
AI-powered verification of motion and intrusion events filters out nuisance alerts caused by weather, lighting changes, insects, and environmental noise. Works with existing AI cameras, NVRs, and third-party video systems — improving alert reliability without replacing infrastructure.

Identifies suspicious or abnormal movement patterns beyond traditional motion triggers, enabling earlier and more accurate detection of potential security threats.

Significantly reduces unnecessary alerts, allowing operators to focus on real incidents, accelerate response time, and manage more cameras with the same team.

Natural-language and metadata-based video search enables operators to instantly locate relevant footage, dramatically shortening investigation time.


Reduce Nuisance Alarms with VLM-Validated Event Detection
AI-powered, context-aware alarm filtering distinguishes real security threats from environmental noise with confidence-scored events:
• Real intrusions: people or vehicles
• Environmental noise: rain, shadows, headlights, insectsCuts false alarms in intrusion and perimeter breach detection by 70–95% compared with motion-only detection.

Enable Fine-Grained Situational Awareness for Parking & Perimeter Security
AI-powered behavior and object recognition provides deeper context beyond simple motion detection:
• Person: aggressive behavior (fighting, smashing), running, crowding, robbery, or shooting
• Vehicle: break-ins, vandalism, illegal parking, abnormal speeding
• Object: unattended items, suspicious packages, weapons
• Environment: fire, smoke, and other safety hazards

Natural-Language Video Intelligence with VLM
VLM maps video and text into a unified embedding space:
• Video frames → visual embeddings
• Text queries → language embeddings
Search video using simple questions:
• “Find people loitering near the trailer after midnight”
• “Show red trucks stopped for over 2 minutes”