Mercor raises $350M Series C at $10B valuation, paying out $1.5M/day to marketplace experts

that like for some reason it just gives me better results. I got a 98 last night. Let's go. 7 hours 44 minutes. Our next Our next guest, Brendan is in the reream waiting room. No, he's [music] in the TVP and Ultra. Welcome to the stream, Brennan. Congratulations. How are you doing? Called his shot.

He's the biggest shot caller in all of Silicon Valley. Yeah, we got to get We got to get some new shots. This is Yeah, I was telling him this. I was like, call the shot. You're holding up the global economy within 5 years. Every company is dependent on you. Like there's no there's no shot this man won't call.

But uh g give us the news. Break down exactly what happened. tell us what is new today. Yeah, I mean the company's been growing like crazy. We're now paying out over $1. 5 million a day to experts in our marketplace. Hit the G for that. There we go. And what else?

Uh and we've uh raised our series C of $350 million at a $10 billion value. Massive. Billionally excited. Yeah, not bad for your first startup. The gong is really going. Something's up with the gong these days. I don't know if you can hear it, but it's like it's raining. Let's get right in.

You had a uh I feel like I remember you had a blog was it blog post uh Friday. Do I have that right? Is it worth is it worth getting into that? Uh about the big things. Yes. Yeah, the big things. Let's talk about the big things.

Yeah, it's really starting with the question of what are the things that we know are going to be the same about our business over the next 10 years and that there's a lot that's going to change over time.

But we know that the three main areas that our customers will always want more improvement and progress are in more candidates on our platform, better matching and faster delivery of all the candidates that we're hiring for them to improve frontier models. And so those are really Bezos inspired. It is exactly. Yeah.

Um similar to how Amazon said that their three big things were more products, better prices, faster delivery. For us, it's a little bit different because no two people are the same, but uh inspired by it very significantly. Totally. Uh let's go let's go through them.

I think uh um and then I guess like want to understand like want to get kind of more into the into the future too.

I think I think people uh some people would have a sense that like there could just be this you know incredible uh demand over the next 5 years and then you know does that demand evolve evaporate but I I want to I want to hear how how you view it uh maybe more specifically. Totally.

What we've been seeing is that there's an enormous trend towards humans training agents how to automate redundant workflows that they would do in their jobs because it's structurally more efficient to do so.

Instead of a customer support representative redundantly responding to hundreds of tickets, they create an eval to train an agent one time how to do that thing. Instead of a banker redundantly analyzing data rooms, they create an eval to train an agent how to do that thing.

And we believe that a huge portion of the broader knowledge work in the economy is going to converge on training agents how to do these activities and our marketplace is really at that frontier of creating this new job category in training agents.

How does uh how does this look long term if one of the big AI platforms becomes really really dominant understands what everyone does and can just ask me to do a task within the app like is there any sort of like disintermediation risk or do you think that what you're building with Meror is special enough that even if you know the OpenAI chat GBT app can detect that oh well you've talked to me enough I know you're investment banker.

I'd love to do an RL environment with you. Here's an offer directly to come and do some training data. Uh like how how are you thinking about counterpositioning against that risk or is that just like not a thing at all?

Well, one of the most important things in building out these environments to train agents is that they need to be very consistently reliable and that you need to put a lot of work into them. uh and if there's noise and that there's some mistakes or issues, then it's very difficult for a model to learn from.

And so as a result, it's really difficult to ask your users to say, "Put in 10 hours to helping to see if we made a mistake in preparing this financial model for you. " Um and those users might flag a mistake, but that's, you know, incorrect half the time.

And so what they instead need to do is build out armies of experts that are able to diligently analyze model performance, go through strict review processes to ensure consistency um and build these RL environments to adopt models for any specific use case.

So you obviously have massive uh diversity on the uh talent side. Uh but how do you think about customer concentration over the next few years? Do you think that like there are clearly power law winners in AI? There are trillion dollar labs, you know, Google and OpenAI is half a trillion dollars.

Like there's huge winners and then there's a ton of startups. How do you see the shape of your business?

Do you think you'll have a lot of medium-siz companies or just tons and tons of small companies and in every individual company will need to come to you for talent to optimize whatever little thing they're doing or will you be doing more work with the really really big labs? How do you think that all shakes out?

I think it'll be some combination. Definitely near-term it looks similar to Nvidia in so far as working with a dozen of the hyperscalers that are investing huge amounts in this.

But over time, what we're seeing is that every enterprise wants to train agents to customize their specific workflows and we have the expertise to help them do that and building out all of the EBEL sets and environments that correspond to every workflow in their businesses that they want to automate. Mhm.

Um what uh any any I I had an eye opening experience yesterday. I have a a friend who's a lawyer and about a year ago I started I I started asking him like what kind of AI tools uh they're using and he was like broadly like not impressed. He was like we're like signing up for them.

They're not get we're not getting a lot of value. Um but uh it's interesting. I'm keeping an eye on it kind of thing. And then yesterday he said to me, "I've seen the future. Harvey isn't perfect, but has better attention to detail and is more thoughtful than almost any junior person at our firm.

I've watched it do 100k of associate level work in 10 minutes.

" And that felt like just extremely notable to me to just see how hard he like 180ed on that is like uh how like what what is the structure and you can talk at a high level to not give away specifics but like how much investment is like going into just that category alone from from from your view I mean we're seeing a huge amount of investment in law certainly I would say the top categories are probably software engineering then finance hands than law.

Um maybe close between medicine and law. Um but I think that the models are very quickly going to be able to do even partner level work at a lot of these firms.

And so that transformation and how it impacts businesses and the economy is going to be really profound and obviously all of the data and evals to enable that is one of the primary blockers to getting there. We have a shout out to one of your employees, Verat Talwis.

So, just wanted to say uh congratulations to him on being part of the team. The chat is just shouting him out. Obviously, it's a big milestone. So, we want to celebrate everyone on the team. What uh how in in conversations for this last round, uh obviously the business has so much momentum.

I'm sure people are just like, "Take my money at all cost, you know, whatever. I just take it. Uh I'll send the money and we'll figure out the docs later. " But uh how big can Merkor get?

Like what is like I if somebody asks like okay if everything goes right what does his business look like in uh does it does it look like you know you're paying out on the levels of like an ADP right is are do you become like one of the largest pseudo employers in history like what's like the what's the craziest outcome?

The way I think about it is that right now businesses are spending about $40 trillion a year on knowledge work. Uh all for people doing these largely monotonous things that have similarities from task to task. But all of that is going to be transformed to training agents to automate workflows.

Instead of doing it ourselves, we'll have agents do those things.

and Merur is building the infrastructure to enable humans to engage with models to teach them to fit into the AI economy and and I think there's an opportunity worth tens of trillions of dollars a year uh to help that transformation happen over the coming decade. Um and so we're only 1% of the way there if that.

Uh and very exciting for everything to come. Are you a foodie? We have another question from the chat. Do do you like fine cuisine? I I am a foodie. Yeah, you are a foodie. Very fortunate coincidence. Yeah, that's good nominative determinism. We're very happy to hear that. Uh, last question. When IPO?

We don't have a specific date in mind yet. Uh, potentially on the horizon, but we'll be sure to keep you guys updated. Let's go. Potentially, let's do an air horn for the horizon. Potentially on the horizon. Now, somebody's probably going to write an article on that, by the way. I'm sorry. This is a new thing.

I I see it all the time. Every time they interview Palmer Lucky and Blonde Bloomberg, they ask him like, "When are you IPOing? " And I'm like, you know, that he would tell you if he had news there. Like, why are you even asking? But I guess it's just fun to ask.

And then in a couple years, we can look back potentially on the horizon is much different than we have no plans, though. So, yeah. Yeah. I mean, you could have said absolutely not. I I would never I will never take this company public in my life. You didn't say that. So, at least we got something. So, thank you.

There you go. Progress. Anyway, uh massive congratulations on all the progress. Uh really really remarkable growth. I mean, what what a fun time, what a fun business. And uh congratulations to everyone on the team. I mean, thanks for having me. Absolute rocket ship. Cheers. Uh have a great rest of your day.

We'll talk to you soon. [applause] Get back to the timeline a little bit. Let's get back to public. com investing