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Prior Labs is tackling one of AI's hardest problems: making sense of the messy, structured data that powers most businesses. While transformers conquered text and images, tabular data — think sales records, inventory logs, customer databases — has remained stubbornly difficult to model at scale. Prior Labs has built pre-trained foundation models specifically for this challenge, enabling companies to generate predictions on structured data without needing massive in-house ML teams or custom pipelines for every use case. It's a bet that tabular AI can follow the same arc as LLMs: pre-train once, fine-tune everywhere. For engineers and data scientists who want to work on genuinely novel ML infrastructure with immediate real-world impact, this is a rare chance to shape how enterprises unlock value from their structured data.
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