CONTEXT360
The missing context for AI.
We are building the infrastructure layer that connects hard-to-access human expertise and real-world work with the models that need to learn from it.
Talk to our teamOUR THESIS
The most valuable training data has not been created yet.
Public data captures knowledge, media, and fragments of behavior at extraordinary scale. It rarely captures the complete context behind expert work: the state, intent, interpretation, action, and outcome.
Context360 exists to build that missing layer—with clear provenance, appropriate rights, disciplined collection design, and structures made for model training and evaluation.
HOW WE WORK
Capability-led. Provenance-first. Built for real use.
Every collection decision should increase the usefulness, defensibility, and intelligibility of the resulting data.
Start with the capability
Define the behavior, decision, or task the model needs to learn before specifying the collection.
Preserve the context
Capture the surrounding state, expert intent, decision logic, action, and outcome—not media alone.
Design provenance in
Treat source, permissions, rights, lineage, transformation, and QA as core parts of the data product.
Earn scale through quality
Validate the protocol with a pilot, then expand only after the technical and semantic standard is clear.