Business

SAP expands data and AI stack with acquisitions of Dremio and Prior Labs

SAP completed two acquisitions in July, adding Dremio and Prior Labs to its portfolio to strengthen enterprise data management and AI capabilities.

SAP expands data and AI stack with acquisitions of Dremio and Prior Labs

SAP completed two acquisitions in July, bringing Dremio and Prior Labs into its group to reinforce the company’s enterprise data management and artificial intelligence portfolio. The transactions are intended to accelerate practical, trustworthy AI adoption in business processes by combining open data infrastructure with specialized AI research.

What Dremio adds

Dremio’s open, high-performance data platform will augment SAP Business Data Cloud. The technology enables data from SAP and non-SAP systems to be accessed through a unified, open architecture for analytics and AI tasks without extensive data movement or format conversion.

Dremio builds on the Apache Iceberg open table format and leverages Apache Polaris and Apache Arrow, providing performance, flexibility and interoperability across systems. Its serverless architecture automatically scales with load, while a semantic layer preserves data meaning, relationships, permissions and provenance — contextual elements required for AI outputs to be interpretable and auditable.

When integrated into SAP’s business applications, Dremio can connect directly to corporate finance, procurement, supply chain, HR and customer management processes. This capability is particularly important as autonomous AI agents proliferate, since reliable decision support depends on up-to-date, governed data with business context.

What Prior Labs adds

Prior Labs, founded in 2024 in Germany, is a pioneer in tabular foundational models. These models are designed specifically for structured business data — such as tables, databases and financial, production or supply-chain records — rather than primarily processing text.

In a short time, Prior Labs has become an internationally recognized research team. Its TabPFN models demonstrate advances in analyzing structured data and the potential of targeted AI solutions for enterprise use. According to SAP’s announcement, Prior Labs will continue to operate within SAP as an independent brand with its own leadership and research program.

Investment and objectives

Beyond an undisclosed purchase price, SAP will invest more than €1 billion over the next four years to expand Prior Labs’ team, develop infrastructure and support long-term research. The stated aim is to establish a globally relevant European AI research laboratory focused on structured enterprise data.

Strategic context and expert view

The acquisitions reflect SAP’s dual innovation strategy: combining strong in-house R&D with targeted integration of external technologies. Hidvégi Péter, Managing Director of SAP Hungary, emphasized that innovation today is not solely the result of closed development cycles but requires global collaboration and timely identification of specialist market players.

Hidvégi Péter said: “The acquisitions of Dremio and Prior Labs exemplify this approach: SAP is not merely buying companies, but bringing together top talent, open technologies and research outcomes with its business applications to deliver tangible and safely deployable innovations for customers.”

The two transactions complement each other in SAP’s portfolio: Dremio ensures open, unified and efficient access to corporate data, while Prior Labs provides advanced models to interpret that data. SAP argues that the real value of enterprise AI depends not only on model sophistication but also on data quality, business context, governability and the degree to which solutions integrate into daily business processes.

Implications

SAP intends the combined approach of internal development and selective acquisitions to keep it both a reliable technology partner and able to react quickly to new opportunities. The integration of Dremio and Prior Labs thus represents more than two completed deals: it is a step toward accelerating data-driven, intelligent and increasingly autonomous enterprise operations.