Agentic AI diagnostics and repair recommendations based on
Client, SLA, System, Repair history, and ticket data
Tribal knowledge of repairs is vulnerable to employee turnover. When experienced technicians leave, critical diagnostic expertise walks out the door
Each request requires manual review of troubleshooting steps and parts against policies — slowing fulfillment timelines
Decision-making depends on technician experience. Without accessible historical insights, less experienced technicians struggle with diagnoses, causing delays
AI identifies the equipment for targeted historical analysis
AI retrieves repair resolution notes of entire product history
AI extracts actions, results are validated and enriched
Actions are and ranked by frequency and occurrence
AI provides repair actions, steps, and component guides