Verkada’s AI-Powered Unified Timeline is an investigation tool within Verkada Command that uses artificial intelligence to reconstruct the movement of people and vehicles across multiple cameras. Instead of requiring security teams to manually review footage camera by camera, the system identifies relevant sightings and combines them into a single chronological, map-based timeline.
The technology addresses one of the most time-consuming elements of video investigation: understanding what happened before and after an initial event. Once an operator identifies a person or vehicle of interest, Unified Timeline automatically searches footage from across the organisation’s camera estate, looking six hours before and six hours after the selected event. Relevant sightings are then presented as a continuous 12-hour investigative timeline.
Reconstructing incidents with AI
Unified Timeline combines several of Verkada’s computer-vision capabilities to identify subjects as they move between cameras. For people, operators can use face detection or appearance search, which considers clothing and other visible attributes. Vehicle analytics can similarly locate vehicles across the camera network.
An investigation can follow one person, one vehicle or a combination of the two, helping security teams establish relationships between different subjects and events. Operators can select a detected individual within historical footage and automatically generate a timeline containing the associated sightings and video clips.
Where cameras have been added to a site floorplan, the system also provides spatial context by highlighting the cameras that detected the subject and showing the sequence of movement through a location. If a subject appears on multiple cameras simultaneously, relevant footage can be presented in a multi-camera view.
This enables investigations to move beyond isolated video clips towards a clearer representation of an incident from beginning to end.
Reducing manual video investigation
Unified Timeline is particularly relevant for security teams managing large buildings, campuses, retail estates, warehouses and multi-camera environments, where manually tracking a person between cameras can require considerable operator time.
The platform can also connect people and vehicles within the same investigation. For example, an operator investigating a theft could identify an individual inside a building, follow their movement through surrounding cameras and add an associated vehicle to the same timeline. Where compatible licence plate recognition cameras are deployed, corresponding number plates can also form part of the investigative process.
Once relevant footage has been assembled, sightings can be converted into an incident within Verkada Command, creating an organised evidence package for review or further investigation.
By using AI to locate, correlate and organise video automatically, Unified Timeline changes the role of analytics from simply detecting an event to helping security teams understand the sequence around it. The result is a more practical investigative workflow designed to turn fragmented footage from multiple cameras into a coherent account of an incident.
