Do you know MIMI ROBOTICS, the spin-off from ETH Zurich which wants to develop the most advanced robotic hand in the world?

Coming from ETH Zurich, one of the world’s leading universities in engineering and robotics, Mimic Robotics tackles one of the last bastions of industrial automation, that of complex manual tasks that require real human dexterity. The Swiss startup starts from the observation that traditional robots excel at repetitive gestures, but fail when it is necessary to grasp, adjust, reposition or adapt to unpredictable variations.

To respond to this structural limit, Mimic Robotics is developing a humanoid hand with 21 joints, mounted on standard industrial arms, controlled by a Physical AI model trained on human demonstrations collected in real conditions. The approach combines advanced hardware, a proprietary foundation model and a unique gesture capture method, allowing the machine to reproduce human skills with submillimeter precision and real-time error correction.

The target market is manufacturing, assembly, automotive, logistics. All these industries still concentrate millions of tasks that are impossible to automate due to a lack of sufficiently flexible robots. With a projection of $38 billion for humanoid and dexter robotics by 2035, Mimic is positioned in one of the most strategic segments of the new generation of industrial automation.

To accelerate this ambition, the company has just raised 13.8 million euros in Seed. The round, led by Elaia and Speedinvest, also brings together 2100 Ventures, Sequoia Scout Fund, 10X Founders, Founderful and 1st Kind, bringing the total funding beyond 17 million euros.

Led by Stefan Weirich (CEO) alongside Stephan-Daniel Gravert (CPO), Elvis Nava (CTO), Benedek Forrai (Founding Engineer) and Robert Katzschmann (Scientific Advisor), Mimic Robotics today brings together a team of 25 specialists in AI, robotic manipulation and industrial systems. The startup is already piloting its technology with large manufacturers, including several Fortune 500, with a view to large-scale commercial deployment by 2027.