Mercor: Meet the 3 21-year old dropouts that just raised at a $250M valuation

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Hi 👋, this is the Today in AI Newsletter: The weekly newsletter bringing you one step closer to building your own startup.

We analyze a cool, industry-shaping AI startup every week, with a full breakdown of what they do, how they make money, how much they’ve raised, and the opportunity ahead. 

Let’s get to the good stuff in this email: 

• This AI startup plans to replace recruiters forever

• They already have over 300K customers with a 7-figure run rate

• They’ve just raised a $30M Series A at a $250M valuation

So what’s the startup and who are the founders behind it? Here’s the story of Mercor 📈

There’s a huge industry around staffing where people, to this day, manually review resumes, manually conduct interviews and manually match people with the right jobs.

💡 This all changes with Mercor.

Mercor was founded in 2023 by Brendan Foody, Adarsh Hiremath and Surya Midha, to build and train LLMs that automate all those processes. 🤖

Mercor reviews a resume the same way a human does, hopping on a zoom call and conducting an interview that’s far more in depth than a human is even able to do.

However, the most important tech is in facilitating the matchmaking process. 👨‍💻Mercor trains very large models that understand all the characteristics that predict why someone is likely to do well at a certain job or task.

💸 Mercor even facilitates all the payments to people hired, so businesses can have someone on their team with the click of a button.

After interviewing thousands of businesses, this is what Mercor found out clients care about the most:

1. Speed 💨

2. Quality of the candidate 🫰

3. Price (Salary) 💰

The reason these factors are difficult to find in candidates is due to businesses’ constraint to manual processes.

Example: When you’re hiring a software engineer remotely, you might need to conduct a dozeninterviews to find a candidate that’s good.

Even then, they might not have been a good pool to start with and the candidate might not have exactly what you’re looking for. 🤷‍♀️

When all of a sudden you can leverage technology to assess and interview hundreds of thousands of people at the cost of software, you’re able to find candidates that are far more relevant. 🤯

You’re able to find candidates that can start immediately, and achieve all that at a cost structure that’s dramatically lower than what people ordinarily find with human processes.

How it works 🔄

On the applicant side:

1. Go to their website as a candidate to upload your resume. 👨‍🎓

2. Join an interview where you talk to an AI that will ask about your past projects, and nuances of your past work experiences.

3. Get feedback on your resume and interview, then get potentially matched with a job. 👨‍✈️

On the business side:

1. Go to their website on the business side.

2. Query for any role you want to hire for with their AI-powered search.

3. Mercor’s evaluation system looks through the candidate pool and recommends candidates that are the best fit. 🤞

This optimizes the recruitment process for businesses where they’re able find better people, save time and make recruiting a lot cheaper. 📈

On the candidate side, undiscovered talent can be found internationally that could be a better fit for jobs. This gives everyone an opportunity all around the world. Win Win for everybody!

☄️ So far, Mercor has had over 300K candidates who have gone through this process on the applicant side!

More recently Mercor has started experimenting with a “visual evaluation” as part of the process, looking at facial expressions and things like voice inflections.

They even found that something as small as the blurriness of someone’s camera can signal what job they’re best for! 😱

Predicting human ability is super high dimensional and requires a ton of data.

🔄 A feedback loop is generated where more progress, means Mercor can operate at a larger scale, giving them more data to work off of to make sense of even smaller features. 

📊This also helps them map different characteristics out to the right performance metrics and KPIs to make finding the right candidate even more accurate.

Backstory 👀

Brendan Foody, Adarsh Hiremath and Surya Midha all met in high school in the Bay Area doing competitive debate. 📚

Adarsh and Surya were the winningest debate team of all time. 🏆 They were the first team EVER to win all 3 of the largest national debate tournaments in the US.

Brendan however, is dyslexic and wasn’t very good at debate so he stuck to what he was good at: Building startups.

👨‍💻 Brendan had started coding in the third grade and was always interested in building things.

While still in high school, Brendan bootstrapped his first company doing cloud consulting. 

He had found that with the AWS activate program, there were a ton of eligible startups to get free cloud credits, but weren’t applying.

📈 This was a huge arbitrage opportunity. Brendan started selling his services for $995, where he would get these startups their cloud credits worth $5k to $25k!!

He did this a lot and ended up making a ton of money in high school. 💴

He then set out to start a software tool with Adarsh with some of the cash he made, to build a better user interface for AWS, but this didn’t go very far. 😢

Brendan had always been interested in cloud interfaces being very inefficient, and started another company with Adarsh to solve this: Seros.

While working on Seros, they’d been hiring software engineers in India to help them build it out, when they came up with another business idea. 💡

There’s incredible, undiscovered talent internationally, but it’s not as dense as talent in areas like Silicon Valley.

When you’re able to automate the process of assessing that talent, you solve the talent density problem. 🤔

You’re able to find people no one else is considering and create incredible experiences from both sides.

They were so much more excited about this one, so decided to drop out of University (Harvard and Georgetown 🎓) at 20 years old to go full-time on it over the Summer of 2023.

Adarsh even turned down an offer from Bridgewater at the time to go all in on this!

Timeline & Stats 📊

On September 1st 2023, Mercor raised a $3.6M seed led by General Catalyst.

🚀 This is when they really started to take off…

By February 2024, Mercor had over 100k applicants and a 7-figure run rate, which got all founders into the Thiel Fellowship.

This marked one of the only times in history an entire founding team received the Fellowship. 💫

💰 Fast forward to September 2024, Mercor raised a $30M Series A at a $250M valuation led by Benchmark with participation from General Catalyst, Peter Thiel, Jack Doresey, Larry Summers, Chris Re and Adam D’Angelo.

Mercor now has 11 full-time employees in the US and 20 international contractors in India, and plan to continue hiring aggressively.

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