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Fundamental builds foundation models for tabular enterprise data, including NEXUS, a Large Tabular Model that adapts to new tasks via in-context learning.
Prior Labs
Prior Labs builds foundation models for tabular data, including TabPFN, a Nature-published model for spreadsheets and databases used across science, medicine and finance.
Prior Labs builds foundation models for tabular data - spreadsheets and databases - with the aim of transforming scientific discovery, medical research, financial modelling and business intelligence. Its flagship model, TabPFN, is a foundation model for tabular data that achieves state-of-the-art performance on tabular machine learning tasks. The work behind TabPFN was published in Nature, and the model has been downloaded over 2.5 million times and attracted 5,500 GitHub stars.
The company's technical scope spans tabular machine learning, foundation models, agentic AI and multimodal systems combining tables, language and images, alongside domain knowledge reasoning and inference. Its stated mission extends beyond prediction towards genuinely agentic AI systems.
Prior Labs employs more than 20 engineers and researchers drawn from leading institutions and describes itself as scaling quickly. The company is backed by Balderton Capital, XTX Ventures and the Hector Foundation, and is advised by Turing Award winner Yann LeCun. Further details are available at https://priorlabs.ai/.
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