Mercor

“One interesting thing about Mercore is we don't have a sales team. There is not a single person who works on sales at Mercore outside of, you know, the founders.”

“No seed round, a little bit of revenue, no series A, no Teal Fellowship, nothing. We were just three friends working in a small office in Palo Alto with our amazing team in India.”

“The only reason we actually just floated those numbers out is because we didn't want our team working on Sundays.”

“Our goal isn't to deploy a hundred million dollars tomorrow.”

“One realization that we've come to is that you can teach people a lot of things, whether it be, you know, technically or going to market or whatever, but The one thing that you can't quite teach people is to care, and that's one thing that we index on pretty h…”

“We changed our like salaries and gusto to 500 dollars a month.”

“You can literally spin up this interview in under 10 seconds.”

“Brendon Suria and I started working together without any business ambition. Necessarily. We just started a dev shop together.”

“It looks exactly the same as placing someone to work at any company, right? So just like Mercore might work with startups making their first hires or companies hiring in a more traditional full-time capacity. It's the exact same thing for a lot of the large AI…”

“Maybe running our entire, you know, internal hiring process for Mercore in a completely automated way, meaning Brandon, Surya, and I don't even talk to someone when they come into the office, and then we walk in the conference room to meet them the first time,…”

“For us, it's hiring and Beating the expert hiring manager by a large margin.”

“It was doing, you know, eight figures in, in revenue, right?”

“An interesting dynamic about of all of our, you know, fundraising rounds is just that, like, we didn't intend on, on doing the fundraising at the time, and it sort of just came to us.”

“But I think the more realistic breakdown is the AI for a specific use case might be able to get us 6070, 80% of the way there. But for that remaining 40, 30, 20%, you're going to need a human To be able to take you all the way there. And the reality of the sit…”

“One of the initial iterations of the Mercore product was just built around a chat interface. Like there was pretty much no other way to hire people unless you use the Mercore chat bot, because we were so bullish on, on chat.”

“It's on a case by case basis. For some customers it can be, you know, over 30%. For some it can be less.”

“There's a huge difference between the top .1% and then the 80th percentile person. So usually for customers, it's not a question of price. It's a question of quality.”

“The round is a hundred million. It was at two billion.”

“It's, you know, Brendan, Suri, and I, and Benchmark on the board.”

“The second network effect is or like data flywheel is around this job prediction piece where we're able to see who is performing well on jobs and the specific reasons why they're performing well on jobs and use that, that end to end Data on people's outcomes t…”

“Actually, our insight about the market is that human data and talent assessment have actually become the same thing, right?”

“My take is that programming is actually more important today And it's just going to happen at a different level of abstraction. One could argue that the leap from assembly to Python was actually maybe even a bigger leap than the leap from Python to natural lan…”

“I think what we consider SaaS will change, right? In the sense that the next era of SaaS will be replacing entire services, right? You know, whether it's the end-to-end process of a recruiting agency like Mercor or another, you know, different service or that,…”

“Net retention is over 100% by a large margin.”

“And what we ended up doing is recruiting these really, really exceptional folks from India to help us out with our dev shop. And then very, very quickly we realized, you know, the software was one thing, but we had found some really, really exceptional people …”

“So on our end, the entire process is automated. So this is everything from a candidate hearing about Mercore and going onto the Mercore platform via job listing, us pulling in their resume, their salary expectations and whatnot. Administering a personalized in…”

“Brex went from like zero to a hundred million dollars in revenue in like in 18 months after launch, and Mercor went from like a million dollars in revenue when I invested to like over a hundred million, like in 11 months.”

“Frankly, I don't think I would have invested in Mercor if I hadn't invested in Brex.”

“We were already at a nine-figure revenue run rate, and the company quadrupled since the scale acquisition.”

“And so now we're 25 times larger in revenue scale than we were at the Series B but in a spot where the business is so profitable that we don't really need to go out for financing or spend too much time thinking about financing while we often get a lot of offer…”

“But actually if I had to choose the most important thing, it would be the internal link to quality, which is that having phenomenal people that you treat incredibly well is the most important thing in this market and getting those people to refer all of their …”

“Well, not exactly. I need to offer a key clarification, which is that we've actually never mandated hours. It was more so when we were talking about nine nine six, it was a description of how the early team worked. Like, in fact, the reason we talked about nin…”

“One of the largest inefficiencies in all of AI research is that the evals that people have been going on Of humanity's last exam and PhD level reasoning or Olympiad math are wholly disconnected from the outcomes that consumers and enterprises actually care abo…”

“So long as there's things that the human is able to do, the model's not able to do, and we want those capabilities in the model, whether it's to schedule a meeting or write emails for you or whatever it is, we need humans that help to create those verifiers an…”

“I don't think that Models are plateauing. Like, if we look at the last 12 months of progress in models, I've been blown away.”

“The total addressable market is limited by the amount of things that humans are better at than models.”

“We work with All of the top research labs at the frontier of model capabilities, and we're not like the crowdsourcing companies in that we try to hide all the people on the platform, pay them low rates, et cetera.”

“When we met Victor, we were at. 1.5 million dollars in revenue run rate. He gave us the term sheet and we were at a little over two million dollars in revenue run rate. So over a hundred X multiple on revenue.”

“There's the new data types that everyone's moving towards called RL environments where we'll call it, rough estimate is like, 50 to 60% of the market, and so doing quite well on that and expanding market share quickly.”

“The outcomes of data and the people that contribute to it are extremely power lot, similar to a company where if you have a hundred people on a project, oftentimes majority of the model improvement is coming from the top 10 to 20% of people, right? Just like s…”

“We have the demand to, like, double overnight if we can meet capacity.”

“We, we're growing over 50% month over month. Like we averaged 54% month over month growth for a while at that time period.”

“We scaled the business from one to five hundred million in the last 17 months, which is the fastest revenue growth of all time. One month faster than Cursor's time.”

“I think that it's likely we'll do a financing soon to answer your question with low dilution, largely because there's a lot of benefits to signaling ourselves as the market leader and RL environments and all of the high complexity data that we produce.”

“Like I remember when I was talking with Jack Dorsey before he invested, one piece of advice he gave me was that we should stay private as long as possible.”

“Our largest customer, I can't share the exact percentage, but the breakdown is relatively similar to Nvidia.”

“We've definitely found those stories of customers where I think they start out multi-vendoring, working with a bunch of different customers, with different vendors, but ultimately get to the point where they realize that they're going to be making a trade-off …”

“Like, the amount of utility that our engineers get from Cursor and Cloud Code and Cognition is incredible, and same thing for-”

“Scale AI came to us and they used our platform to hire thousands of people.”

“Like, we have very positive growth in net margins, unlike most AI companies.”

“In fact, the company is growing faster now at 500 than it's ever grown before, and so the growth continues accelerating.”

“Our average marketplace pay rate is 95 dollars an hour to put that in frame of reference, scale and search generally pay about 30 dollars an hour.”

“When Felicis gave us the term sheet, we were at twenty million in revenue run rate. So it's a hundred X multiple on the revenue”

“I think the truth is that all along it's been much more about hiring people that like give a shit and love what they do and are obsessed with it and the way that we are rather than specific hours. And early on those were highly correlated, but I think that as …”

“Now this company has gone to five hundred million in revenue, faster than anyone else, I believe, in history. I think it was 17 months.”

“I genuinely think that most B to B companies are going to get hit worse than Merkur.”

“We're doing a ton of data collection in the physical world as well, especially across skilled domains where you have electricians and mechanics and scientists strapping cameras to their head to record things.”

“So the revenue is between a 30 and 40% gross margin, but the key distinction and why it's not GMV, but it's revenue, is that the experts are actually only one part of the broader value chain that we deliver to customers.”

“There was someone I was hiring the other day, and he had an offer for twenty million dollars in cash per year from TBD, and like that's the kind of stuff we run into on a regular basis.”

“We maybe can't double prices. We could double capacity. We could probably increase prices by 30% without much of an impact.”

“Like we have the demand to Double overnight. We just don't have the capacity.”

“In 12 months time, that's probably about triple that.”

“There was this broad perception on Twitter that was much more exaggerated than what actually happened within the business.”

“No, I wouldn't. I mean, ultimately we've gotten a lot of acquisition interest and we could walk away with, like I could walk away with billions of dollars in cash.”

“Now we're paying out over three million dollars a day and the fastest job category ever created in history.”

“Think of one person that's very prominent who's invested in multiple competitors and just, like, made this tweet about how all of our data was getting accessed by China when it was totally untrue.”

“The, we burnt a half a million dollars after our seed round. And then from there, we've pretty much been profitable ever since. We have more cash than we've ever raised.”

“And so we view having over five hundred million in cash and a super profitable business as a significant asset and allowing us to be prepared for when there is a market correction to make sure that we consolidate market share.”

“That one is false.”

“We're building out an eval set that measures how effectively agents can build end-to-end SaaS applications, where twenty-twenty-five was the year of how do you get a model to make a PR and a code base, and twenty-twenty-six is the year of how do you get the mo…”

“On Apex, the Frontier model right now is at about 40%, and 12 months ago the Frontier model was a one, which was scoring one percent.”

“When I try to get agents to do all of these workflows throughout Mercure, there's just an enormous amount of context that lives in people's heads that the agents need to have access to perform effectively.”

“Because in our incident, it was the attacker that used a swarm of coding agents to help get access to the system as is happening in a lot of these.”

“We have our interview question agent that where we've done over five million interviews and ask all the questions in the interviews.”

“I mean, I think that Meta you know, like, currently the relationship is still paused. Every other one of the Frontier Labs has grown their relationship with us since and the company has been crushing it but they're the only one that is paused, which is public.”

“We've had Three employees that have founded companies worth in excess of a hundred million dollars.”

“They gave us a term sheet within 36 hours for 2.3 million dollars at a twenty three million dollar post-money valuation.”

“Now we have an AI project manager that just completed its first project managing that entire thing end to end, where it's able to hire the experts. It's able to answer their questions. It's able to build the annotation tool using its coding tools within our pl…”

“When we have this talent network of over five million people that are able to refer their friends, it's just so much easier for us to find the marginal doctor because we have that enormous talent network that can refer us to their friends.”

“We are finding that the labs tend to prefer partnering with a very horizontally capable vendor that is able to flex across all of the different Verticals and scale extremely quickly rather than working with a hundred different vendors that they have to train f…”

“And so it allows vendors that are extremely high quality to be super differentiated in so far as pricing power, because quality is the X factor that becomes dramatically more valuable than any other dimension.”

“And it's more about people that actually are very acclimated to the frontier of AI, because it's the people that understand, that both have the expertise in oncology, but also are power users of ChatGPT or Claude that are able to find where the model makes mis…”

“That's not true.”

“Right now, we're spending more on tokens for our internal agents than we are on employee headcount.”

“And there's oftentimes this very power law nature of data that drives model improvement in that out of a data set of 10,000 tasks, the top 2000 tasks will create majority of the value.”

“And so there's this enormous mobilization of hundreds of thousands and soon millions of people to build out the full distribution of everything that you could pass into Google Workspace and everything that you could want out on the other side in every job cate…”

“False. Our relationship with OpenAI is stronger than ever.”

“By September of 20, 25 or say October, we were at called four hundred million in revenue run rate. And then Felisa's was like, we want to invest more. And so they gave us a term sheet at a ten billion dollar valuation.”

“We're at twenty million in revenue. They ask us, what valuation do we think makes most sense? And I say one to two billion dollars. So they give us a term sheet at a two billion dollar valuation.”

“Well, in our Apex benchmarks, we're getting closer to around 50% of Long Horizon workflows. Top models are scoring around around that much.”

“I buy it. I think it's also self-serving towards Mercore, in that we think that every specialized model will need enterprise specific eval and training data to show the model how it's performing in its setting, and I think it depends on I think the diversity a…”

“As the headcounts increased, you know, like more than 10 X in the last year, we just want to be careful not to grow one faster than the other.”

“To be honest, I let the team do whatever is best for them, and this is a trend I've just observed amongst almost everybody, is that cloud design has done a great job. People really like using it, it's easy to use, and we've just had a natural movement towards …”

“We made a tool that's maximally flexible, has all sorts of, we had, like, hundreds of different projects running on it. That's just chaos to manage, and what we needed to do sooner was to put guardrails on the type of services that we support, and work closer …”

“We've biased towards more senior hires. Who are better at understanding what drives the business forward, finding, kind of, like, really crocking how we operate, how we make more revenue, how we deliver better services to our customers, how we keep our custome…”

“The data type that's growing the fastest for us is environments.”

“I think that real world, like physical data is going to grow significantly over the next three years.”

“Probably the same answer as before in that, like, the three years out opportunity of robotics.”

“We see very Rapidly increasing demand for cyber defensive capabilities via data, and very interesting data types”

“It's the direction we have been heading, which has reduced concentration, and it's the direction that we'll continue to head as every enterprise begins to have human data work for their proprietary use cases.”

“I want very careful never to delegate judgment or decision making to models because it's, they make you think that it's doing the right thing, but You have to be paranoid with them still, right? You still have to, like, double check everything, and that's what…”

“I'm proud that of the people I work closest with on my teams, I've only had attrition to founding. And we've had quite a bit of it.”

“Yeah, I think so, but I think it might play out similar to driverless cars, where it's really hard to scale physical things as opposed to software, so it might be more of a, more of like a Waymo robo-taxi-cruise type moment than a ChatGPT moment, but I think t…”

“I wouldn't say that open source model improvements cannibalize our core business because data is most valuable on the frontier of model performance, so each of our customers has their own unique goals and is purchasing eval and training data sets To fill gaps …”

“The data types also change very frequently. So we're, we've moved from supervised fine tuning to preference ranking to Rubric based annotation to now RL environments across a whole bunch of different modalities.”

“We can't spend money fast enough to service all of the demand that we have.”

“It doesn't annoy me, no, because the, you know, we end every week with millions more in the bank, right? So it's funny how you can have, I've been at other Companies where I've seen, you know, interesting financial engineering and accounting, and people can ha…”

“We've moved away from take-home assignments. We do one take-home assignment, which is, like, can you just, like, use an agent to go, you're on your own for a bit of time, go use an agent, you know, give, produce this artifact for me, and we'll look at it.”

“So the trend that we see is we're, as a product team, constantly fighting to reduce surface area and simplify things, and we also see a higher ratio of PMs to ENG because engineering is less bottlenecked.”

“Evals and training data are the primary bottleneck to model performance right now.”

“There's so many providers at a billion dollars plus in revenue. Handshake's over a billion. McCaw's over a billion. Serge is over a billion.”

“I just don't believe you can throw a bunch of venture money into accounting firms or law firms. And magically turn them into the next Mercur or hugging face or any of these things.”

“These data companies, like you mentioned Mercore, yes, they sell data, but every person at that company gets how AI is going to look much clearer than the average human, and that makes them worth significantly more than, you know, even what investors will say.”

“I'm in McCaw and I think we did it at, like, two or three billion. My memory should be better, but I'm older than you. And I didn't do the latest round at, you know, whatever, twenty billion dollars”