About Human Ground — Europe's human ground for embodied AI
Why Human Ground exists: Europe's skilled physical work is retiring faster than it can be replaced, and robots have to succeed in real work, not just in demos. Human Ground is where people and embodied AI learn to work together.
Europe's strength was never just its factories. It was the skill of the people in them. That skill is retiring faster than it can be replaced — warehouses, factories, building sites and care settings cannot fill the work in front of them, and the gap grows every year.
Every useful machine learned from people first. Language models learned from everything we ever wrote down. Machines that act in the physical world have to learn from something much harder to write down: how work is actually done.
The field is debating how they should learn — from human demonstrations, from reinforcement, from simulation, from models of the world. It is the right debate, and it is missing its ending. Whatever the method, every robot arrives at the same place: a real workplace on an ordinary day. The pallet is in the wrong spot. The light is poor. A colleague needs a hand. The task is almost the one it trained for, and not quite. That is where demos end, and where real deployments succeed or stall.
In machine learning, grounding is what connects a model to the world it acts in. For embodied AI, that world is human work — the skill, the judgment, the edge cases, and the standard of "done well" that only the people who do the work can define.
We call it the human ground: the place where people and embodied AI learn to work together. Human Ground is built to be that place — between the European businesses where physical work is done and the teams building the models and machines that will work alongside them. We capture real work for those teams to learn from. We measure models and robots against it. We open real operations for robots to be tested in and, when they are ready, to go to work in.
For the businesses that take part, it means a clear, independent view of where robots can support their people, robots that prove themselves before any investment, and a share in the value their work creates.
What we will not do. Captured data is never used to evaluate or discipline the people in it. Everyone captured chooses to take part and can say no without their employer knowing. The businesses that open their doors stay anonymous unless they choose otherwise. Our work is not for weapons or surveillance.
We don't build robots or models. We work with everyone who does.
We are early, and we are building this step by step. If you build embodied AI, or run the kind of work it needs to learn from, we would like to talk.
Grounding embodied AI in real human work.
Human Ground