Physical AI startup Mowito raises $3 million in pre-seed funding round | Company News
Physical artificial intelligence (AI) startup Mowito, which is building foundation models for industrial robot arms, on Tuesday said it has raised $3 million in a pre-seed funding round led by Version One Ventures.
The round also saw participation from All In Capital, Unisol, iSeed, and angel investors including Soumith Chintala (Thinking Machines Lab), Adarsh Kulkarni (Foundry Robotics), Ashish Kulkarni (Coformer.ai), and Vaibhav Domkundwar (Better Capital).
The company said the funding will be used to accelerate its expansion in the United States, strengthen its engineering and go-to-market teams, and scale deployments across automotive and electronics manufacturers.
Founded in 2024, Mowito is developing physical AI models that enable industrial robots to learn directly from task demonstrations, eliminating the need for conventional programming while maintaining the precision required for manufacturing operations.
The company serves automotive and electronics manufacturers globally, with teams based in Bengaluru and Detroit.
Mowito said its robots are already operating on manufacturing lines at a Fortune 500 automotive company and one of the world’s largest electronics contract manufacturers, supporting high-precision assembly applications in the automotive and consumer electronics sectors.
“Manufacturing has reached a point where hardware is no longer the bottleneck — software is. Factory robots shouldn’t need to be reprogrammed every time production changes. We believe robots should learn the same way people do: by observing and repeating. This funding allows us to accelerate that vision, expand globally, and bring Physical AI to more manufacturing environments,” said Puru Rastog, co-founder and chief executive officer of Mowito.
Kushal Bhagia, Partner at All In Capital, said manufacturing is entering a new phase where AI will fundamentally reshape industrial automation.
“Mowito is building foundational technology that removes one of the biggest barriers to industrial automation — the complexity of robot programming. The team’s technical depth, early customer validation, and vision for Physical AI make them exceptionally well positioned to define this category,” he said.
