Thomson Reuters Vigilant Vehicle Manager
Description
The purpose of the AI use case in Thomson Reuters Vigilant Vehicle Manager is to intelligently organize, correlate, and analyze large volumes of license plate and vehicle sightings data. By automating the identification of recurring patterns and providing data-driven insights, it streamlines the workflow for identifying vehicles that may warrant attention. The AI capabilities reduce time-consuming manual reviews, improve accuracy in spotting significant trends, and help allocate investigative resources more effectively for timely and well-informed actions.
Detailed example
The AI features produce overviews of vehicle activity, highlight recurring patterns, and point to areas for further review.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
License plate reader systems are used by law enforcement to assist with identification of vehicles associated with criminal investigations. ATF has no role in training or managing AI capabilities which are incidental to providing the service.
Controls / human review
ATO: No; PIA: Not published
Data needed
The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.