Detect concealment gestures and theft behavior in real time — before the offender leaves the store. No facial recognition, GDPR-compliant.
Retail shrinkage costs European retailers €49B annually, yet EAS gates and human CCTV monitoring catch less than 5% of theft incidents. Professional shoplifters know how to defeat tag-based systems, and guards cannot watch every camera.
The behavioral engine tracks body trajectory, speed, and dwell time near high-value displays — flagging patterns that precede theft.
Computer vision analyzes hand-to-item interaction vectors: picking up merchandise, concealment gestures toward bags, pockets, or clothing.
Within 200ms, security receives an alert with a video clip and location — enabling intervention before the offender exits.
No. Argos analyzes behavior — gestures, movement patterns, and hand-item interactions — never identity. This makes it GDPR-compliant by design and effective against first-time offenders that watchlist-based systems miss.
The engine distinguishes normal shopping behavior (browsing, comparing items) from theft indicators (concealment gestures, tag manipulation). Context-aware classification keeps false positive rates far below motion-based or EAS systems.
Security staff receive an instant alert with a short video clip, camera location, and severity level. Teams can intervene discreetly before the person leaves — turning detection into prevention rather than after-the-fact evidence.
Request a demo and test detection on your existing infrastructure.