SAP has agreed to acquire Dremio and Prior Labs in a twin move that extends its reach across two layers of enterprise AI: the data architecture beneath large-scale analytics and agentic systems, and the model research needed for structured business data. Terms of both transactions were not disclosed.
Dremio is expected to close in Q3 2026, subject to customary conditions and regulatory approval. The Prior Labs deal is also pending regulatory clearance. Prior Labs will continue to operate independently, and SAP said it plans to invest more than €1 billion over the next four years to scale it into a frontier AI lab focused on structured enterprise data.
The Dremio acquisition gives SAP a clearer route to unifying SAP and non-SAP data without forcing customers into another round of extraction, duplication, or format conversion. SAP said Dremio will help turn SAP Business Data Cloud into an Apache Iceberg-native enterprise lakehouse, allowing SAP and third-party data to sit on the same open foundation. SAP also plans to use Dremio’s technology to build a universal open catalogue on Apache Polaris and the Apache Iceberg REST Catalog API, creating a shared semantic and governance layer for connected analytics engines.
Prior Labs addresses a different requirement. Large language models are being inserted into enterprise software at pace, but many high-value use cases still depend on tables, forecasts, transaction records, and other structured datasets. Prior Labs specialises in tabular foundation models, which SAP said are better suited to predicting outcomes such as payment delays, supplier risk, upsell potential, and customer churn. Its open-source TabPFN tools have been downloaded more than three million times. SAP said the team will provide a direct path to productisation across SAP AI Core, Business Data Cloud, and the Joule agent layer. Philipp Herzig, SAP’s CTO, said: “Enterprise AI doesn’t stall because the models aren’t good enough; it stalls because the data isn’t ready for AI agents.”
The acquisitions deepen a strategy SAP has been building around governed enterprise data, open architectures, and AI systems that can work across business processes rather than sit above them. Dremio extends the open data fabric needed to assemble context across fragmented enterprise estates. Prior Labs gives SAP tighter control over models built for the structured operational data that runs finance, procurement, HR, and supply chains. The two additions bring data infrastructure, metadata, and specialised model research closer together inside the same stack.
SAP has been building Business Data Cloud as the centre of that architecture. The service is designed to connect mission-critical SAP data with third-party data for analytics and AI, and the company has been expanding the ecosystem around it. In April, SAP and Google Cloud announced new integrations to support multi-agent orchestration, zero-copy access to data across both environments, and more automated customer engagement workflows. SAP has also widened model access and developer controls behind its AI stack, with recent updates bringing Joule into SAP Datasphere and adding newer third-party models to the generative AI hub in AI Foundation.
Enterprise software groups are under pressure to show that AI can operate on governed data inside production systems, not only generate responses in isolation. That has increased the value of technologies that preserve business meaning across multiple data sources, support open formats, and work with structured records without creating another layer of duplication. SAP’s decisions on Dremio and Prior Labs reflect that shift. One deal is centred on interoperability, lakehouse architecture, and shared metadata. The other is centred on models trained for tables, columns, and business variables rather than unstructured text alone.
The emphasis on tabular AI is notable because a large share of enterprise value still sits in structured systems of record, where prediction, classification, and optimisation often carry more weight than fluent text generation. At the same time, the move towards Iceberg and open catalogues reflects a market moving away from closed data silos and towards architectures that can support analytics and AI across mixed environments. SAP is aligning itself with both currents at once: open data formats on one side, and specialised models for structured enterprise data on the other.
Dremio is scheduled to close in the third quarter, while Prior Labs is set to continue as an independent entity backed by new SAP investment. Once completed, the two deals will add depth to SAP’s effort to embed AI inside enterprise workflows that depend on live, structured, and governed data.
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