SAP closes €1B bet on tabular AI with Prior Labs

What happened?

SAP, the German enterprise software giant, has closed the acquisition of Prior Labs, a startup based in Freiburg specializing in artificial intelligence for tabular data. According to The Next Web, the deal value exceeds €1 billion. Prior Labs develops AI models that understand and process structured data (like spreadsheets and databases), unlike language models that dominate unstructured text. The operation, which has already received all regulatory approvals, places SAP in a unique position within the enterprise AI ecosystem.

Founded in 2021 by a team of researchers from the Max Planck Institute, Prior Labs had raised around €40 million in previous rounds, according to PitchBook data. Its technology is based on an approach known as 'tabular foundation models,' which are neural networks specifically trained on structured data, capable of handling missing values, relationships between columns, and complex numerical distributions. Unlike language models like GPT-4, which require enormous amounts of text, Prior Labs achieves competitive results with much smaller datasets, which is crucial for enterprise environments where data is sensitive and often limited.

Why is it important?

While the AI industry has focused on chatbots and generative text models, SAP is betting on a less visible but critical niche: tabular data. These represent the backbone of most business processes (ERP, CRM, finance, logistics). Integrating Prior Labs' technology will allow SAP to offer advanced analytics, predictions, and automation directly on the data its clients already manage, without needing to move it to external platforms. This reduces security risks and integration costs, a key factor for large corporations with strict data governance policies.

Historically, SAP has tried to integrate AI into its products, such as SAP Leonardo and SAP AI Core, but these initiatives did not achieve massive impact. The acquisition of Prior Labs represents a strategy shift: instead of building from scratch, SAP buys mature and proven technology. According to Gartner analysts, the market for AI on tabular data will grow at a compound annual rate of 28% until 2028, driven by the need to automate business processes. SAP, with over 400,000 customers in 190 countries, is in an excellent position to capitalize on this trend.

Market consequences

• Competitive advantage: SAP differentiates itself from competitors like Microsoft (Copilot) and Google (Vertex AI) by focusing on structured data, an area where its domain knowledge is deep. While Microsoft integrates Copilot into Office 365 and Google into Workspace, SAP can offer AI that understands financial transactions, inventories, and supply chains natively. For example, a CFO could ask 'What was the cost variance in the last quarter for the EMEA region?' and get an accurate answer without needing to export data to Excel.
• Closed ecosystem: The acquisition could accelerate the creation of a native AI assistant in SAP S/4HANA, Business ByDesign, and SuccessFactors, reinforcing customer lock-in. Clients already investing in the SAP ecosystem will find more value in integrating these capabilities, making migration to competitors like Oracle or Workday more difficult. Additionally, SAP could offer pre-trained models for specific industries (manufacturing, retail, banking), increasing differentiation.
• Impact on startups: Other tabular AI startups (like Einblick, Obviously AI, and DataChat) could see increased investor interest or seek to be acquired by large platforms like Salesforce, Oracle, or IBM. SAP's deal validates the segment and could trigger a wave of consolidation. According to CB Insights, investments in tabular AI increased by 45% in 2025 compared to the previous year, and are expected to continue rising.
• Competitor reaction: Microsoft has already integrated tabular capabilities into Azure Machine Learning, but its approach is more generic. Oracle, meanwhile, has developed its own AI engine for databases but lacks a foundational model like Prior Labs'. SAP's move pressures these players to accelerate their own acquisitions or internal developments.

What readers should know

Prior Labs' technology is not a conversational language model but a system specifically trained to understand relationships between columns, detect anomalies, and generate insights from numerical and categorical data. SAP plans to integrate it into its products to enable natural language queries on business data, but also to automate tasks like reconciliations, forecasts, and fraud detection. For example, an SAP system could automatically identify unusual patterns in invoices, suggest inventory adjustments based on seasonal trends, or generate financial reports with just a natural language question.

The deal has already received all regulatory approvals, so its impact will begin to be seen in upcoming SAP releases. The first functionalities are expected to appear in SAP S/4HANA Cloud by the end of 2026, followed by integrations in SuccessFactors and Ariba. Current SAP customers will be able to access these capabilities through additional licenses or as part of premium subscriptions, generating new revenue streams for the company.

In summary, SAP's acquisition of Prior Labs is not just a technology purchase but a strategic bet on redefining how companies interact with their data. While generative AI grabs headlines, SAP focuses on the 80% of corporate data that resides in tables, a move that could transform business productivity in the long term.