BEHAVIOURAL VIDEO ANALYTICS
Your cameras already see everything. Now they'll tell you what matters
Our Behavioural Video Analytics solution turns passive CCTV networks into proactive, intelligent surveillance systems by uniting two complementary AI capabilities: self-learning anomaly detection and high-precision object and attribute recognition. Rather than relying on manually configured rules or round-the-clock human monitoring, the system learns what “normal” looks like for each camera and automatically surfaces unusual or unsafe behaviour in real time, while also enabling rapid forensic search by attributes such as clothing colour, gender, approximate age, or vehicle characteristics.
Designed to integrate seamlessly with existing VMS platforms and camera infrastructure, the solution can cut video requiring manual review by up to 99% and dramatically reduce false alarms, freeing operators to focus on the events that truly matter. From loitering and perimeter breaches to aggressive behaviour, falls, and suspicious activity, it catches both anticipated threats and the unexpected without ongoing rule configuration or manual tuning.
Key Features
Self-Learning Anomaly Detection
No Rules, Zones, or Thresholds to Configure
The system learns each camera’s unique environment within 24 hours and builds a full behavioural baseline over its first week in operation.
Detects the Unexpected
Surfaces incidents that were never pre-defined, such as unusual gatherings, activity in restricted areas at odd hours, or abnormal speed and direction of movement.
Self-Adapting Baselines
Automatically updates as lighting, layout, or foot-traffic patterns change, removing the need for manual reconfiguration.
Dramatic Reduction in Review Workload
Cuts video requiring manual attention by up to 99%, letting a single operator effectively oversee thousands of cameras.
Core Behavioural Triggers
Covers loitering, trip and fall, unusual crowd count, unusual direction, unusual location, unusual speed, unusual time of day, and occupancy limits.
Optional Hazard & Aggression Modules
Detects floor hazards, aggressive behaviour, and medical emergencies through dedicated, privacy-conscious AI engines.
High-Precision Object & Attribute Recognition
Real-Time Weapon Detection
Accurately identifies firearms even in dynamic, high-traffic environments, with strong false-alarm filtering.
Intrusion Detection
Identifies people or vehicles in designated zones at specified times, filtering out the vast majority of false alarms caused by shadows, wildlife, or weather.
Retail Loss Prevention
Flags potential shoplifting behaviour, such as concealing items, with high detection accuracy to enable proactive intervention.
Unified Deployment & Integration
Works with Existing Cameras and VMS
Layers onto current infrastructure without requiring hardware replacement.
Fast Time-to-Value
Self-learning analytics begin generating meaningful events within 24 hours, with no manual zone drawing or threshold setting.
Enterprise-Grade Scalability
Built to process massive video volumes across large, distributed camera networks for government and enterprise deployments.
Flexible Hosting
Available as cloud-based SaaS or fully on-premise for organisations with strict data sovereignty needs.
Actionable Real-Time Alerts
Delivers events to dashboards and mobile apps with screenshots, timestamps, and location context for immediate response.
Connects devices and systems from any manufacturer on one open platform, protecting existing investments and giving you the freedom to choose best-of-breed technology for every application with no vendor lock-in.
Cross-references data from multiple sources to catch complex events that individual systems would miss on their own, for example, linking a failed access card swipe, a motion sensor alert, and an unrecognised vehicle into a single confirmed security breach.
Walks every operator through a predefined, step-by-step response procedure when an incident occurs, ensuring consistent, auditable, and rapid handling regardless of who is on shift.
Triggers preconfigured responses the instant an event occurs, unlocking emergency exits, activating lighting, and notifying first responders the moment a fire alarm is raised, without waiting on a human decision.
Displays all security assets and active incidents on a live, interactive map. Operators click a camera icon to pull up live video or a door icon to lock or unlock it remotely, with full geospatial context for every event.
Logs every event, action, and operator response automatically, creating a complete audit trail for post-incident analysis, compliance reporting, and performance review.
Lets security managers monitor systems, receive alerts, and respond to incidents from a smartphone or tablet, keeping control in hand from anywhere, not just the control room.
Analyses historical event data to identify patterns and forecast emerging risks, helping teams move from reactive monitoring to proactive threat prevention.
Centralises visibility into available security personnel, vehicles, and equipment, so operators can dispatch the right response assets to the right location, every time.
Applies live changes to rules, thresholds, and device configurations across all connected subsystems without interrupting operations or requiring changes to each system individually.
Continuously checks the status of every connected device, flagging a faulty camera, offline sensor, or failed component before it creates a coverage gap, not just after a security event occurs.
Runs on redundant servers, gateways, and databases with automatic failover, so a subsystem failure never interrupts control room operations or compromises business continuity.