right. I think we’re going to see that type of specialization, and I think we’re also going to see the opposite. Some of the large firms—we’re working with some on the scale of Morgan & Morgan—are coming together. The ones that got big are going around buying other law firms because they realize that with Eve, they can very quickly consolidate. What used to be a very painful reintegration process can now be done based on exactly what the client wants: a legal outcome. Eve is made just for that.
Yeah.
By doing that, they can largely work around a lot of the change management, workforce changes, and operational changes, because Eve handles a lot of that for them. They can speed up the time it takes to make that acquisition worthwhile.
6. Pricing Law by Outcomes
The funny thing is that there’s this movement underway toward outcome-oriented pricing.
Mm-hmm.
Software used to be priced per seat per month. I used to joke that it was the tall, grande, venti model of software selling. You go to any SaaS company’s website—this is why Claude can clone them all so readily—and they all look the same: $79 a month, $99 a month, $129 a month. Tall, grande, venti. It was priced per seat.
Mm-hmm.
Look at a company like Zendesk, which had $2 billion of ARR when it was last a public company. It was taken private by Permira and Hellman & Friedman, and now they’re asking, “How many seats do you need?” Maybe zero. We need to deliver outcomes. Everybody in the software world, especially a lot of AI companies, is saying, “We deliver outcomes; we charge for outcomes.” The interesting thing is that the form of law you focused on was outcome-oriented from the very beginning. But there are other types of law that aren’t outcome-oriented, where I’m sure clients would much prefer outcome-based pricing. Sometimes it’s tricky. I have a trust and estate attorney at McDermott Will & Emery. She’s very good, and she’s so expensive. I guess my outcome is my death, so I don’t know if I want that. But you’d prefer to say there’s a fixed cost.
In their defense, the reason to charge by the hour isn’t so much to rip off the client; 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 other forms of law should probably look more like plaintiff’s law. They should have outcome-oriented pricing as well.
Mm-hmm.
Immigration law should be outcome-oriented, too. Everything should be outcome-oriented pricing, but it’s hard because there’s a data deficiency in figuring out how I’ll win this case on behalf of the defendant. You could probably expand well beyond plaintiff law. I don’t know if you agree with me, but how do you think about law in general changing? I feel like plaintiff’s law was ahead of everything we’re seeing right now. Everybody wants outcomes; nobody wants to pay for the ingredients or the inputs. This was probably the only field of business where it was always outcome-oriented. Shouldn’t other parts of law work that way?
That is our exact belief as well. The hard part is that it’s difficult. When you’re on the defense side or even the plaintiff side, the question with a new case is whether it’s 10 hours of work or 100 hours of work. In many cases, you really don’t know until you take it on. For plaintiffs, that’s why we had to go so deep into each practice area to achieve outcomes. We were doing what’s now called long-horizon agents last year. That’s just what was needed to drive results, and now it’s getting better and better at actually driving legal outcomes.
Ultimately, I think what’s needed to democratize law is that, from a set of facts, you need to know how much compute you need to arrive at an outcome. That happens through aggregating and making better use of data, and through better use of compute to achieve that outcome. We’re doing both. That’s why we’re laser-focused on outcomes, and we want to drive outcomes.
This David-versus-Goliath thing is happening everywhere. It’s not just in big law or in-house legal. Those are just where the budgets are, so they can basically write a blank check for an interim period. The forcing function—how much is this actually worth in outcomes to me?—isn’t known. You know this: when you go fundraise, you might get hit with a $100K check. What’s the exact outcome of that? It’s very hard to know what the value is, but that’s the only way they can price today.
Right.
That’s because they don’t know what the expected value of their work actually is.
Well, that’s the asymmetry as well.
Exactly.
I don’t know. You need to hire a lawyer for your Series C, and what does that mean? It could be very simple, or it could be very complicated, so it’s very hard to have a flat rate.
That’s right.
They could get burned in the low direction. They can’t get burned in the low direction, right? It’s, “I charged you $25,000, and I spent an hour on this.” But they could get burned if they have to spend 4,000 hours of attorney time. They could lose money on that. 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.
That’s exactly right.
Obviously, that’s a little different from plaintiff law. How do you guys charge? How did you think about it? I imagine that when you started the business, you didn’t know exactly what you were going to charge or what type of customer you’d charge.
I imagine your thinking has evolved on this as well.
Absolutely. Weirdly enough, from day one, we started with the “tall, grande, venti” model.
Tall, grande, venti, yes.
Venti model.
Yes. Yeah.
That’s what we started with because we didn’t know any better, right? As we dug into it, we realized 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 on. We’re talking a year and a half ago, which is pretty funny to call early in today’s world.
AI time. Yes, like dog years times 100. Yes.
Exactly. But that is kind of what happened to us, right? There’s so much room to grow. We talked about that value diagram: a third goes to attorneys, and half of that is labor. That’s half they don’t have to spend anymore, right? So how do you actually turn that into something more useful?
The best way to get more useful work is actually to spend it, weirdly, on more tokens and more work that Eve can do to make more money for your firm. That is the cycle we’re in today, and a lot of the market dynamics helping us come from exactly this. We believe the billable-hour model isn’t going to die completely, but I think it’s going to go the way of the seat-based pricing model. For some subset of law, that’s probably the best way to charge for the work, because it’s very difficult to know the value until an outcome many years later. But for a lot of it, that’s not true anymore. For a lot of it, you actually know what the outcomes are, and you should be able to bring your work down to an amortized amount and deliver that back. That’s what we’re betting on. This is why we focused on delivering legal outcomes from day one, end to end, in such a way that it’s 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 are supply-constrained, not demand-constrained. Many of them have an infinite influx of clients they can’t serve because the math doesn’t really work in terms of cost versus CAC versus LTV. The old-fashioned thing for any business applies to them as well: Where are your constraints? What holds you back from growing faster? You’re obviously growing incredibly fast. What are your rate limiters? What inputs do you need to grow faster as an output?
It’s really fascinating because a lot of the legal benchmarks—even benchmarks that you share publicly, that Anthropic and OpenAI, many of whom we’re working very closely with, are working on—care about almost a single outcome: Here’s the task; did it do mostly okay? The world is now moving into agentic work. For us, the only thing that ever mattered was the agentic outcomes.
Right.
Now that’s getting more and more attention. The end outcome here is that, with the technology and processes we have today, there’s still a decent amount of human touch needed per case. But by doing more work, we’ve been drastically reducing that month over month. In our industry, we need to do that per case type. For every single case, we’re learning it like a science: How do you actually resolve this case, and how do you build a mini attorney brain that can crunch all these data points toward that resolution, drive it across the board, and work with all the tools it has access to, including Claude, to drive that outcome? That’s a really hard problem.
We’re largely limited by engineers at this point. We have a limitless number of things to do to drive this forward. The other fun part is that we have demand. The moment we’re able to deliver on, let’s say, motor vehicle accident cases end to end, the amount of value unlocked for the world 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? Like, answer the phone, onboard the client, and get a check from GEICO. Has that happened end to end?
Not yet, but we’re close. That is why we need the engineers.
Yes.
To put things in perspective, a single case has probably 10,000 back-and-forths.
10,000?
Something like that.
Wow.
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 you have to make outbound calls to insurance companies and healthcare companies to get hold of the records the client already had. That takes two weeks today. With Eve outbound agents, we have voice AI that can make the outbound call. 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. That’s one step that’s needed.
From there, you have to create a document and have a conversation with the other side. These are all tasks we’re completing end to end. Today, there’s a little bit of touch required, where someone makes an outcome better or does something a little better. But what we’re building right now is how to drive this whole thing end to end.
Yeah.
We’re seeing early signs of that, and it’s actually live with some customers.
Going back to the defense side and their colossus of information, have you seen their reaction change in general? As an example, is it, “Uh-oh, these guys contacted me with this; I always need to settle”? They probably have pretty firm rules about this. They don’t just randomly make it up as they 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, “Oh, you demanded this much. My first attempt is going to settle here.” But if their costs go down, maybe that changes, right? Have you seen any change in the reaction of your clients’ counterparties?
I would say the defense side largely still works on an hourly business model, so they haven’t quite caught up to the same pace as our attorneys. There’s a lot of pricing asymmetry here. What the defense used to do for one law firm we were working with was push out discovery request dates until the day before Thanksgiving or a major holiday, and then send the discovery, because they knew the person would go on vacation and be stuck with all this workload. They wouldn’t do a good job on it or would rush it.
Because this was such a repeated tactic, they created an agent on Eve to respond the same day. The next time this came through, they responded immediately with the responses, and the defense was like, “What is going on here?”
Yeah, yeah. The tactics don’t work anymore.
We’re seeing so many variants of that happening now, which is causing the defense to realize, “Wait, this is what happens when the other side has resources.”
Right.
“Oh, crap.”
Right.
That’s what’s fun to see.
Well, Jay, this is a fantastic conversation. I learned a lot. I didn’t realize there were 10,000 touches every time you went through a case. Really fascinating, and I’m delighted to be your partner and bring Eve to the next 10,000 firms.
Thank you. We still have so much more to go. We’ve probably helped a couple hundred thousand clients to date, and we have hundreds of millions to touch. I would love to make a difference in their lives every day.
Awesome.
Thank you.