Enact Intelligence Raises €26.68 Mn in Pre-Seed Funding to Develop Advanced AI Robotics

The funding round included investments from venture capital firms redalpine, Notion Capital and firstminute capital.

Several well-known angel investors also participated, including Arthur Mensch, founder of Mistral; Yann LeCun, founder of AMI Labs and former Chief AI Scientist at Meta; and Andrew Lonsberry, founder of Path Robotics.

Manuel Yves Galliker, CEO and founder of Enact Intelligence, said, “Unlike the early days of LLMs, physical AI has the advantage of starting from strong reasoning, language, and vision capabilities already in place. Instead of trying to collect every piece of data needed to teach a robot common sense about the world, we can build on top of existing models, like video models, and adapt them to output robot actions for interacting with the real world. So what we are addressing is the ability to efficiently learn from experience and perform tasks reliably, both of which require the model to understand the physics of the robot and the task at hand.”

“Dexterity is the next frontier in robotics, and Enact is tackling it with a new data modality: starting with high precision force data from bespoke actuators they are rethinking the entire stack from the hardware up. We are very excited about Enact’s approach of leveraging orthogonal data to improve existing models and build a data moat,” said Dr. Harald Nieder, General Partner of redalpine.

Enact Intelligence was founded in March 2026 by Manuel Yves Galliker. The company is developing robots that can not only see their surroundings but also sense touch and physical contact when interacting with objects.

Before starting Enact, Galliker led the software team for NEO, a humanoid robot developed by 1X. He also helped build 1X's AI team in Silicon Valley and later worked at the robotics research lab Physical Intelligence.

According to Enact, most robots today rely mainly on cameras and vision to understand their surroundings. This makes it harder for them to handle objects reliably and learn from their experiences.

Existing touch and force-sensing technologies can help robots interact with objects more effectively. However, these solutions are often too expensive or fragile for widespread use in industrial environments.

Read Also- Legora Raises $550 Mn Series E at $8.8 Billion Valuation to Expand AI Legal Platform