About

Robotics companies have data. Model labs have models. Neither will give the other access to what they’ve spent years building.

We hold both under custody — in an environment whose architecture, not our promise, enforces the neutrality — so the comparison can finally happen.

Foundation model quality crossed a threshold in the last two years. The fine-tuning gap — the difference between a general-purpose model and one trained on your specific robot, your specific tasks, your specific error distribution — is now the primary bottleneck for deploying capable robotics in production. The models exist to close that gap. The data exists to close it. The missing piece is a way to combine them without either side giving up what they’ve spent years building.

We don’t make a model. We don’t own training data. We don’t have a preferred robotics platform or a sales relationship with any hardware vendor. Our only product is the outcome of the comparison — and the comparison only has value if both sides trust it.

Neutrality isn’t a value we hold. It’s a constraint we built around. The business only works if the enclave is genuinely impartial, which means the incentives are aligned with the architecture. You don’t have to take our word for it — the structure of our revenue model makes it self-defeating to favor either side.