kausable raises €12M to rethink how AI learns
Tech.eu Cate Lawrence
European AI startup kausable raised €12 million in seed funding to develop reasoning-first AI models that adapt to new tasks and contexts without costly retraining. The company trains foundation models once on synthetic causal data, then enables them to learn new behaviors from just a handful of examples, demonstrated through its TipPFN forecasting model tested across 15 domains. This approach reduces data requirements and computational costs compared to conventional foundation models, positioning kausable to address industrial systems that currently require expensive, repeated AI retraining cycles.
Why it matters
AI systems need constant, costly retraining. European AI startup kausable raises €12 million in a seed funding round to solve this problem by developing reasoning-first frontier AI that adapts efficie...
