The world of artificial intelligence continues to push boundaries, and a recent development from Prague-based EquiLibre Technologies proves just how rapidly innovation is accelerating. Founded by three former DeepMind researchers who once built an AI capable of beating humans at poker, this startup has now successfully applied similar technology to the high-stakes world of stock trading. Their strategic bet appears to be paying off handsomely, as EquiLibre Technologies has achieved an impressive valuation of $500 million.
This remarkable valuation follows a Series A funding round, the details of which remain undisclosed, but confirmed to be led by Creandum. In a significant testament to EquiLibre’s potential, Creandum’s vice president, Cameron Sellers, revealed that this investment represents the largest single capital injection the firm has ever made into one company. This monumental backing underscores the venture capital community’s strong belief in the transformative power of EquiLibre’s AI.
From Game Theory to Market Mastery
The secret sauce behind EquiLibre’s success lies in reinforcement learning (RL), an advanced AI training technique. This method, which proved incredibly effective in poker, thrives in environments where self-learning models can be incentivized by clear rewards. EquiLibre CEO Martin Schmid highlights the core simplicity: “The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?”
This isn’t just theoretical money; EquiLibre’s algorithms are making real-world impact. In a strategic partnership with prominent quant firm Tower Research Capital, their AI agents have been actively trading billions in daily volume across major indices like the S&P 500 and NASDAQ. The startup initially rolled out its agents on crypto markets in 2025, and their track record has been nothing short of exceptional.
EquiLibre proudly boasts a “perfect record of zero negative months since inception.” This means that their investments have consistently finished each month in positive territory, showcasing remarkable stability and profitability in volatile markets. Such consistent performance makes them incredibly appealing in the financial sector, where even marginal improvements can translate into significant gains.
A Lab-First Approach with DeepMind Roots
Despite their significant impact on financial markets, EquiLibre’s founders emphasize their identity as “a lab first, not a finance firm.” CEO Martin Schmid, alongside CTO Rudolf Kadlec and CSO Matej Moravcik, don’t hail from traditional finance backgrounds, and their motivation extends beyond market efficiency. Schmid articulates their driving force: “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.”
Their journey began at DeepMind, where they were visiting PhD students at Google’s former AI research office in Edmonton, Canada. There, they developed DeepStack, a groundbreaking AI program that became the first to defeat professional players in no-limit poker. Their advisory board includes luminaries like Rich Sutton, who received the Turing Award in 2024 for his pioneering work in reinforcement learning, further cementing their deep academic roots.
Choosing Prague, Czechia, as their base for EquiLibre was a deliberate strategic move. Schmid explains that returning to their home country allowed them to tap into a strong network of former colleagues and friends from the Czech diaspora. This choice continues to pay dividends, as Schmid notes, “It’s much easier to keep the good people here, because there’s not a new sexy AI thing happening every two months” compared to more saturated tech hubs like San Francisco.
Scaling Innovation and Navigating the Future
Before this impressive Series A, EquiLibre had already secured two other funding rounds, including a pre-seed round with CEE-focused VC firm Credo. Dealroom data further reveals a $10 million seed round led by Blossom Capital, which valued the company at $140 million, highlighting the exponential growth in their valuation. This rapid appreciation reflects the industry’s newfound confidence in reinforcement learning, particularly within financial applications.
Schmid acknowledges that when EquiLibre began, there was considerable skepticism surrounding reinforcement learning’s application in trading. However, he believes the tides have turned dramatically. Now, RL is becoming the industry standard, and by having started four years ago, EquiLibre believes they have a significant head start.
Looking ahead, EquiLibre has ambitious plans to scale its compute infrastructure, aiming to bring online what they expect will be one of the largest compute clusters in Central and Eastern Europe (CEE). This strategic investment will be crucial for maintaining their technological edge and expanding their capabilities. While competitive pressures exist from giants like Jane Street, who also leverage RL and boast vast GPU resources, EquiLibre remains focused on efficiency, striving to “get more from less.”
Despite the competitive landscape, EquiLibre’s founders are optimistic. Schmid believes that unlike poker, the financial trading market is not a “winner-takes-all” scenario. With their unique blend of DeepMind-level AI expertise, a “lab-first” ethos, and a strong strategic foundation in Prague, EquiLibre Technologies is poised to make a lasting mark as a leading AI lab in trading.
Source: TechCrunch – AI
