Transportation & Transit

Real-time situational awareness on existing cameras, infrastructure inspection from fleet vehicles with automatic work orders, incident evidence with custody for claims defense, and records request automation with passenger privacy protected.

No. RTSP/ONVIF and any VMS, including vehicle-mounted cameras, with phased rollouts that start on the corridors that matter most.

Incident footage and reports become one evidence record with chain of custody and integrity certificates, so injury and damage claims are answered with proof instead of settlements.

Yes. Events flow into dispatch, 311, and CRM systems, and infrastructure defects file deduplicated work orders automatically.

AI Live Insight adds real-time detection to a city's existing RTSP or ONVIF cameras, covering people, vehicles, crowds, traffic signals and signs, fire and graffiti, with zone rules for loitering, intrusion and crowd counts. One GPU handles about 32 to more than 100 cameras depending on frame rate and models, and capacity scales out by adding servers. Detections are sent by webhook to 311, CRM or dispatch systems so they can become service requests.

AI Live Insight detects potholes, fallen trees, graffiti and damaged electricity poles in footage from survey vehicles or drones, and GPS telemetry in that footage places each defect on a map. Detections can be sent by webhook to a 311, CRM or work management system to open a maintenance request.

AI Live Insight can be trained to detect curbside violations such as double parking, bike-lane blockage, accessible-bay blockage, loading zone misuse and overstaying on existing cameras. These models are trained per engagement against footage from the city's own cameras, and each detection becomes an alert with time, camera, severity and a video clip that can be sent by webhook to enforcement or CRM systems.