We pre-train our model on RGB video from everyday sources - phones, drones, dashcams, etc. - without requiring manual labels or bespoke data.

Unlike others who rely on proprietary datasets as a moat, we embrace ubiquity. Our models learn purely from visual observation, allowing them to adapt across styles and domains.

For example, by watching Star Wars, our system can learn the visual grammar of sci-fi environments -materials, lighting, motion dynamics - without needing labels.

The same model can then observe real-world footage from an autonomous vehicle or a handheld phone and immediately generalise to interact with the world -powering robots that can see, reason, and act across realities, simply by watching.

This is the path to universal integration: no manual tuning, no retraining - just observation.