Vision

The insight

Training data for people is training data for robots.

Vision-Language-Action models — the next frontier of physical AI — learn from exactly what an XR training session captures: first-person video, natural-language instructions, fine-grained motor actions and outcome signals.

Operator with VR controllers working alongside a robotic arm

Egocentric video from the trainee's virtual camera, frame by frame, in Unreal Engine scenarios.

Language

Task instructions embedded in every scenario: "identify the slip hazard and reach emergency exit B".

Action

Head and hand poses, controller inputs, world state — with a correct/incorrect label on every behavior, from the platform's scoring system.

The direction

From training platform to data engine for embodied AI.

Today

XR training

Companies train their people with SafetyScapes and FireScapes. Every session is captured at the data level — behaviors, decisions, outcomes — not just scored.

Structured trajectories, annotated in natural language, in standard formats compatible with the major open-source Vision-Language-Action models.

Beyond

Safe robots

Humanoid platforms and industrial robots that learn safety-domain behavior from human demonstrations — collected where safety is already being taught.

Why it matters

The hardest annotation problem is already solved.

Knowing whether a behavior is correct is the most difficult labeling challenge in robotics. Our platform's scoring system resolves it natively, for the safety domain, in every single session. This is what makes behavioral data from XR safety training so distinctive.

For Humans.
For Robots.