The completed deal brings one of the world’s leading Tabular Foundation Model research teams into the SAP family, doubling down on SAP’s early mover advantage in structured-data AI.
SAP SE announced it has completed the acquisition of Prior Labs, the pioneer of Tabular Foundation Models (TFMs), accelerating SAP’s success in TFMs, which began with SAP-RPT-1, and bringing one of the world’s leading TFM research teams into the SAP family.
Prior Labs will continue to operate as an independent entity, with SAP committing to invest more than €1 billion over the next four years to scale it into a globally leading frontier AI lab for the structured data that runs the world’s businesses. Terms of the deal were not disclosed.
Large language models (LLMs) struggle to make accurate predictions on structured business data because they have only a rudimentary understanding of tables, numbers, and statistics. Unlike LLMs, TFMs are purpose-built for this type of data and can accurately predict business outcomes from tabular data, such as payment delays, supplier risks, upsell opportunities, customer churn risk, and more.
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“Early on, SAP recognized that the greatest untapped opportunity in enterprise AI wasn’t large language models; it was AI built for the structured data that runs the world’s businesses,” SAP CTO Philipp Herzig said. “We built SAP-RPT-1 to prove that conviction for enterprise data. Prior Labs has built a leading TFM on public benchmarks and built one of the leading research teams in this category. Combining their frontier model work with enterprise data and customer reach is how we intend to lead this category globally.”
“Over the last 18 months, Prior Labs has built an incredible team, increasing the velocity in tabular foundation models,” Prior Labs CEO Frank Hutter said. “Joining the SAP family gives us the resources, data environment, and customer reach to take this category to its full potential.”
With Prior Labs now part of SAP, the two companies have the opportunity to establish an industry-leading AI research lab and shape a new category in TFMs. The lab will operate as an independent unit to ensure research velocity, while SAP provides long-term investment and a direct path to productization across the SAP portfolio, including SAP AI Core and SAP Business Data Cloud, as well as the agentic layer with Joule.
With over 3 million downloads, Prior Labs’ TabPFN is a widely adopted open-source tool for tabular AI, supporting a dynamic developer ecosystem. SAP is fully committed to continuing to support this open-source strategy. Prior Labs cofounders Frank Hutter, Noah Hollmann, and Sauraj Gambhir lead a team of world-class AI researchers and practitioners. The company works with leading scientists in the field, including Yann LeCun, ACM A.M. Turing Award winner and executive chairman at Advanced Machine Intelligence, and Bernhard Schoelkopf, director of the Max Planck Institute for Intelligent Systems and ELLIS president, both of whom will serve on Prior Labs’ scientific advisory board as it scales into a globally leading frontier AI lab.
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Accelerating Innovation
Prior Labs’ TabPFN-2.6 is the top-performing model on TabArena, the leading benchmark for TFMs. TabPFN-2.6 matches the accuracy of a four-hour automated machine learning pipeline — instantly, in a single model, at a fraction of the complexity.
With a conversational interface layered on top, business users can ask questions in natural language, generate or select datasets, and run “what-if” scenarios without needing to be data science or machine learning experts. With Prior Labs’ models, SAP will provide in-context learning, allowing users to supply data records and receive instant, reliable predictions without any model training. A single TFM can adapt to any business use case on the fly, delivering faster time-to-value while ensuring GDPR compliance.
With Prior Labs, SAP will deliver TFMs with superior predictive capability that understand tables natively, learning statistical reasoning directly from data, and will power agentic AI systems capable of understanding high-level goals, combining tables, language, and images to reason, integrate domain knowledge, infer causality, and adapt dynamically.
Now that the deal has closed, SAP and Prior Labs plan to turn top AI research into enterprise-ready innovation, enabling customers to get even more value from their tabular business data. True intelligence requires moving beyond correlation to understand causation. Answering “What will happen?” is useful, but answering “Why will it happen?” is transformative.
