From Poker to Wall Street: DeepMind Alumni’s AI Trading Startup
Three former DeepMind researchers who created an AI that defeated professional poker players have now applied the same technology to stock trading—and the bet appears to be paying off. Their Prague-based AI lab, EquiLibre Technologies, is now valued at $500 million after raising an undisclosed-sum Series A, TechCrunch learned.
The round was led by Creandum. Although the VC also declined to disclose the size of the round, vice president Cameron Sellers confirmed it was the largest single investment the firm “has ever made in one go into a company,” he told TechCrunch.
The Reinforcement Learning Connection
The common denominator between poker and Wall Street is that they are well suited for reinforcement learning, an AI training technique where self-learning models are incentivized by rewards. According to Martin Schmid, EquiLibre CEO, “The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?”
Proven Track Record
This isn’t just game money. EquiLibre’s algorithms have been trading billions in daily volume across the S&P 500 and NASDAQ. The startup claims its agents have been doing well since their rollout on crypto markets in 2025, and now on stock exchanges, with “a perfect record of zero negative months since inception,” meaning they have finished each month with their investments up overall.
Why VCs Are Betting Big
By applying its AI to quant hedge funds, EquiLibre operates in a field where automation is commonplace and improvements can quickly turn into cash. Creandum’s Sellers noted, “The potential total addressable market of trading in the financial markets is one of the biggest on earth, and there are countless funds over the years that have generated quantums of profit that make most venture-backed successes look small.” He emphasized that EquiLibre explicitly defines itself as “a lab first, not a finance firm.”
The Founders’ Journey
Schmid and his co-founders—CTO Rudolf Kadlec and CSO Matej Moravcik—don’t have a background in finance, and it is not what drives them. “I’m not doing this because I’m excited about making markets efficient. I’m doing this because we are all excited about building new things that have never been built before, and this is a lot of fun to build,” Schmid told TechCrunch.
The trio were visiting PhD students at Google DeepMind’s Applied AI lab (which Alphabet closed in 2023). There, they built Superhuman AI, the first AI program to defeat pro players at no-limit poker, also known as Texas hold’em. They also worked with professors now part of the startup’s advisory board, including Rich Sutton, who received the Turing Award for his work on reinforcement learning.
Building in Prague
To build their startup, the founders decided to move back to their home country, Czechia. “This is where we had a lot of people we had worked with, and there was a large Czech diaspora at Google and other places,” Schmid said. That helped EquiLibre build its initial team back in 2022 and reach its current headcount of 25. Compared to San Francisco, “It’s much easier to keep the good people here, because there’s not a new sexy AI thing happening every two months.”
EquiLibre is not the only hot AI startup in town—ElevenLabs is based in the same building. Still, it plans to scale its compute infrastructure, bringing online what it expects will be one of the largest compute clusters in Central and Eastern Europe (CEE).
Funding and Valuation Journey
While EquiLibre declined to disclose its total funding to date, Schmid said it previously raised two other funding rounds. Pre-seed backers include CEE-focused VC firm Credo, which also backed ElevenLabs and UiPath. According to sources, EquiLibre’s $10 million seed round was led by Blossom Capital at a $140 million valuation.
Sellers confirmed that the Series A $500 million valuation was a big jump. But it also comes after the winds have changed favorably for reinforcement learning (RL), including in trading. “When we started, people were skeptical,” said Schmid. “But now RL is the standard. Because we started four years back, we believe we are ahead.”
The prospect of frontier AI labs by DeepMind alumni is an area of hot pursuit by VCs. Another recent example is Ineffable Intelligence, which recently raised $1.1 billion.
Competitive Landscape
Still, there is a risk that EquiLibre will get leapfrogged by competitors. Trading giant Jane Street, for instance, experiments with LLMs “or whatever else we need to train good models.” It also claims it has “tens of thousands of high-end GPUs,” while EquiLibre is seeking to squeeze more compute out of way fewer chips and “get more from less,” Schmid said.
Considering the competition, EquiLibre will have to play its cards well to reach its goal of being known as “the AI lab in trading.” But this isn’t poker, and there might be no losers. Says Schmid: “This is not a winner-takes-all market.”