Solutions
Four ways teams use the factory
The models differ, the loop does not. Each of these teams generates data, trains on it and validates the result — they just weight the three stages differently, which is exactly what capacity planning has to account for.
The demonstrations are the bottleneck. Not the GPUs.
Teams building general-purpose robot brains — end-to-end vision-language-action models that have to transfer across humanoids, arms and mobile bases.
The scenarios that matter are the ones that never happen.
End-to-end driving stacks and world models trained on fleet video rather than hand-written rules.
Validation is the release gate.
Driverless fleets whose software is re-validated before every release — for regulators as much as for the road.
The line cannot stop for data collection.
Manufacturers, warehouses and ports automating the flexible, high-mix work that fixed automation was never able to handle.
Not on the list?
If your models touch the physical world, the loop is the same
Agriculture, mining, construction, inspection, surgical robotics, defence logistics — the workloads look different on the surface and identical underneath. Tell us what you are training and we will size it.