The DeepMind trio who built a poker AI are now making money for quant hedge funds
EquiLibre Technologies, a Prague-based AI lab founded by three ex-DeepMind researchers, is now valued at more than $500 million. Three former DeepMind researchers who created an AI that beat humans at poker have now applied the same technology to trading stocks - 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.
Key Takeaways
- The round was led by Creandum, and, although the VC also declined to disclose the size of the round, vice president Cameron Sellers confirmed that it was the largest single investment the firm "has ever made in one go into a company," he told TechCrunch.
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.
- That made the startup appealing to Creandum, Sellers said.
"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," Sellers said.
- 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 said.
The prospect of frontier AI by by DeepMind alumni is an area of hot pursuit by VCs as well.
- While there, they built DeepStack , the first AI program to defeat pro players at no-limit poker, also known as Texas hold 'em .
They also worked with professors who are now part of the startup's high-profile advisory board - including Rich Sutton, who went on to receive the Turing award in 2024 for his work on reinforcement learning.
- Not that EquiLibre is the only hot AI startup in town.
Stats & Key Facts
- #EquiLibre Technologies, a Prague-based AI lab founded by three ex-DeepMind researchers, is now valued at more than $500 million.
- #EquiLibre Technologies, a Prague-based AI lab founded by three ex-DeepMind researchers, is now valued at more than $500 million.
- #Their Prague-based AI lab, EquiLibre Technologies , is now valued at $500 million after raising an undisclosed-sum Series A, TechCrunch learned.
- #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.
The round was led by Creandum, and, although the VC also declined to disclose the size of the round, vice president Cameron Sellers confirmed that it was the largest single investment the firm "has ever made in one go into a company," he told TechCrunch. 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?"
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. By applying its AI to quant hedge funds, the startup is in a field where automation is commonplace and, if successful, improvements can quickly turn into cash.
That made the startup appealing to Creandum, Sellers said. "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," Sellers said. But he noted that EquiLibre explicitly defines itself as "a lab first, not a finance firm."
For more details please read the original article at TechCrunch AI.
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