SAP to Acquire Prior Labs to Establish a Globally Leading Frontier AI Lab in Europe

Rhea-AI Summary

SAP (NYSE: SAP) agreed to acquire Prior Labs to create a frontier AI lab for tabular foundation models, with SAP committing to invest more than €1 billion over four years. Prior Labs will operate independently; the transaction is subject to regulatory approval and expected to close in Q2 or Q3 2026.

Prior Labs' TabPFN-2.6 is top-ranked on TabArena and its TabPFN tool has over 3 million downloads. The lab will feed TFMs into SAP AI Core, SAP Business Data Cloud and Joule for enterprise productization.

Positive

• SAP commits >€1 billion investment over four years
• Prior Labs' TabPFN-2.6 is top-performing on TabArena
• TabPFN open-source tool has over 3 million downloads
• Prior Labs to operate as independent frontier AI lab within SAP

Negative

• Transaction pending regulatory approval
• Deal terms were not disclosed, creating valuation uncertainty
• Expected close in Q2/Q3 2026 subjects timing to customary conditions

News Market Reaction – SAP

+0.39%

+0.39% Session close to close

In the May 4 session, SAP gained 0.39%, reflecting a mild positive market reaction.

Data tracked by StockTitan Argus on the day of publication.

Market Context

This announcement expands SAP’s AI strategy by acquiring Prior Labs and committing more than €1 bill...

Analysis

This announcement expands SAP’s AI strategy by acquiring Prior Labs and committing more than €1 billion over four years to build a frontier TFM research lab in Europe. It follows earlier AI acquisitions aimed at data readiness and business transformation. Key factors to watch include regulatory approvals, integration into SAP AI Core and Business Data Cloud, ongoing support for Prior Labs’ open-source TabPFN, and how quickly research output becomes enterprise-grade products.

Key Figures

Planned investment: more than €1 billion Investment horizon: four years Open-source downloads: over 3 million +3 more

6 metrics

Planned investment more than €1 billion SAP commitment to scale Prior Labs over the next four years

Investment horizon four years Timeframe for SAP’s committed investment in Prior Labs

Open-source downloads over 3 million Downloads of Prior Labs’ TabPFN open-source tool

Team-building period 18 months Period over which Prior Labs built its current team

Model version TabPFN-2.6 Top-performing TFM model on TabArena benchmark

Pipeline time reference four-hour Automated machine learning pipeline time matched by TabPFN-2.6

Previous Acquisition,AI Reports

2 past events · Latest: Mar 27 (Positive)

Same Type Pattern 2 events

Date	Event	Sentiment	24h Move	Catalyst
Mar 27	AI acquisition	Positive	-1.8%	Agreement to acquire Reltio to make enterprise data AI-ready.
Jun 05	AI acquisition	Positive	+2.5%	Agreement to acquire WalkMe to enhance Business AI and CX portfolio.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Pattern Detected

AI-related acquisitions have produced mixed reactions: one positive, one negative price move.

Recent Company History

Over the past year, SAP has repeatedly used acquisitions to deepen its AI capabilities. The company agreed to acquire WalkMe in 2024 to enhance business transformation and Business AI offerings, which coincided with a 2.46% price rise. In March 2026, SAP announced plans to acquire Reltio to make SAP and non-SAP data AI-ready, but shares fell 1.83%. Today’s Prior Labs acquisition fits this ongoing AI and data strategy.

Key Terms

large language models, tabular foundation models, llms, automated machine learning, +3 more

7 terms

large language models technical

"Large language models (LLMs) struggle to make accurate predictions on structured business data"

Large language models are advanced AI systems trained on vast amounts of text to understand and generate human-like writing, like a very fast reader and writer that learns patterns in words and sentences. They matter to investors because they can change how companies operate—automating customer service, speeding analysis, cutting costs, creating new products—and they introduce risks around accuracy, security and regulation that can affect a firm’s revenue and reputation.

tabular foundation models technical

"Prior Labs, the pioneer of Tabular Foundation Models (TFMs), announced that they have entered"

Tabular foundation models are large AI systems trained to understand and work with tabular data — the rows-and-columns format used in spreadsheets and databases. Like a Swiss Army knife for spreadsheets, they can spot patterns, fill in missing values, and make forecasts across many datasets without building a new model from scratch. For investors, they can speed and standardize data-driven decisions, reduce manual analysis, and potentially lower the time and cost to extract actionable insights from financial and operational records.

llms technical

"Large language models (LLMs) struggle to make accurate predictions on structured business data"

Large language models are advanced computer programs that read and generate human-like text by learning patterns from huge amounts of written material; think of them as digital employees that can draft reports, answer questions, summarize documents, or generate code. They matter to investors because they can change a company’s costs, speed of product development, customer service, and competitive edge — and they also create new risks and regulatory questions that can affect profits and valuation.

automated machine learning technical

"TabPFN-2.6 matches the accuracy of a four-hour automated machine learning pipeline — instantly"

Automated machine learning (AutoML) is software that handles the repetitive steps of building predictive models—preparing data, trying different model types, tuning settings and testing outcomes—so useful models can be created faster and with less specialized expertise. For investors, AutoML can lower development costs, speed product rollouts and help companies scale data-driven decisions like pricing, marketing and risk detection, while also creating pressure to adopt or risk falling behind.

in-context learning technical

"SAP will provide in-context learning, allowing users to provide data records to receive instant"

In-context learning is a capability of advanced AI models to learn how to perform a new task simply by being given examples or instructions in the prompt, without changing the model’s underlying software. For investors, it matters because it lets companies add or personalize features quickly and cheaply—like teaching a tool new tricks by example rather than rebuilding it—affecting product rollout speed, operating costs, and competitive edge.

gdpr regulatory

"A single TFM can adapt to any business use case on the fly, resulting in faster time to value with GDPR compliance."

General Data Protection Regulation is a law that sets rules for how organizations must collect, store and use personal data about people, and gives individuals rights over that data. It matters to investors because noncompliance can lead to large fines, higher operating costs and damaged reputation, while strong compliance can be a competitive advantage—think of it as a strict safety code for handling customer information.

agentic ai systems technical

"will power agentic AI systems capable of understanding high-level goals, combining tables"

Agentic AI systems are artificial intelligence programs designed to set goals and take actions on their own, such as planning steps, making decisions, and interacting with digital or physical environments without constant human direction. For investors, they matter because they can automate complex work, create new revenue streams or cost savings, and also introduce risks around reliability, oversight, legal liability, and regulation—similar to hiring an autonomous employee who can both boost productivity and require new controls.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Acquisition doubles down on SAP's early mover advantage in tabular foundation models

WALLDORF, Germany and FREIBURG, Germany, May 4, 2026 /PRNewswire/ -- SAP SE (NYSE: SAP) and Prior Labs, the pioneer of Tabular Foundation Models (TFMs), 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. 

"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."

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. 

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 further support this open-source strategy. The 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 Schölkopf, director of Max Planck Institute for Intelligent Systems and ELLIS president, both of whom will serve on Prior Labs' scientific advisory board as it scales to a globally leading frontier AI lab.  

Accelerating Innovation

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.

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

About Prior Labs
Prior Labs is the pioneer of Tabular Foundation Models, a new category of AI purpose-built for structured data. Founded by Frank Hutter, Noah Hollmann & Sauraj Gambhir, Prior Labs' TabPFN model series, published in Nature, set the state-of-the-art on tabular benchmarks across hundreds of independent academic studies. Prior Labs is scaling tabular foundation models to handle millions of rows, real-time inference, and entirely new data modalities, while building the infrastructure to deploy them in production across some of the most demanding industries on earth.

Headquartered in Freiburg, Germany, and offices in Berlin and New York City, Prior Labs has built one of the leading AI research teams globally, with researchers recruited from Google, Apple, Amazon, Microsoft, G-Research, Jane Street, Goldman Sachs, and CERN. www.priorlabs.ai

About SAP
As a global leader in enterprise applications and business AI, SAP (NYSE: SAP) stands at the nexus of business and technology. For over 50 years, organizations have trusted SAP to bring out their best by uniting business-critical operations spanning finance, procurement, HR, supply chain, and customer experience. For more information, visit www.sap.com 

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SOURCE SAP SE

FAQ

What did SAP announce about acquiring Prior Labs (SAP) on May 4, 2026?

SAP announced an agreement to acquire Prior Labs to form a frontier AI lab focused on tabular models. According to the company, SAP will invest more than €1 billion over four years and intends to keep Prior Labs operating independently while pursuing product integration.

How much will SAP invest in Prior Labs and over what timeline (SAP)?

SAP said it will invest more than €1 billion in Prior Labs over four years. According to the company, that funding is intended to scale Prior Labs into a globally leading frontier AI lab for structured business data and productization.

When is the SAP acquisition of Prior Labs expected to close and what approvals are required?

The transaction is expected to close in Q2 or Q3 2026, subject to customary closing conditions. According to the company, the deal remains pending regulatory approval and other standard closing requirements before completion.

What is Prior Labs' TabPFN and why is it significant to SAP (SAP)?

TabPFN is an open-source tabular foundation model tool widely adopted by developers, with over 3 million downloads. According to the company, TabPFN-2.6 ranks top on TabArena, providing predictive capability for structured business data.

How will Prior Labs technology be used across SAP products like SAP AI Core and Joule (SAP)?

SAP plans to integrate Prior Labs' TFMs into SAP AI Core, SAP Business Data Cloud and the agentic layer with Joule to productize tabular AI. According to the company, this aims to provide in-context learning and instant predictions without retraining.