Company brain AI for multi-brand equipment service

A similar manual, a different unit

A service team looks after equipment from several manufacturers. A request concerns a family of machines with different control variants, and the library holds manuals for an earlier and a newer variant. The service history records a controller replacement, so the serial number alone does not settle which manual to use. Searching for the model name returns both.

A fluent answer says nothing about whether it is current, so the assistant answers only from the material it retrieved. Facts are updated through changes in the sources and need no retraining of the model. A withdrawn manual stays in the archive to explain past requests.

What it costs and when it pays back

The model is a small item here. The result depends on the time that searching and asking around take today, and on how much of it remains for checking the answer. In service work, picking the wrong manual costs more than the search itself: the technician works from a document for another variant and has to go back to the machine. We count such return visits separately in the trial.

Before we price the build, we run a test on 20 to 100 questions the team has already asked: we compare the application's answer with what the employee found by hand, and we count the time from the question to the source. The test takes 5 working days and costs €0.

When a library is enough

An ordered library or the manufacturer's search is enough when the technician knows the equipment's designation and needs one document. Microsoft's guidance for SharePoint content describes why current, ordered sources matter for an agent. An assistant is justified when the answer means linking documentation from several brands with the register of units and the service history. Creating requests or ordering parts is a separate agent scope with its own permissions.

Where to start

The first scope is one family of equipment with its variants, and a documentation owner who resolves contradictions. A wider scope is described in private ChatGPT for maintenance teams.

For the first call, one question that keeps coming back to colleagues and where the team looks for the answer are enough. You do not need to send confidential documents, and you receive the written plan within 2 working days.