Understand the history of any piece of equipment in just one click

The problem: taking over equipment with no context

You've probably assigned an intervention to a technician who has never worked on that particular piece of equipment. Before they even touch it, they need to understand what has happened over the past weeks or months: which failures occurred, which symptoms kept recurring, which spare parts were already replaced, which adjustments were made.

In most teams, that means going through the task history one by one, reading activity reports, trying to piece together a timeline. Time taken away from the actual job — sometimes as much time as the job itself.

What it actually costs

The problem is not that information is missing. In a well-used CMMS, interventions are documented: every closed task leaves a trace, every activity recorded by a field technician accumulates in the equipment record. But this information is fragmented. It is organized chronologically, not by relevance. To extract meaning from it, you have to read it, sort it, and mentally summarize it.

This is synthesis work that every technician redoes from scratch every time they take over equipment — at every handover, every time they work on a machine they don't usually follow.

AI synthesis: an automatic reading of the history

From the equipment record in Mobility Work, network administrators now have a dedicated tab for AI synthesis. With one click, the system analyzes all tasks scheduled over the last six months — whether completed or not — and generates a structured summary, written in the user's language.

The summary is not a list of tasks. It is an interpreted reading built from three types of data: the tasks themselves (description, associated maintenance plan, tags), the activities recorded by technicians (what they did, time spent), and spare part consumptions (which part, which quantity, on which date). In a few seconds, the technician has a consolidated view that would have taken twenty minutes to reconstruct manually.

A concrete example: a technician is covering for an absent colleague on a compressor. They open the equipment record, consult the AI synthesis, and immediately read that the cooling circuit has been the subject of three corrective interventions in two months, with a head gasket replaced during the last one. They know where to look first — without reading ten individual reports.

Three situations where it changes your day

Last-minute replacement. The usual technician is absent. Their replacement can take over the equipment without waiting for an oral briefing or relying on a colleague's memory.

Shift handover. At the end of a shift, the incoming technician doesn't need a lengthy debriefing to understand the status of the equipment. The synthesis serves as a structured handover.

Resuming after a production shutdown. After a long stop — extended weekend, annual overhaul — the technician resuming supervision of a facility can quickly identify equipment that showed warning signs before the shutdown.

What changes for the organization

The value goes beyond the individual technician. A team that spends less time reconstructing intervention context is a team that documents better, because every recorded activity feeds the synthesis that will be useful to the next person on the job.

The loop becomes virtuous: documenting is worth the effort, because documentation is immediately usable — not just six months later during an audit.

Three actions to benefit now

1. Check the quality of your activity and consumption records: AI synthesis is only as good as the data it analyzes. If technicians close tasks without filling in activities or logging spare part consumptions, the summary will be minimal. Start with your most critical equipment and ensure every intervention is documented.
2. Make synthesis part of the handover ritual: before any intervention on unfamiliar equipment, consulting the AI synthesis becomes as natural a reflex as scanning the QR code.
3. Share summaries during maintenance meetings: the synthesis can feed the weekly review of critical equipment, giving the whole team a shared view of the fleet's condition.