The data layer for contextual intelligence

Harbor is building the data layer that turns real human signal into frontier-ready context. Not a labeling marketplace. Not a generic crowd panel. Capture, judgment, provenance, and delivery—so models learn from how work actually happens.

Models have raced ahead on capability. Production systems still fail when they meet the world: messy rooms, noisy audio, rare edge cases, ambiguous human intent. That gap is not closed by more compute alone — it is closed by faithful, multimodal human data collected under the constraints of deployment.

We believe the winning stack is three systems operating as one: a distributed network of contributors who collect where models will run; domain experts who validate against rubrics that matter; and a passport of trust so every delivery carries integrity and provenance into the evaluation pipeline.

Our focus is audio-visual AI — vision, speech, wearables, robotics, and agentic workflows — because those modalities are where synthetic shortcuts break first and where real human presence is non-negotiable.

Harbor exists so frontier teams can acquire high-quality contextual intelligence at the speed of their product roadmap, with the audit trail enterprises require.