Field teams in energy and utilities often work where the network is weak and the cost of a wrong safety call is physical, not just a bad screen. A model that only works in the office, or that silently overrides a procedure, does not survive contact with a real site.
What makes AI work different here
- Connectivity is not guaranteed. Inspection and checklist tools have to finish the job offline and sync later. A cloud round trip cannot be on the critical path.
- Safety calls stay with a person. A model can flag what the camera or the form saw. It should not close a safety decision on its own.
- The procedure is the source of truth. Answers about a site have to follow the operating procedure and the asset record, not a general description of the equipment.
- Devices in the field are old. The model has to run on the hardware technicians already carry.
Where we typically start
We start from the job a technician is in the middle of, what must work with no signal, and which decisions stay human. One published example is outage-desk answers that read the live map. The other is utility field inspection, the closest shipped field workflow.
Services we typically provide
Case studies from this industry
Frequently asked questions
Will this shut equipment down automatically?
No. The pattern is a flag and a record. The person on site, following the procedure, makes the operational call.
What happens with no signal?
The inspection completes on the device and syncs when the network returns. The model used in the field is the one on the device, not one you hope to reach.
Is the published example an energy plant?
The energy study on this page is outage-desk answers that read the live map and refuse a time the map does not show. The utility inspection study is the field example: offline review that raised how many inspections a shift could finish. Neither one is an autonomous plant decision.