EvenUp raises $150M Series E to bring AI to 20M annual personal injury cases — still just 1% penetrated

Um, but what what a run for gold. We have our next guest in prestream waiting room. We have Ramy from Evenup. Let's bring him on in. Bring him in to the TV film. How are you? Welcome to the show. Hey guys, how's it going? Uh, it's great to see you. We're doing great. We got our we got our gong ready for you. Yes.

Uh, introduce yourself, the company, and any of the news today. My name is Rammy. I'm the CEO and co-founder of Evenup. We are happy to announce our $150 million series E led by Bessemer. There you go. Congratulations. Uh yeah, break down the company history. Uh yeah, how you got into uh the category.

Yep, we started Even Up about 5 years ago. This is before legal tech or generative AI was all that interesting. And the premise was to ultimately even up the playing field for personal injury victims in the US. Yeah.

So every year there's about 20 million injury victims where often these cases take a lot longer than they need to to settle or settle for a small fraction of what they're worth. And so our goal is to even up that distribution by helping ultimately their attorneys. So it's a B2B startup.

We're helping them across the whole life cycle of their injury cases. Think of it as doing the heavy work for these attorneys for them at what I call superhuman quality.

We're helping them settle their cases faster, helping them settle their cases for larger amounts, and removing a lot of the manual work as we go through a lot of these workflows for these attorneys and their staff. Uh how are you guys already running up against the the oppositions uh or or the defenses AI themselves?

How how is the battle evolving? Yeah, we we don't really see too much of that. Um, the crazy thing is this is our fourth round of financing in the last two years. Wow. And we're on this really rapid growth trajectory where we see about 10,000 cases a week.

But when you think about just the TAM here on 20 million cases, we're about 1% penetrated today. So in a way, even though we're it's a big number, it's still very early days in our space. So we haven't seen any of that come through.

What we have seen is ultimately being able to change some of the operations of these law firms for the better. So, one of our firms has scaled revenue by about 70% year-on-year on a base of over 100 million of revenue without adding headcount. Mhm.

Another one of our firms have used one of our products in mediation in real time where they turned a $50,000 offer into a multi-million dollar offer. So, it's kind of crazy to see the impact we've been able to have, but it's still early days. Is plaintiff screening a different business? So yes, not fully.

The way you can think of this is the way we help is, you know, imagine somebody gets injured. They would typically call an injury attorney. They would sign up. They see a billboard. They see a billboard and the billboard says injured. Call this number.

They call that number and they describe their injury and then someone needs to qualify that and it's probably not the most highest paid lawyer and it feels like those intake forms could be processed by AI, but is that something you're looking at doing? So yes, it's really interesting.

So we we don't do the intake call themselves, but as soon as the intake call is done, the transcript of those calls is something that we would analyze. Sure. To say, "Hey, law firm, you need to prioritize this case. " Y or this might be a case you want to draw. Yep.

We don't do the signing up of the case, but as soon as there's any information, whether it's audio or document based um info in these cases, we read that, we scan it, and we ultimately make decisions off of that with the obviously with the with the attorney hand in hand.

uh how are like hallucinations and and uh how are you thinking about like lawyer in the loop?

Uh Jordi was talking about this uh there was some case about uh uh a consulting group that turned over an analysis to a city and had to give them a huge refund because it was delight delivering uh a a a study that was just inventing like judgments that no judge had actually Yeah.

it wasn't grounded in like the ground truth of case law. And uh I I imagine that like I I mean the stakes are pretty high.

The model just had a really but also I mean you you you could you could wind up in a situation where like your firm is like forever tainted by a certain judge and the judge is like I remember what you did. That was really sloppy. Uh I imagine that your clients and your customers uh care deeply about that.

Like what are the what are the strategies for avoiding those types of situations?

you you both brought up, you know, really great points here and and it's it's a really funny thing because folks are always like, "Hey, generative AI and legal tech are all shoeins for each other, but folks generally tend to forget accuracy really matters.

" These cases, you can't be 90% of the way there in a legal letter. That's how you get this, right? Or that's how you get those again some of those headlines that you guys just mentioned. Yeah.

And so the way we think about this internally is you need to have done a lot of cases because every basis point of accuracy matters. Mhm. And so another way of thinking about it, we do a number of different legal workflows for these attorneys.

But if you think of one letter called a demand letter, that's one of the documents we prepare for our for our firms. The quality from this in us being able to repair this two years ago versus today was very different. Yeah. Right.

When we started, keep in mind this is before GPT3 and and the big, you know, all the craziness around AI two years ago, we had to have a human in the loop to QA these letters. Yep.

And if you think about the inputs in these cases, and we're at a point now where we're going to be millions of pages of medical records, u medical bills, police reports, raw underlying documents, we've had to fine-tune these models, one to be able to get a much higher level of accuracy than what you typically see off the shelf.

And so it's what's a simple example of this is if you think of something as intuitive as, hey, list me all the medical visits that a plaintiff has seen in a case.

If you just go into any of your, you know, models today that are, you know, publicly available, ask it to do it for you, you'll see the accuracy is just not good enough. And so this is where we had to train our our own data service model just to do something as intuitive as be able to pull out a date.

When you look at these case files, you get to see timestamp dates, signature dates, date of birth, etc. There's so many different dates. It gets pretty complic complicated with even just one piece of extractions. And that's how we had to build this with time.

You've had to do a lot of you got have to get your reps in to get the quality of where it needed to be. How are you growing the business? Are you running billboard ads? If you're an injury attorney, call this number. Or or are you doing uh state? You should really you should really do that on the 101.

That would be great. Uh or or or are there like legal tech conferences that you like what does the top of funnel look like for you? Yeah. This is the the crazy thing as well about our space is this is such a massive space that folks just don't necessarily know too much about. But when you mention those billboards Yeah.

and you folks are kind of saying this in just but when you see one of these firms has a thousand billboards in California. Yeah. That's I don't know any of any SAS business that has a thousand billboards. You know what I mean?

Like massive marketing machines and they're based on our math there's around 300,000 of these injury attorneys. Wow. And there about 20 million cases and they're all over the place. Right. Yeah. One of our largest customers, as an example, is in Alabama. Mhm. You would have never thought it would be in Alabama.

We have massive firms in California. Massive firms on the east coast. And it really follows population. Yeah. Where there are people, there's going to be injuries because it can mean anything from motor vehicle accident to a dog case, even police brutality cases. There's many different ways folks get injured.

And so, as long as there's people, there's going to be personal injury attorneys. As long as there personal injury attorneys, they're all B toC. They're all kind of like they want to be found. Because if you think about our go to market approach, we have a over 100 person go to market team that's territory based.

So this is where we would go local in LA, in SF, wherever it might be to be able to get these folks. And that's where, you know, a lot of this is outbound as opposed to inbound.

Did you ever think about the Atrium Clear Spire model of like bolting an actual law firm onto your software company of an LLC bolted to the uh to the CC Corp with like an MSA? Uh that was a model that's been tried a few times. They they think people are trying it again.

But did it ever occur to you to try and try your own cases, team up with a lawyer, build a firm? Yeah. For us, like we we we want to the way at least I see this space evolving is I see this as very much a win or take most.

And even though we're in vertical SAS here, it there's like elements of Uber andyft that feel true to our space where the first startup that gets 10% of LA will win LA. Yeah. because every time you see these cases, the better this whole system gets.

And I'll just I'll elaborate on that a little bit more and that should hopefully explain why we're doing this in a very B2B fashion. But the one thing you folks should know is even though there's 20 million cases, 99% of them are settled privately. Mhm.

And so there's a real wide gap in performance in terms of how long these cases take to settle and how much they settle for. And generative AI alone can't solve that problem.

You need to be able to see a lot of cases for you to be able to do that because most of this data is sitting in the inboxes of a very fragmented industry. And so for us, the goal is how do we expand our go to market, you know, as quickly as we can to be able to go from 1% to 10% to 30% market share.

And the want to think about as a key metric, more cases we see, the better the system ultimately gets. And if we're just very focused on I mean we we'll never do this but like competing against our own customers you get of the cases that are out there. Yeah that makes a ton of sense.

Do you think that legal AI is underhyped as a category? Obviously there's a ton of funding flowing in but there's not you know on the code generation side it's sufficiently hyped right every researcher at every company you know is talking about the the leverage they're getting.

Every startup founder is talking about the leverage they're getting. every CTO is talking about the leverage they're getting. Public company CEOs legal is like, you know, just happens.

Uh, you know, there we certainly have plenty of lawyers in tech, but they're not, you know, they just don't tend to be in a position where they can talk about stuff in the way that regular software engineers can.

So, it feels like you could be seeing the same type of revolution happening, but it just would be much uh get much much less coverage. No, for sure. I I think that there's obviously been when we started um even up a couple years ago you folks can imagine it's like legal tech sucks, AI sucks, personal injury sucks.

Like my background is I used to work at Whimo and I used to work as like a tech investor before that and so it's definitely a lot there's a lot more attention today in legal tech than there's ever been before. Is it again is it overblown or not?

I think in the end of the day, the thing that makes our space so different when we're selling to these injury attorneys, the thing you folks should know is it's a very fragmented, highly competitive, and most importantly, commissiononly industry. These folks make a percentage of the value of the cases that they settle.

So unlike other parts of, you know, AI or legal, there's no experimental ARR, right?

These are not like big firms where they can afford to spend a million dollars on something and because of how competitive it is like you better believe this thing can actually help their case operations otherwise they'll turn they don't have the luxury of you know being able to have big IT budgets etc.

And so in that sense, if you think about our 2,00 customers, they wouldn't be around if they're not seeing real demonstrable ROI in terms of increasing case outcomes or reducing duration of these cases. And in that sense, you know, I do think it is call it it's still early days.

And and if you think about the mission of the business, it's not um I I think it's just going to be it's inevitable in terms of those 20 million cases being able to be settled not again all over the place, but as fast as they can for the fair amount.

And so in that sense when we're just 1% penetrated it's it's not over I at least in my mind it's like clear ROI. Well, yeah, and there's that that customer alignment where they're incentivized to adopt as much AI as they possibly can because they're not billing hourly, right?

They're just getting paid when these cases settled.

uh versus you know a traditional law firm if you if something they used to be able to build 10 hours for suddenly takes 30 minutes and they had a lot of margin in that 10 hours there's not there's not the same incentive to adopt uh as as what you're seeing you nailed it and and the other thing that's also different about this wave and it's funny because I was having a conversation with one of our um one of our customers about this some of these folks are still on prem but they're one of our biggest customers and So when you go to a law firm and you're like, "Hey, you got to be on the cloud.

" They're not going to understand what you really mean. When you're going to these law firms and you're like, "Here's a legal letter. It was drafted instantly. " You can evaluate the quality of this thing relative to your own staff because you're a subject matter expert.

You know what it, you know, this legal letter does. And that's what allowed the space to adopt a lot quicker than anything that we've seen before in legal tech.

And and again, I I think again you really pinpointed it, but they really genuinely care a lot about being faster, settling settling quicker, spending less time on review because anything that they save, they get to keep, right, as their own margins. Totally.

One of my first jobs ever was uh doing paper filing at a law firm as an intern. I was like a kid. And you were a paper boy then, you're kind of a paper boy now. We're still paper enthusiasts.

I I hadn't I hadn't put it together until I until I actually just had this conversation and reflected on like how crazy that was that I mean I guess the cloud like barely existed then but yeah it was paper back then it was wild. I mean computers were around but like my job was sort of like yeah inventorying this stuff.

So yeah, law moves slowly. Like the like a lot of the law firm partners that get like effectively tenure are like my process works and I like it printed out or I like I like you know having the network the internet at my office is reliable. I don't know about putting it in Google. So like people got to figure it out.

When do you when do you expect the first AI uh legal company to IPO? Hm.

Still feels like we're probably couple years out, but I imagine the revenue for you or some some of these other players could get there uh you know get to that $500 million mark or wherever whatever the uh wherever it needs to be to to be interesting to to Wall Street. Yeah.

So, this my um just on the paper piece real quick, then I'll answer the other question. And it's it's so funny the way you can kind of think of this.

There's been so much innovation in more of the consumer like how to get leads like the consumer uh part of personal injury where like you know attorneys are advertising on Tik Tok on social etc. But on the operation side there's been very little innovation back to your paper days. They're still doing stuff on paper.

We've had some of our folks asked to pay our our annual SAS subscription with monthly checks to give you a sense of how cool the ops piece can be in this space. And so this is the first time really in history that these operations of these firms are changing pretty substantially, right?

Because you now can do a lot more with a lot fewer staff. Yeah. And if you think about again like where we're going with this, you're going to see these firms be just be able to handle a lot more volume.

And and if you think about the the amount of cases that person attorneys take on today, you'd be surprised at how many cases they're not taking on because they just don't have capacity or they can't make the math work because again of their of their model. Yeah. Yeah. So I think I missed the other question.

What was the other question again? Oh, I just kind of Yeah. IPO timelines for the category. When when do you expect the first companies to get out? Yeah. It does feel like an entirely different like market. Like there's no like clear comps that everyone knows.

It's not just like, oh, another like, you know, SAS company that we can just immediately comp to. So, it would be like a new Yeah. In the legal industry, law firms can't go public, right? Yeah. Yeah. Exactly. Financial got to be different. Yeah.

I would love to hear some color on like how the public market might receive some of these. Yeah.

I I mean in terms of like timeline I would say again the 500 million of ARR median ARR um you know business going public the threshold there I think we're a couple of years away but you know I mean we're we're scaling super fast we're more than doubling yearon year on a on a meaningful base so I do think we're maybe two three years not us but for one of the companies us as well two three years out before going public in terms of like how the markets might receive it it's so interesting right that these are such different businesses where you're going to see a lot more TAM Y than you've seen in traditional software.

And so I I I kind of say this, one of our one of our biggest customers is is paying us 4 million a year and they have 100 employees at the firm. Wow. Think of the Yeah. 40,000 value per head. Yep. Exactly. So you're delivering a ton of value to this. Yeah.

Because one of the things that comes up with with some of our investors, hey, is like you're focused in a very niche part of personal and 300,000 attorneys out of, you know, over a million, it's maybe 30% of the base in the US. But when you're making 10x more revenue per head than traditional SAS, Yep.

your T is actually meaningfully bigger than a lot of these SAS companies. Sure. Sure. that are out there.

And so again, I do think it'll be interesting to see much more rapid growth, much higher base SAS businesses than you've ever seen before and how the market would would be able to evaluate that because it is it is going to be different than traditional SAS. Totally. Well, congratulations on the funding milestone.

I'm sure we'll see you back here again soon. Maybe one more round before the end of the year. You've already done a couple, you know, uh but uh looking forward to the next conversation. Have a great rest of your day. Thank you so much for hopping on. Cheers. We'll talk to you soon. And now it's time for our song.