The context
A French industrial equipment manufacturer builds equipment installed at end customers across the country. Until now, a failure meant a phone call, a trip, an on-site diagnosis, and sometimes a second visit because the right part was not in the van.
The manufacturer wanted two things: to know remotely how its equipment actually behaves in service, and to be able to hand that data back to its customers, who are starting to ask for it and whom European data regulation now entitles to it.
What we did
We added cellular telemetry from the equipment into AWS IoT Core, then built the platform that makes use of it.
- Ingestion and storage of the measurements, with a data model designed so that adding a new equipment type does not mean rebuilding the pipeline.
- Predictive maintenance trained on operating history, so an intervention is triggered before the failure rather than after the customer’s call.
- Documented data portability APIs for end customers, built to satisfy the obligations introduced by the Data Act.
- Three read channels over one source: those REST APIs for end customers, an MCP server for agents, and the web interfaces used internally. Three views of one dataset, not three pipelines to keep in step with each other.
- Administration interfaces for fleet management and after-sales tracking.
The outcome
Interventions are now planned rather than endured, and the support desk answers with the full history of the equipment in front of it.
Data portability, approached at first as a regulatory constraint, turned out to be a commercial argument: the manufacturer now sells visibility over its equipment as a service, to customers who needed it without knowing how to ask.
The delicate part was not the predictive model but the alert threshold. It trades false alarms against missed failures, and that trade belongs to the maintenance team rather than to the model: a business setting, exposed as one, rather than a parameter buried in a notebook.