Mowito Lands US$3M Pre-Seed to Bring Physical AI to Manufacturing

 

Mowito Co-Founders (L-R): Safar V, Adityanag Nagesh, and Puru Rastogi

Indian Physical AI startup Mowito has secured US$3 million in pre-seed funding, led by Version One Ventures, with participation from All In Capital, Unisol, iSeed, and angel investors including Soumith Chintala, Adarsh Kulkarni, Ashish Kulkarni, and Vaibhav Domkundwar of Better Capital.

The latest investment follows the company's earlier US$540,000 angel funding round, bringing its total disclosed funding to US$3.54 million since its founding in 2024.

Why Did Mowito Raise New Funding?

According to the company, the new capital will be used to:

• Expand operations into the United States
• Grow its engineering team
• Strengthen go-to-market capabilities
• Scale deployments across automotive and electronics manufacturers

The funding comes as manufacturers increasingly adopt AI-driven automation to improve productivity while addressing labor shortages and production complexity. According to the International Federation of Robotics (IFR), global industrial robot installations reached approximately 541,000 units in 2023, highlighting sustained demand for factory automation despite broader macroeconomic headwinds.

What Does Mowito Build?

Founded in 2024 by Puru Rastogi, Adityanag Nagesh, and Safar V, Bengaluru-based Mowito develops Physical AI foundation models for industrial robot arms.

Rather than relying on manually written robotic code, Mowito enables industrial robots to learn manufacturing tasks directly from human demonstrations. This approach allows manufacturers to deploy automation more quickly while continuing to use existing robotic hardware, reducing implementation costs and deployment time.

Physical AI has become one of the fastest-growing segments of artificial intelligence, extending foundation models beyond software into autonomous machines capable of interacting with physical environments.

How Does Mowito's Technology Improve Industrial Automation?

Traditional industrial robots require extensive programming that can take several days for each production task. Any change in a product design, manufacturing process, or component often requires engineers to rewrite large portions of robotic code.

Mowito's Physical AI models replace much of this manual programming by allowing robots to observe demonstrations and autonomously learn manufacturing workflows while maintaining the precision required for industrial production.

Traditional Industrial Robotics	Mowito's Physical AI Approach
Manual programming required	Learns from demonstrations
Configuration may take days	Faster deployment
Code rewritten after process changes	Adapts to changing tasks
Higher engineering effort	Reduced programming complexity
Limited operational flexibility	Improved manufacturing agility

Where Is Mowito's AI Already Being Used?

The company says its technology has already moved beyond pilot testing into commercial production environments.

According to Mowito, its software currently powers robotic systems on manufacturing lines operated by a Fortune 500 automotive company, supporting high-precision assembly applications across both the automotive and consumer electronics industries.

Commercial deployments at enterprise manufacturers provide an early validation point for the startup's Physical AI platform as manufacturers seek more flexible automation systems.

Who Are Mowito's Competitors?

Mowito operates within the rapidly evolving industrial automation and machine vision market alongside established global companies, including:

• Cognex
• Keyence
• Omron
• Fanuc

Unlike traditional automation providers that focus primarily on sensors, machine vision, or programmable industrial robots, Mowito positions itself around AI-native robotic learning, where robots acquire manufacturing skills from demonstrations instead of rule-based programming.

The broader Physical AI market is attracting growing venture capital interest globally as advances in foundation models create new opportunities across robotics, manufacturing, logistics, and autonomous systems.

Although Mowito currently operates from India, its expansion into the US places it within a global innovation ecosystem alongside AI and robotics hubs such as Hub71 in Abu Dhabi, ADGM's technology ecosystem, and advanced manufacturing initiatives supporting intelligent automation worldwide. Similar demand is also emerging from large-scale industrial projects such as NEOM, where AI-powered automation is expected to play an increasingly important role in future manufacturing infrastructure.

 

 

FAQ

1. What is Mowito?
Mowito is a Bengaluru-based startup founded in 2024 that develops Physical AI foundation models for industrial robot arms. Its software enables robots to learn manufacturing tasks from demonstrations rather than traditional programming.

2. How much funding has Mowito raised?
Mowito has raised a total of US$3.54 million, including a US$3 million pre-seed round led by Version One Ventures and an earlier US$540,000 angel round.

3. How does Physical AI differ from traditional robot programming?
Traditional industrial robots require explicit programming for each task and often need code changes whenever products or processes change. Physical AI allows robots to learn tasks directly from demonstrations, reducing setup and reprogramming time.

4. What industries is Mowito targeting?
Mowito is primarily targeting automotive and consumer electronics manufacturers, where high-precision assembly and frequent production-line changes create strong demand for adaptive robotic automation.

5. Who are Mowito's main competitors?
Mowito competes with established industrial automation and machine vision companies including Cognex, Keyence, Omron, and Fanuc, while differentiating itself through AI-driven robot learning capabilities.