SAP’s €1 Billion+ Acquisition of Prior Labs: The Inside Story of the Tabular AI Deal

• Rail maintenance — A case study on the Prior Labs site shows Prior Labs partnered with Hitachi to advance predictive maintenance in rail .
• Financial forecasting — A case study documents that Prior Labs and TD (TD Bank) explored TabPFN for financial forecasting at enterprise scale .
• Healthcare and life sciences — Research applications span pancreatic cancer diagnosis, oncology, neurology, and cardiology ; a case study with BostonGene used TabPFN to identify immune system profiles .
• Environmental and energy — The model has been applied to wildfire risk prediction and renewable-energy nowcasting .
• Battery materials — TabPFN-2.5's applications extend to environmental forecasting including algal blooms and wildfire risk, and renewable-energy nowcasting .

Latest model: TabPFN-3 with Thinking Mode

TabPFN-3 was released on May 12, 2026 . It supports datasets up to 1 million rows and 200 features, with native text feature support on the API . The API offering TabPFN-3-Plus (Thinking) introduces inference-time compute scaling (test-time compute) — spending more time during fitting for significantly higher accuracy . On the TabArena benchmark, TabPFN-3-Plus (Thinking) beats all non-TabPFN models by over 200 Elo, and outperforms AutoGluon 1.5 extreme while being 10× faster . TabPFN-3 itself remains open-source .

Deal structure and independence terms

• Acquisition price — Not disclosed, but SAP committed to invest more than €1 billion over four years to grow Prior Labs .
• Independence — Prior Labs continues to operate as an independent entity, retaining its brand, leadership, research agenda, and customer relationships .
• Open-source commitment — SAP fully supports Prior Labs' open-source strategy; TabPFN-3 is released open-source and the model has over 3 million downloads .
• Leadership — Founders Frank Hutter, Noah Hollmann, and Sauraj Gambhir continue leading the team . Yann LeCun and Bernhard Schoelkopf serve on the scientific advisory board .

Strategic rationale from leadership

Philipp Herzig, SAP CTO, said SAP recognized early that the greatest untapped opportunity in enterprise AI was not LLMs but AI built for structured business data. He stated: "Combining their frontier model work with enterprise data and customer reach is how we intend to lead this category globally" .

Frank Hutter, Prior Labs CEO, said: "Joining the SAP family gives us the resources, data environment and customer reach to take this category to its full potential" . In a LinkedIn post after close, he added: "Same team, same offices, same mission, open models, backed by €1B+. What changes? The scale and the planning horizon. SAP is the perfect partner, with an enormous scale of tabular data and distribution" .

The combined entity plans to pursue frontier research in enterprise AI, scientific discovery, causality, relational data, and agentic systems — moving beyond correlation to causation, and enabling agentic AI that understands tables, language, and images to reason and adapt dynamically . SAP also outlined moonshot ambitions in medical data and material sciences, with applications already demonstrated in oncology diagnosis, clinical decision-making, and battery materials research .