Prague’s EquiLibre Hits $500 Million Valuation
EquiLibre Technologies, a Prague-based artificial intelligence lab founded by former DeepMind researchers, has secured a Series A funding round led by Creandum. The investment pushes the startup’s valuation to $500 million. The company utilizes reinforcement learning to automate financial trading, reporting consistent monthly gains since its deployment on live markets.
From Poker Tables to Global Exchanges
The startup’s founders—CEO Martin Schmid, CTO Rudolf Kadlec, and CSO Matej Moravcik—honed their expertise as visiting PhD students at the Google-owned company’s former research office in Edmonton, Alberta. Their track record includes the creation of DeepStack, the first AI program to defeat professional players at no-limit poker, also known as Texas hold ’em. Their research included collaborations with Rich Sutton, a pioneer in reinforcement learning who received the 2024 Turing Award.
The trio chose to establish their lab in Prague, citing the local talent pool and a desire to avoid the high turnover rates common in hubs like San Francisco.
The Mechanics of Automated Returns
EquiLibre applies reinforcement learning—a machine learning technique where models are incentivized through rewards—to identify patterns in financial markets.
“The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?” according to CEO Martin Schmid.
By partnering with quant firm Tower Research Capital, the startup has deployed its algorithms to trade billions in daily volume across the S&P 500 and Nasdaq. The company reports that its agents have maintained a record of zero negative months since their initial deployment in crypto markets in 2025.
Rapid Growth Amid Market Competition
The $500 million valuation marks a significant increase from the company’s earlier funding milestones. According to Dealroom data, EquiLibre previously raised a $10 million seed round led by Blossom Capital at a $140 million valuation.
The startup’s growth has attracted venture capital firms like Creandum, which identified the financial sector as a high-potential market for AI-driven automation. However, the field is increasingly crowded. Major trading firms, including Jane Street, have stated they already incorporate reinforcement learning and LLMs into their trading infrastructure. While Jane Street manages massive computational resources, Schmid stated that EquiLibre’s strategy involves maximizing efficiency, or “getting more from less” compute power.
Scaling Research in Central Europe
EquiLibre is currently focused on scaling its technical capabilities. The company intends to build what it expects will be one of the largest compute clusters in Central and Eastern Europe to support its ongoing research and trading operations.
Despite its success in financial markets, the company maintains its identity as a research lab rather than a traditional finance firm. Schmid noted that the team’s primary motivation remains the technical challenge of building novel AI systems, and he suggested that the market for automated trading is large enough to accommodate multiple participants rather than operating as a “winner-takes-all” environment.