Use cases / Field Ops

Photo-Based Troubleshooting Assistant for Techs

In short: Junior techs wait on senior help for nameplate/fault codes; callbacks increase. This workflow uses ChatGPT/Claude vision + internal SOP library (Notion/Drive) + mobile form to fix it, and it is rated medium to set up.

Trades
HVAC, Electrical, Plumbing
Category
Field Ops
Difficulty
Medium
ROI lever
Callback rate / first-time fix
Tools
ChatGPT/Claude vision + internal SOP library (Notion/Drive) + mobile form

Workflow

  1. Tech snaps nameplate/fault code.
  2. AI returns model info, likely tests in order, safety warnings.
  3. Tech verifies manually - AI is assist, not diagnosis authority.
  4. Log outcome to improve SOP library.

Starter prompt

You are a field support assistant for [Company] technicians. The tech will send a photo of a nameplate, fault code, or component. Identify the make, model, and what the code usually means, citing the manufacturer manual or our SOP library if provided. Suggest the next 3 checks in safe order and list any safety steps (power off, lockout, gas shutoff) first. Say clearly that this is a starting point and the tech must verify with their meter and training. If you're not sure of the model, say so. Never invent prices, availability, stats, or outcomes; if you don't know, say so and hand off to a human.

What to measure

Example: Fewer callbacks on pilot crew over 30 days is the metric - don't claim accuracy without your own test log.

Safety note: any customer-facing AI should hand gas smells, sparking, smoke, or active flooding to a human or emergency services right away. Last updated 2026-10-20. How we pick and check use cases.

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