SAP and Prior Labs announced that they have entered into a definitive agreement for SAP to purchase Prior Labs, accelerating SAP’s success in TFMs that started 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. The transaction is still pending regulatory approval.
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 based on tabular data such as payment delays, supplier risks, upsell opportunities, customer churn risk and more.
Once the transaction is closed, with Prior Labs, SAP will have the special 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 with SAP AI Core and SAP Business Data Cloud as well as the agentic layer with Joule.
Prior Labs’ TabPFN-2.6 is the top-performing model on TabArena, the top 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 and machine learning experts. With Prior Labs’ models, SAP will provide in-context learning, allowing users to provide data records to receive instant, reliable predictions without any model training. A single TFM can adapt to any business use case on the fly, resulting in faster time to value with 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.
After the close, SAP and Prior Labs plan to turn top AI research into enterprise-ready innovation, allowing customers to get even more value out of their tabular business data. True intelligence requires moving beyond correlation to understand causation. Answering “What will happen?” is useful, but answering why it will happen is transformative.
The transaction is expected to close in Q2 or Q3 of 2026, subject to customary closing conditions, including regulatory approvals.
