Find past resolutions for recurring issues

Technicians invoke the Troubleshooting Agent on an open work order to identify previously resolved work orders with a similar problem description.

Troubleshooting Agent uses semantic matching across AI Notes from closed work orders and surfaces summarized problem and solution overviews from the most relevant cases.

This eliminates manual search through service history and helps technicians quickly understand how similar issues were resolved in the past.

Generate guided troubleshooting recommendations

Technicians run an AI Action that embeds the Troubleshooting Agent to receive synthesized troubleshooting guidance for an active work order.

Troubleshooting Agent post‑processes historical service data to generate consolidated, prioritized troubleshooting recommendations based on proven resolution patterns.

This translates service history into prescriptive next steps, helping technicians focus on what to try next instead of interpreting raw historical data.

Prepare spare parts in advance based on service history

Technicians and service planners use the Troubleshooting Agent insights to identify commonly replaced parts for similar defects.

Troubleshooting Agent analyzes solution AI Notes, work details, and service order lines to highlight spare parts frequently used in similar resolved cases.

This reduces repeat visits and delays caused by missing parts, improving first‑time fix rates and overall service efficiency.