German AI Startup Kausable Raises €12 Mn Seed to Build Self-Adapting Reasoning AI

The funding round was led by UVC Partners and Entourage. Existing investors HTGF and Mätch VC also joined the round with additional investment.

Kausable is also supported by several angel investors from the AI industry and research community. These investors are connected with organizations such as Black Forest Labs, OpenAI, Google DeepMind, Noxtua, and the European Laboratory for Learning and Intelligent Systems (ELLIS).

“The world evolves rapidly, and so should AI. However, even the most capable current AI systems are very static in how they interpret the world and need constant, time-consuming, and costly retraining. With kausable we solve this problem by developing a new kind of world model that learns efficiently and robustly on its own and adapts to the ever-changing world. This offers huge opportunities across highly dynamic domains, such as robotics, the energy sector, and finance,” said Johannes Haux, CEO and co-founder of kausable.

“Most AI models are trained to remember the past. kausable is building AI that can reason about the future. Instead of relying on ever-larger datasets and constant retraining, they’re developing a fundamentally different approach: systems that adapt, infer causality and solve problems they have never seen before. It’s an ambitious scientific bet, and exactly the kind of foundational AI company we’re excited to back,” emphasised Pieterjan Bouten, co-founder of Entourage.

Founded in 2025 by Johannes Haux, Dr. Benjamin Herdeanu, and Gregor Ramien, Kausable is developing a new AI foundation model that focuses on reasoning. It can learn from a small amount of data and does not need to be retrained every time it faces a new situation.

The AI is designed to adapt on its own, even when it encounters scenarios that were not expected when it was first built. This makes it more flexible and efficient than many traditional AI models.

The company has also published AI research with Columbia University. In addition, it created TipPFN, a zero-shot AI model that can predict rare but important events in complex and constantly changing systems.

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