Real-time detection at scale

Detect intrusions, loitering, restricted-zone movement, and anomalies across large camera fleets using production-grade video analytics.

Recognition with governed controls

Enable identity and object recognition workflows where permitted—anchored to measurable performance benchmarks and strong audit controls.

Evidence-first alerts

Generate alerts with visual context, timestamps, and traceable event history so operators can act quickly without guesswork.

Workflow-ready outputs

Convert detections into workflows—escalations, validations, dispatch, and reporting—so incidents move forward, not sideways.

Human-in-the-loop validation

Review detections with confidence signals and supporting evidence to prevent alert fatigue and maintain operational credibility.

Continuous performance monitoring

Track detection quality over time and across sites to identify drift, camera issues, and rule misconfiguration before they become operational gaps.

GenAI incident summarisation

Generate concise incident summaries and reports from event timelines to support shift handovers, reviews, and investigations.

Start with existing infrastructure

Adopt Vision AI on top of current CCTV and monitoring environments to reduce deployment friction and time-to-value.

Edge and central deployment options

Deploy analytics close to cameras where needed, while maintaining central command visibility and governance.

Reusable rules and response workflows

Standardise detection rules, escalation paths, and reporting templates across sites to maintain consistency at scale.

Perimeter intrusion and loitering detection (critical sites)

Proactive perimeter security and intrusion detection remains a primary adoption driver for intelligent video analytics.

Workplace safety and PPE compliance (industrial, construction, infrastructure)

Regulatory pressure and safety governance are increasing, and computer vision PPE monitoring is becoming a practical control layer for EHS teams.

Fire, smoke, and wildfire early detection (warehouses, utilities, remote assets)

Video-based fire and smoke detection has become a major growth area due to the need for early warning across large or remote zones.

Retail loss prevention and organised retail crime deterrence

Retailers are reporting rising shrink and increasing focus on loss prevention and security technology, accelerating demand for intelligent video analytics.

Traffic, parking, and crowd intelligence (campuses, cities, events, large facilities)

Smart-city and large-campus operations are expanding the use of AI video analytics for traffic flow, violations, and crowd management.

Vehicle recognition and controlled access (ports, logistics, secure campuses)

ANPR is widely used to automate vehicle identification for access control and operational enforcement at scale.