The platform supports a prevention-first safety approach by helping organizations detect, intervene, analyze, and continuously improve:
Detect: Identify high-risk events and unsafe conditions in real time, including forklift pedestrian interactions and collisions, vehicle collisions, blind spots, zone management, loading docks risks, machine zone exposure, lone worker situations. AI Risk Radar also monitors configurable SIF risks such as improper walkway use, missing PPE, and blocked emergency equipment.
Intervene: Trigger real-time alerts, visual and audible warnings, vehicle slowdown, zone-based controls, and other connected safety actions where configured.
Analyze: Capture near-misses, unsafe interactions, and recurring risk patterns through AI-powered video intelligence, event data, and centralized safety analytics.
Improve: Help EHS and operations teams identify root causes, prioritize corrective actions, benchmark risk exposure, and strengthen preventive controls over time.
This closed-loop approach helps organizations reduce serious injury and fatality (SIF) exposure, improve visibility into leading indicators, and act on risk before it develops into an incident.