Trapeze EAM, Preteckt Now Integrated to Benefit Transit Maintenance Teams

Trapeze’s EAM software now integrates with Preteckt’s AI-predictive maintenance software to streamline processes and empower maintenance teams.

The joint initiative integrates Preteckt’s AI-driven vehicle prognostics with Trapeze’s enterprise asset management software to create a fully automated predictive maintenance solution.

By combining these two powerful applications, agencies will be able to prevent catastrophic failures from occurring by providing predictive maintenance plans for ease of use in diagnosing issues, as well as filing work orders from a single system.

The Trapeze, Preteckt Partnership

Driven by customers who desired work orders and predictive maintenance plans under one system, Trapeze and Preteckt collaborated on creating an integrated solution that allows for maintenance teams to continue using the Trapeze EAM system, while reviewing Preteckt’s maintenance plans as part of the service requests.

“Preteckt is always looking for partners to work with to ensure customer needs can be met with innovative solutions,” said Krish Inbarajan, CEO at Preteckt. “This is an industry first solution driven by the need from joint customers to ensure a cohesive solution is provided in partnership with Trapeze EAM. This EAM team is open and really cooperative to work with, and we look forward to working closely together in the future.”

By conducting real-time monitoring on bus components and configuring predictive alerts, issues, and faults can be proactively addressed. Preteckt provides these early warnings of failures to ensure actions can be planned with the right resources and parts availability. Technicians receive these alerts and a specific repair plan via Trapeze EAM.

Constant visibility into vehicle conditions lowers maintenance costs per mile, minimizes in-route failures, and increases repair efficiencies in the yard, according to Trapeze and Preteckt officials.

“Through our collaboration with Preteckt, customers can go beyond preventative maintenance  using big data and AI insights to prevent failures,” said Steve Sawyer, GM Trapeze EAM. “The best part is technicians can access the information from the EAM system they know. ”