Bengaluru-based AI startup Mowito has secured $3 million in pre-seed funding to expand its operations into the United States. The company develops AI models that allow industrial robot arms to learn factory tasks by observation, aiming to replace traditional, time-intensive manual reprogramming.
Mowito, a startup with operations in Bengaluru and Detroit, has raised $3 million in a pre-seed funding round to advance its physical artificial intelligence technology. The round was led by Version One Ventures, with additional backing from All In Capital, Unisol, iSeed, and several individual investors. This capital injection is primarily aimed at supporting the company’s expansion into the United States market and growing its engineering and sales teams.
The core of Mowito’s business is its AI software designed for industrial robot arms. In many manufacturing environments, robots must be manually reprogrammed every time a product line or component is changed. This process is often costly and time-consuming. Mowito’s technology aims to address this by enabling robots to learn new tasks by observing human demonstrations. The company believes this approach allows for greater flexibility on the factory floor, potentially helping manufacturers adapt more quickly to changing production needs.
Mowito is targeting sectors such as electronics and automotive manufacturing for its deployments. By focusing on software that mimics human learning—observing and repeating—the company seeks to solve a common bottleneck in industrial automation where software capabilities have not kept pace with hardware advancements. The firm is led by co-founders Puru Rastogi, Adityanag Nagesh, and Safar V.
For investors monitoring the industrial technology space, the primary monitorables include the company's ability to scale its deployments within the competitive US manufacturing sector and its success in proving the reliability of its observation-based learning models in high-precision environments. The transition from demonstration to large-scale industrial use often involves significant testing and integration challenges, which will be critical factors to track as the company grows its US footprint.