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The senior engineer who retired last year never has to leave.
When an experienced technician retires or leaves, their knowledge — built over years of working a specific product line or facility — goes with them. The junior technician sent to site has the manual but not the intuition. First-time fix rates drop. Repeat visits cost. The gap between documented procedure and operational reality widens every year.
A technician arrives on site, scans the equipment with their phone or smart glasses, and sees exactly what to do — not the generic manual, but the specific procedure for this machine, this configuration, with annotations from every engineer who has ever worked on it. Edge cases are flagged before they become problems. The senior engineer's patterns, captured and structured, are available to every technician on every job.
A combination of computer vision (equipment recognition from camera feed), a structured knowledge graph (built from service records, manuals, and annotated expert walkthroughs), and an AR overlay layer that renders step-by-step guidance anchored to physical features of the machine.
The knowledge layer is built once from existing documentation and a structured interview/recording process with experienced engineers. It updates with every completed job — closed-loop learning from field outcomes. The interface runs on standard iOS/Android hardware; smart glasses are optional but supported.
The system connects to existing service management platforms (ServiceMax, Salesforce Field Service, or bespoke) via API.