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The world generates petabytes of video every day, and almost none of it is readable to machines. Frontier VLMs that can unlock this (like Gemini) are too expensive to run at the volume real industries have, too generic for any single task, and can't be deployed on-prem where sensitive video lives.
We are building an auto vision factory: take video plus a customer's objective, distill a frontier model, and post-train a small open model that is SOTA on that one task and serve it blazingly fast. Our first product, Marlin, is a 2B-parameter open-weights video VLM that matches Gemini-2.5-flash on dense captioning and temporal grounding at a fraction of the cost.
Founder at Kailash Labs. Previously visiting researcher at KAIST working on robot learning and long-term memory for decision-making agents. Published at NeurIPS (spotlight) on offline RL during research at Tsinghua. Aerospace Engineering from IIT Bombay.
Founded 2026 · Source
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