Sentinel Vision — AI Safety Copilot for Factories
Existing CCTV cameras become 140 tireless safety officers that predict accidents before they happen.
Sentinel Vision runs computer-vision models on edge devices connected to a plant's existing CCTV. It detects missing PPE, people in forklift paths, blocked fire exits and unsafe postures in real time — and, uniquely, learns near-miss patterns to predict where the next incident is most likely.
The challenge
Safety teams could review only a fraction of camera footage, incidents were reported after the fact, and near-misses — the best early warning signal — went almost entirely unrecorded.
Our solution
We deployed edge AI boxes that process video locally (no footage leaves the plant), a privacy layer that blurs faces by default, and a central dashboard that turns detections into heatmaps, risk scores per zone and automatic WhatsApp alerts to shift supervisors.
Key capabilities
01Real-time Detection
- Helmet, vest, glove & goggle compliance
- Person–forklift proximity & speed zones
- Blocked exits, spills and smoke
- Ergonomic posture risk scoring
02Predictive Safety
- Near-miss clustering & trend detection
- Zone risk forecast for each shift
- Root-cause suggestions using a safety LLM
- Weekly auto-generated safety briefings
03Privacy & Operations
- On-prem edge processing
- Face blurring by default
- WhatsApp / siren / PA integrations
- Works with existing IP cameras
Screens & experiences
Technology stack
Want results like Sentinel Vision?
Tell us about your idea — we'll reply with a plan and estimate within one business day.