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Physical AI startup Mowito raises $3 million to teach factory robots by demonstration, not code
Founded in 2024 by Rastogi, Adityanag Nagesh, and Safar V, Mowito builds software designed to run on standard, unmodified industrial robotic arms. It currently operates across Bengaluru and Detroit, supporting customers in automotive and electronics manufacturing. The new capital will fund Mowito's expansion in the United States, growth of its engineering and go-to-market teams, and continued deployment across automotive and electronics manufacturing clients. Mowito, a startup building AI foundation models for industrial robotic arms, announced on Tuesday that it has closed a $3 million pre-seed round. Version One Ventures led the raise, with All In Capital, Unisol, and iSeed joining as institutional backers. Angel investors such as AI researcher Soumith Chintala, along with founders from Foundry Robotics, Coformer.ai, and Better Capital also participated. Mowito is taking on a problem that has persisted in manufacturing automation: even as robotic hardware has become cheaper and more capable, programming that hardware remains slow and hairy. A single change to a product line can force engineers to spend days rewriting control code. Mowito flips that model, letting robots learn tasks by watching a human demonstrate them rather than being explicitly coded. "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," said cofounder and CEO Puru Rastogi. The startup will use the new funds to expand internationally and deepen deployments across manufacturing sites, he added. Founded in 2024 by Rastogi, Adityanag Nagesh, and Safar V, Mowito builds software designed to run on standard, unmodified industrial robotic arms. It currently operates across Bengaluru and Detroit, supporting customers in automotive and electronics manufacturing. The new capital will fund Mowito's expansion in the United States, growth of its engineering and go-to-market teams, and continued deployment across automotive and electronics manufacturing clients. Physical AI systems are trained to perceive and act in the physical world, rather than just process text, images, or data. Where large language models (LLMs) learn from text and generate text back, physical AI models learn from sensor data, video, and physical demonstrations, and output real-world actions. The space has seen rising interest from investors and chipmakers alike. Manufacturing, which has structured environments and high-value repetitive tasks, is seen as one of the first places it will be tested.
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Mowito Raises $3 Million to Build Smarter AI Robots for Manufacturing
Mowito, a startup building foundation models for industrial robot arms, has raised $3 million in a pre-seed round led by Version One Ventures. The round also drew participation from All In Capital, Unisol, iSeed, and a notable lineup of angel investors, including Soumith Chintala of Thinking Machines Lab, Adarsh Kulkarni of Foundry Robotics, Ashish Kulkarni of Coformer.ai, and Vaibhav Domkundwar of Better Capital. stated that the capital will be used to accelerate its expansion into the US market, grow its engineering and go-to-market teams, and scale deployments further across automotive and electronics manufacturers globally. Co-founder and CEO Puru Rastogi framed the funding as a bet on solving a shift he sees already underway in manufacturing, arguing that hardware is no longer the constraint holding factories back and that robots should be able to learn the way people do, by watching and repeating. "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.
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Mowito, a Physical AI startup building foundation models for industrial robotic arms, has closed a $3 million pre-seed round led by Version One Ventures. The company is replacing traditional robot programming with demonstration-based learning, allowing factory robots to learn tasks by observing humans rather than requiring extensive coding for every production change.
Mowito has announced the closure of a $3 million pre-seed round to accelerate its mission of transforming how industrial robot arms learn and operate in factory environments
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. Version One Ventures led the funding round, with participation from All In Capital, Unisol, and iSeed, alongside prominent angel investors including AI researcher Soumith Chintala and founders from Foundry Robotics, Coformer.ai, and Better Capital2
. Founded in 2024 by Puru Rastogi, Adityanag Nagesh, and Safar V, the startup currently operates across Bengaluru and Detroit, supporting customers in automotive manufacturing and electronics manufacturing1
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Source: Analytics Insight
The startup addresses a critical challenge that has plagued manufacturing automation for years: while robotic hardware has become increasingly affordable and capable, programming that hardware remains time-consuming and complex. A single change to a product line can force engineers to spend days rewriting control code, creating significant operational friction
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. Mowito builds AI foundation models for industrial robotic arms that fundamentally change this paradigm, enabling robots to learn tasks by observing human demonstrations rather than requiring explicit programming for each task.Mowito's approach centers on teaching factory robots by demonstration, allowing industrial robot arms to acquire new skills through observation and repetition. "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," said Puru Rastogi, co-founder and CEO
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. Physical AI systems are trained to perceive and act in the physical world, learning from sensor data, video, and physical demonstrations to output real-world actions—a stark contrast to large language models that process text and images1
. The software is designed to run on standard, unmodified industrial robotic arms, eliminating the need for specialized hardware investments.Related Stories
The new capital will fund Mowito's expansion in the United States, growth of its engineering and go-to-market teams, and continued deployment across automotive and electronics manufacturing clients
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. This funding allows the company to scale deployments further across manufacturing environments globally, bringing smarter AI robots for manufacturing to a broader customer base2
. The space has attracted rising interest from investors and chipmakers alike, with manufacturing environments—characterized by structured settings and high-value repetitive tasks—viewed as one of the first proving grounds for AI-driven robotic automation1
. For manufacturers watching production flexibility become increasingly critical, Mowito's demonstration-based learning approach could signal a shift toward more adaptable factory floors where robots learn tasks by observing rather than waiting for engineers to rewrite code with each product iteration.Summarized by
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