Bridging the Physical-Digital Divide: Bengaluru’s Mowito Secures $3 Million to Revolutionize Industrial Robotics with Physical AI

In a landmark development for India’s burgeoning deeptech ecosystem, Bengaluru-based robotics startup Mowito has successfully closed a $3 million (approximately ₹28.6 Cr) pre-seed funding round. The investment signals a growing institutional appetite for "Physical AI"—the next frontier in industrial automation that seeks to bridge the gap between abstract machine learning models and the tangible, high-stakes environment of the factory floor.

The funding round was led by Version One Ventures, with significant participation from prominent venture capital firms including All In Capital, Unisol, and iSeed. The round also saw a notable roster of angel investors, including Thinking Machines Lab CTO Soumith Chintala, Foundry Robotics founder and CEO Adarsh Kulkarni, Coformer.ai co-founder and CEO Ashish Kulkarni, and Better Capital founder and CEO Vaibhav Domkundwar.

Main Facts: Empowering the Industrial Workforce

Mowito, established in 2024 by co-founders Puru Rastogi and Adityanag Nagesh, is tackling a long-standing bottleneck in the manufacturing sector: the rigidity of industrial robot arms. Traditionally, deploying a robotic arm for a specific task required intensive, specialized coding—a process that is time-consuming, expensive, and difficult to pivot when production needs change.

Mowito’s proprietary Physical AI platform changes this paradigm. By developing AI models that allow standard industrial robots to "learn" by observing and repeating human operator movements, the startup is essentially democratizing robotic programming. Instead of writing lines of code, factory workers can demonstrate a task, and the Mowito-powered system translates that observation into an executable workflow.

Key Objectives for the Capital Injection:

• US Market Expansion: The startup is aggressively targeting the North American manufacturing belt, moving beyond its initial footprint to capture a larger share of the US automotive and electronics market.
• Talent Acquisition: A significant portion of the funds is earmarked for strengthening the engineering and go-to-market teams, specifically hiring experts in robotics, computer vision, and machine learning.
• Operational Scaling: The company aims to move from pilot projects to full-scale, multi-site deployments across global manufacturing leaders.
• R&D Acceleration: Continued investment in its Physical AI core to improve the robustness, safety, and adaptability of the robots in unstructured environments.

Chronology of a Rising Deeptech Star

The journey of Mowito is one of rapid iteration and high-level execution.

• Q1 2024: Mowito is incorporated in Bengaluru by Puru Rastogi and Adityanag Nagesh. The founders identify the lack of human-centric machine learning in industrial settings as a critical inefficiency.
• Mid-2024: The startup completes its initial proof-of-concept, successfully demonstrating that standard industrial robot arms can perform complex tasks without traditional hard-coding.
• Late 2024: Mowito secures its first enterprise clients, deploying its technology in the facilities of a Fortune 500 automotive manufacturer and one of the world’s largest electronics contract manufacturers.
• Early 2025: The company formalizes its presence in Detroit, establishing a dual-hub operation between India and the United States to align with the global automotive supply chain.
• Current Milestone: The $3 million pre-seed round marks the transition from stealth-mode innovation to commercial scaling, validating the founders’ vision in the eyes of top-tier investors.

Supporting Data and Industry Context

The rise of Mowito is not an isolated phenomenon; it represents a broader shift in how global manufacturing is integrating artificial intelligence. As supply chains move toward "China Plus One" strategies and localized production, the demand for flexible, autonomous manufacturing solutions in India and the US has spiked.

According to recent industry analysis, the global industrial robotics market is projected to grow exponentially as companies seek to mitigate labor shortages and improve precision. Startups like Mowito are riding this wave by offering a software layer that makes existing, "dumb" hardware suddenly capable of high-level cognitive tasks.

The sector has seen significant movement recently. For instance, in June, deeptech manufacturing firm Ethereal Machines raised $28.5 million in a Series B round to expand its precision manufacturing capacity into the US and Europe. This indicates that Indian deeptech is no longer just a service provider for foreign firms; it is becoming a hub for hardware and robotics innovation that can export solutions globally.

Furthermore, the Indian government’s proactive stance on "Make in India" for high-tech components is creating a favorable tailwind. During the CII Annual Business Summit 2026, IT Minister Ashwini Vaishnaw highlighted that global giants like Google are "seriously considering" manufacturing AI servers in India. With global players like HP already producing in the country, the ecosystem is rapidly maturing, providing the infrastructure and talent pool that startups like Mowito rely on.

Official Responses and Strategic Vision

The sentiment surrounding the funding reflects a shared belief in the "observe and repeat" learning model.

"We believe robots should learn the same way people do: by observing and repeating," said Puru Rastogi, co-founder and CEO of Mowito. "This funding allows us to accelerate that vision, expand globally, and bring Physical AI to more manufacturing environments. Our goal is to make industrial automation as intuitive as learning a new hobby."

Investors have echoed this optimism. The participation of veterans like Soumith Chintala—a key figure in the development of PyTorch—underscores the technical credibility of Mowito’s approach. By bringing together experts in machine learning and seasoned robotics entrepreneurs, Mowito is building a moat around its technology that goes beyond mere software integration.

Implications: The Future of the Factory Floor

The implications of Mowito’s success are twofold:

1. Democratization of Automation

For years, advanced robotics were the exclusive domain of companies with the budget for dedicated automation engineers. By stripping away the requirement for complex coding, Mowito lowers the barrier to entry for Small and Medium Enterprises (SMEs). This could lead to a massive productivity boost in sectors that have historically been resistant to full-scale automation due to the high cost of maintenance and programming.

2. The Shift to "Physical AI"

While the current AI boom is largely dominated by Large Language Models (LLMs) and generative text, Physical AI is the next frontier. The ability for a machine to interact with the physical world, navigate obstacles, and learn from human intuition is the final piece of the puzzle for a fully autonomous factory. Mowito is positioning itself at the center of this movement, effectively turning the robot arm from a static tool into an adaptive, intelligent employee.

3. Strengthening the India-US Manufacturing Corridor

With operations spanning Bengaluru and Detroit, Mowito serves as a bridge between the world’s most significant software talent pool and the heart of global automotive manufacturing. This cross-pollination of expertise is likely to result in more efficient manufacturing standards and a stronger, more resilient supply chain.

Conclusion

As the industrial sector faces unprecedented pressures to increase speed, precision, and flexibility, Mowito’s $3 million infusion serves as a vote of confidence in the future of human-robot collaboration. By focusing on the "learning" aspect of robotics, the startup is not just selling software—it is selling a new way of working.

As they scale their deployments and refine their models, the eyes of the manufacturing world will be on Mowito. If they can successfully replicate their success in Fortune 500 plants across broader industries, they may well define the next decade of industrial evolution, proving that the future of manufacturing is not just about machines, but about machines that can learn from the best of us: humans.