The internet was humanity's first dataset. The physical world is its last — and its biggest. We're taking it. Atom by atom. And handing machines a world they can finally understand.
Language models ate the internet. There's nothing left to scrape.
The next frontier has no URL — it's hands, tools, motion, friction, consequence: the way the physical world actually behaves. That data isn't missing. It was never recorded.
So we record it — at a fidelity nobody else reaches, at a scale nobody else dares.
This is CyberCode — the app you talk to. Search reality like a database, compose a training set in plain language, watch it verify to the frame. The window below is the real thing, running.
Wearable, first-person rigs and on-device software — engineered in-house, run at fleet scale. The layer everyone else outsources, we own outright.
A platform that decides what to capture, drives collection task by task, and tracks every one to delivery. Raw human effort, forged into an industrial line.
An engine that smelts raw recordings into structured, queryable data — sampling, multi-model inference, indexing, storage, full provenance.
Automated QC and human-in-the-loop review. Nothing ships until it's been challenged frame by frame.
A 3D perception stack that rips people, hands, objects, and scenes out of raw footage — the structure of action itself.
A structured map of every real-world scenario worth capturing. We know exactly what reality is still missing — and we hunt it.
Developer and researcher tooling, plus open frameworks — so others can build on what we mine.
Everyone else buys their capture hardware off a shelf. We engineer ours. Spin the rig. Spin the glove. This is the silicon end of the chain — the layer that decides whether the ground truth is real.
Synthetic data is a rumor about the world. We deal in the world.
A dataset you can't trust is a liability. Ours is verified to the frame.
It's where we start.
From the silicon on a head rig to the tensor a model trains on — one team, one unbroken chain, zero black boxes.
Built for the labs and world-model teams training embodied AI. High signal-to-noise. Clean. Verified to the frame. You don't take our word for it — you drive it, see it, then build on it.
Search by occupation, scene, and process. Compose a training set in plain language and watch it assemble — no tickets, no waiting on a data team. The app responds at the speed of thought.
Every clip carries its birth certificate — full provenance, verified to the frame. A scenario graph tracks exactly what reality is still missing, so coverage grows on purpose, not by accident.
Quality gates, frame-level provenance, and certificates a world model can be held to. When the data is wrong you'll know which frame — not just that the loss won't drop.
▸ Whitepaper — Why data scale isn't the moat · the verification, provenance & taxonomy behind the data.
Download the app, query the data live, and pull real samples. When it earns a place in your pipeline — request full access.
We are building the best real-world dataset on Earth — and the day we finish, we'll make it obsolete ourselves. We are not here to compete. We are here to set the origin.