Mowito raises $3 million to teach factory robots by demonstration, transforming manufacturing automation

Mowito Secures $3 Million to Advance Physical AI in Manufacturing

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 1

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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 Capital 2

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. 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 manufacturing 1

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Solving Manufacturing Automation's Persistent Software Bottleneck

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 1

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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.

How Physical AI Enables Robots to Learn by Demonstration

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 2

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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 images 1

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. The software is designed to run on standard, unmodified industrial robotic arms, eliminating the need for specialized hardware investments.

Expansion Plans and Market Implications

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 1

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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 base 2

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. 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 automation 1

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. 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.