Targa Telematics has launched an AI-powered fleet maintenance platform designed to help operators manage vehicle maintenance by bringing together data from multiple sources into a single system.
The new platform, Maintenance Excellence, uses what the company describes as “Agentic AI” to combine data from telematics devices, vehicle manufacturers’ systems and external platforms to monitor vehicle health, identify potential maintenance issues and coordinate maintenance activities.
According to Targa Telematics, the system can detect early signs of vehicle wear or faults, schedule maintenance appointments and automate administrative tasks such as stakeholder notifications, workflow management and approvals.
The company said the platform has been developed to address the increasing complexity of fleet maintenance, where operators often need to coordinate activity between workshops, parts suppliers, logistics providers, manufacturers and other service partners.
Chris Horbowyj, UK commercial director at Targa Telematics, said: “UK fleet operators are managing increasingly complex maintenance ecosystems while facing continued pressure to maximise vehicle availability and control costs.
“With Maintenance Excellence, we are delivering an Agentic AI-powered solution that enables organisations to move beyond reactive maintenance and manual coordination to intelligent, autonomous management of the entire maintenance lifecycle. The result is greater operational efficiency, reduced downtime and smarter decision-making across the fleet.”
Targa cited research carried out in Italy among more than 120 mobility operators, which found that 69% believed integrated vehicle data management would improve the accuracy of information relating to vehicle downtime, while 66% said better coordination of maintenance information could help reduce vehicle inactivity.
The company also said data from its Targa Telematics Observatory suggests that applying AI to fleet maintenance could reduce maintenance costs by up to 30% and cut vehicle downtime by 13%.
