Fast learning physical AI for any robot.
We teach your robot a new industrial task in 24 hours.
Today's physical AI gets to 70% and stops there.
Foundation models have made robots general; they have not made them reliable. On a real production task base policies land at 60 to 70% success. Closing the last 30% today takes months of engineering per task, at two to five times the cost of the robot.
Inait's product, iAM Robotics, closes that gap on the robot already on your factory floor. It learns the specific task on your cell in a day, takes it to production grade, and keeps it running as parts, lighting and tooling drift. When the part changes, a few new demonstrations and it is back at work.
Shop-floor ready physical AI.
One manipulation task at a time, production ready. iAM Robotics takes a task from the first description to running on your cell, in under 24 hours of robot time. No AI team needed on site.
Show
Describe the task and what varies between cycles: where parts lie, how they are oriented. Our software collects the demonstrations on your robot by itself; an operator only supervises. If a simulation is available, part of the task is learned there, with less time on the real cell.
Learn
The platform turns those demonstrations into a policy for your task, trained in the cloud or on your own infrastructure. Fast learning means a few demonstrations are enough, not millions of samples.
Run
Runs on your local hardware and keeps learning on the job, so drift stays under control. When the part changes, a few new demonstrations are enough to adapt.
Already working in real factories.
We take the customer's robot, their cameras, their computers, and add only our software.
Gear pick-and-place for a Microsoft industry customer. Their engineers had plateaued at 65% with the best available methods. Same robot, same task, same room: 100%, fully autonomous, set up in under 24 hours of robot time.
Heavy automotive parts, packed tight with no fixed position, repacked for assembly. The customer's own attempt had plateaued at around 60%, with 2 cm precision that damaged parts. With Inait: 99% in simulation, 98% on the real cell, within the 10 mm tolerance required, on a robot and parts it had never seen in the real world, in under 24 hours of robot time.
Senses everything. Reacts instantly.
Today's robot policies look at the scene, generate a whole chunk of actions, execute them blind, and only then look again. Touch, force and the other sensors mostly go unused.
Our models work differently. They sense everything, vision, position, touch, force, and every new signal can change the very next action. The loop is closed continuously, so the robot reacts the instant the world changes.
A different kind of AI:
fast learning.
Not more data and bigger models, but AI built on how real brains learn. For more than twenty years, at EPFL and through the Blue Brain Project, Henry Markram and his teams digitally reconstructed how real brains are built, validated neuron by neuron against biology.
How these digital brains learn is Inait's crown jewel: like an apprentice, they pick up a task from a few demonstrations and improve with every attempt. iAM Robotics pairs them with a toolkit of proprietary brain-like AI tools for real industrial robots, running on standard hardware.
Who we build with.
Proof beats promises.
Tell us about your task.
One week to tell you if your task qualifies for a free proof of concept in 2026. One more to measure the success rate on your cell.