Fleetio’s new AI Service Advisor is a built-in maintenance expert designed to help fleets make faster maintenance decisions and automate routine processes.
Built on one of North America’s largest proprietary fleet maintenance datasets, Service Advisor assessed more than $1.4 billion in maintenance spend during a six-month open beta, helping assets return to service an average of 2.5 hours sooner per repair.
Since the open beta, Service Advisor has expanded from helping teams evaluate maintenance to automating more steps across the maintenance workflow.
“We’re moving toward a world where fleet technology does more than surface information. It should understand the context behind a decision, apply what it has learned from years of operational data and help determine the right action in the moment,” said Jorge Valdivia, CTO at Fleetio. “AI Service Advisor brings that intelligence directly into the maintenance workflow by automating routine decision-making to help fleets focus on the situations that require experience, ultimately driving real cost savings.”
The AI Service Advisor prioritizes issues that need attention, evaluates repairs in context, drafts service, advances low-risk approvals within fleet-defined policies and closes routine follow-up after service.
According to Fleetio, that translates to fewer delays between identifying a problem and initiating repairs, reducing time in the shop.
Service Advisor applies fleet-specific intelligence throughout the maintenance process by:
- Drafting work orders from maintenance signals.
- Assessing in-progress maintenance against fleet history, costs, warranty opportunities and maintenance patterns.
- Prioritizing issue to focus on items with the highest operational impact.
- Automatically resolving eligible issues and approving low-risk repairs within fleet-defined policies.
Fleets are increasingly managing more maintenance signals, making it difficult to know what needs immediate attention and what can proceed safely.
Service Advisor helps fleets scale the judgment of their best maintenance experts without adding another process to manage. By automatically resolving more than 2,000 maintenance issues each month, it eliminates routine follow-up after service and keeps maintenance records current. Behind that intelligence are 14 years of maintenance data spanning millions of assets and tens of millions in repair orders.
