Every frame, read for hazards.
Each frame the drones, 360 cameras and robots bring back is read for OSHA-aligned hazard classes — open leading edges, unsecured ladders, unguarded penetrations, missing high-vis, crane-radius exposure — ranked by severity and confidence, and assigned with the frame attached.
What it does
Safety AI is not a camera product bolted to the side of the platform. It is one head of GR Brain, reading your captures, your incident history, and the hazards your sites actually produce — so a scaffold detail that has hurt someone on your work ranks above a textbook one that never has.
Every frame is scanned; nothing is sampled. Findings arrive ranked by severity and confidence, and only the top of that ranking reaches a phone — the superintendent responsible for that grid line gets three severity-one items with frames attached, not four hundred alerts. Hazards are logged while they are still hazards, not discovered in an incident review. Faces and bodies are blurred before a frame leaves the camera, and a detection is evidence for a conversation with a crew, never a case file on a worker.
In practice
- 01
Scan every frame
Drone flights, 360 walks and robot rounds all land in the same queue. 27 hazard classes, aligned to OSHA subparts, read on every frame the site produced that morning — 14 minutes from capture to finding.
- 02
Rank by severity and confidence
Severity comes from the hazard class; confidence comes from the read itself. Low-confidence detections go to a review queue where a safety coordinator confirms or dismisses them, and it is that judgement — not the first read — that goes on the record.
- 03
Assign with the evidence
A finding is routed to the person who owns that area, carrying the frame, the timestamp and the location on the plan. It closes the way any observation closes: with a new frame showing the hazard gone.
Spec
- CLASSES
- 27 · OSHA-ALIGNED
- RANKING
- SEVERITY × CONFIDENCE
- CAPTURE → FINDING
- 14 MIN
- FACES
- BLURRED · 100% OF FRAMES
94%
Hazard-detection accuracy