Three former DeepMind researchers who created DeepStack, the first AI to defeat professional poker players at no-limit Texas hold’em, have raised a Series A at a $500 million valuation for their Prague-based startup EquiLibre Technologies. The company’s autonomous AI agents now trade billions in daily volume across the S&P 500 and Nasdaq.
The round was led by Creandum. While neither side disclosed the round size, Creandum vice president Cameron Sellers told TechCrunch it was “the largest single investment the firm has ever made in one go into a company.” The valuation jumped from $140 million at seed, which was led by Blossom Capital.
From Poker to Markets
CEO Martin Schmid, CTO Rudolf Kadlec, and CSO Matej Moravcik built their trading system on reinforcement learning, the same AI training technique that powered their poker research at DeepMind’s Edmonton lab. Reinforcement learning works by letting agents learn from rewards rather than labeled data, and financial markets provide a clean scoring function.
“The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?” Schmid told TechCrunch.
In partnership with Tower Research Capital, EquiLibre’s agents have been live-trading since 2025, starting with crypto and expanding to equities. The startup claims “a perfect record of zero negative months since inception,” according to TechCrunch.
The RL Tailwind
The fundraise reflects a broader shift in investor appetite toward reinforcement learning startups founded by DeepMind alumni. Ineffable Intelligence, another ex-DeepMind venture, raised $1.1 billion in April. EquiLibre is notable as one of the few in the cohort based outside the UK.
“When we started, people were skeptical,” Schmid said. “But now RL is the standard. Because we started four years back, we believe we are ahead.”
The startup currently employs 25 people and plans to use the funding to scale compute infrastructure, building what it expects to be one of the largest compute clusters in Central and Eastern Europe.
Competition and Scale
EquiLibre faces competition from firms with far more hardware. Jane Street, which posted a major jump in trading revenue in Q1 2026, claims it already uses reinforcement learning with LLMs and has “tens of thousands of high-end GPUs.” EquiLibre’s strategy is to extract more performance from fewer chips.
“This is not a winner-takes-all market,” Schmid said. The startup’s advisory board includes Rich Sutton, who won the 2024 Turing Award for his foundational work on reinforcement learning.
Sellers framed the opportunity in venture terms: “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.”
Schmid was more direct about what drives the team: “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.”