Where is Prior Labs headquartered?

Prior Labs is headquartered in Freiburg, Germany. The company has a team of 10-50 people.

What does Prior Labs do?

Prior Labs operates in the AI in Analytics & BI sector. Prior Labs develops enterprise-scale AI foundation models for structured/tabular data analysis, enabling fast and accurate predictions on complex datasets World's first AI models capable of processing 10M+ rows of structured data in seconds, enabling real-time decision making and unlocking value from previously inaccessible datasets

When was Prior Labs founded?

Prior Labs was founded in 2024. It is based in Freiburg, Germany.

Who is the CEO of Prior Labs?

Frank Hutter is the CEO of Prior Labs. The company was founded in 2024.

Where is Prior Labs located?

Prior Labs is headquartered in Freiburg, Germany.

What funding stage is Prior Labs at?

Prior Labs is currently at the Acquired stage.

How many employees does Prior Labs have?

Prior Labs has approximately 10-50 employees.

Prior Labs

Category: AI in Analytics & BI

Prior Labs develops enterprise-scale AI foundation models for structured/tabular data analysis, enabling fast and accurate predictions on complex datasets Prior Labs was founded in 2024. The company is led by Frank Hutter. Based in Freiburg, Germany. Team size: 10-50. Total funding raised: €9 million. Latest round: Acquired. Key investors include Balderton Capital, XTX Ventures, Hector Foundation, Atlantic Labs, Galion.exe, Thomas Wolf (Hugging Face), Peter Sarlin (Silo AI), Guy Podjarny (Snyk), Ed Grefenstette (DeepMind), Robin Rombach (Black Forest Labs), Chris Lynch (Data Robot), Ash Kulkarni (Elastic).

Founded: 2024
Headquarters: Freiburg, Germany
Team size: 10-50
Total funding: €9 million

Value proposition

World's first AI models capable of processing 10M+ rows of structured data in seconds, enabling real-time decision making and unlocking value from previously inaccessible datasets

Products and solutions

TabPFN-3 (latest default OSS model; up to 1M rows, May 2026), TabPFN-3-Plus (API; Thinking mode + native text features), TabPFN-2.6 (previous default), TabPFN-2.5 / TabPFN-2.5-Plus, TabPFNv2 (Nature 2025), TabPFN-TS / TabPFN-TS-3 (time-series), TabPFN-Rel (relational harness for multi-table DBs, Aug 2026), TabPFN Enterprise / VPC deployments, RelArena-α relational benchmark, MCP agent integrations

Unique value

Specialized focus on structured/tabular data (vs. text/images) with breakthrough scaling (TabPFN-3: up to 1M rows in-context); Published in Nature; 4M+ downloads; ~8K GitHub stars; acquired by SAP as independent frontier AI lab

Target customer

Enterprises handling large-scale structured data in industries like healthcare, finance, manufacturing, and life sciences

Industries served

Healthcare (genomics, precision medicine), Financial services (risk modeling, fraud detection), Manufacturing (predictive maintenance), Environmental monitoring, Pharmaceutical R&D, Energy, Technology, Industrials

Technology advantage

TabPFN's hybrid architecture combines neural networks with symbolic AI for both speed (millisecond predictions) and interpretability; patented AutoML techniques; domain-adaptive transfer learning; handles 10M+ rows in seconds

How they differentiate

Prior Labs differentiates through TabPFN, a pre-trained foundation model for tabular data that delivers predictions in seconds with minimal training. Unlike traditional AutoML tools that require hours of training, TabPFN performs inference via in-context learning, reducing training time from hours to seconds while handling missing values and unstructured features.

Main competitors

Ikigai Labs, Neuralk AI, TabICL (INRIA), AutoGluon, Google AutoML, Amazon SageMaker, Microsoft Azure ML

Key partnerships

SAP (parent; Prior Labs operates as independent frontier AI lab; productization via SAP AI Core / Business Data Cloud / Joule), Hugging Face (model distribution and open-source collaboration), Microsoft Azure AI Foundry (cloud deployment), AWS SageMaker (cloud deployment), Databricks (Lakehouse deployment), BostonGene (healthtech), Hitachi Rail (predictive maintenance), XTX Markets (financial services), Yann LeCun & Bernhard Schölkopf (scientific advisory board)

Notable customers

Oxford Cancer Analytics (UK biotech), BostonGene, Hitachi Rail, Taktile, Exito, NHS / UHNM NHS Trust, European Commission, Creditplus Bank, TD Bank

Major milestones

SAP acquisition closed (17 Jul 2026); independent lab with €1B+ commitment, SAP definitive agreement announced (4 May 2026), TabPFN-3 / TabPFN-3-Plus release (May 2026), TabPFN-Rel + RelArena-α release (Aug 2026), TabPFN-2.6 release (March 2026), Nature publication (2025), €9M pre-seed (February 2025), 4M+ downloads; ~8K GitHub stars

Growth metrics

Acquired by SAP (closed Jul 2026) as independent frontier AI lab with €1B+ 4-year commitment; TabPFN-3 released May 2026 as new default; TabPFN-Rel relational release Aug 2026; 4M+ downloads; ~8K GitHub stars; Azure AI Foundry / AWS SageMaker / Databricks deployments

Market positioning

Positioned as a leader in enterprise-scale tabular AI, Prior Labs targets industries requiring rapid, accurate predictions from structured data (finance, healthcare, biotech). Their models are marketed as a self-reinforcing cycle of scale due to adaptability across datasets, with TabPFN-2.5 handling up to 10 million rows.

Geographic focus

Europe (Freiburg, Germany-based), with enterprise clients globally including US, UK, and European markets

Patents and IP

Multiple pending patents related to 'neural-symbolic hybrid architectures for tabular data' and 'automated feature engineering in high-dimensional structured datasets'

About Frank Hutter

World's most cited AutoML researcher; Professor of Machine Learning at University of Freiburg; Co-founder of Prior Labs from ELLIS ecosystem; Former research leader in automated machine learning (AutoML)

Latest news about Prior Labs

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Official website: https://priorlabs.ai