Prior Labs
Open-source tabular foundation model for instant predictions on structured data.
About Prior Labs
Prior Labs develops TabPFN, an open-source tabular foundation model that delivers state-of-the-art predictions on structured data without manual feature engineering. TabPFN 2.5 handles up to 50,000 data points and 2,000 features, with enterprise-scale versions supporting 10 million rows. Used by Hitachi for predictive maintenance and Oxford Cancer Analytics for disease detection.
Key Features
💰 Pricing
Open source core model. Enterprise versions available with custom pricing.
Free open-source TabPFN model
Enterprise-scale models and support
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