Less unexpected downtime
The prediction warns in time — the vehicle enters the workshop as planned instead of breaking down on the road.
AI-supported fleet management: vehicles, their documents, service events and the parts warehouse in one system — and the AI predicts likely failures and maintenance needs from historical data.
A vehicle breaking down on the road means lost transports and lost work; a forgotten expiry means fines; and scattered spreadsheets mean opaque costs. The fleet data exists — just not in one system, and it does not speak up in time.
The prediction warns in time — the vehicle enters the workshop as planned instead of breaking down on the road.
Inspection, insurance, vignettes — the system warns in time, nothing expires unnoticed.
A true per-vehicle cost picture — well-founded replace-or-keep decisions.
Chat-based AI agents and a classic graphical interface at the same time. Everyone can work in their own style.
The system covers every area of the fleet: registry, service, warehouse and prediction — in one place, connected.
Technical data, mileage and documents with expiry watching
From report through worksheet to closure, with costs
Part numbers, RFID, replacement cycles and stock levels
Expected maintenance needs from historical data
Dashboard and mobile view of the fleet status
Registration, technical inspection, insurance, vignettes — the system warns in time.
Report, worksheet, closure — your own workshop and external service partners in one system.
Costs per vehicle and per event — you see what each vehicle really costs.
Part numbers, RFID support, replacement cycles, multiple warehouses — used parts are booked to the worksheet automatically.
Maintenance needs and risks forecast from historical service and mileage data.
Active/idle vehicles, upcoming expiries, open service events and cost trends — on desktop and mobile.
The AI forecasts likely failures from historical service and mileage data. The vehicle enters the workshop when it hurts operations the least — not when it breaks down on the road.
The vehicle breaks down on the road — lost transport, emergency repair, waiting for parts
Planned workshop slot — parts prepared, downtime minimized
The return comes from the downtime days avoided, the fines saved, the optimized parts stock and the manual administration replaced.
Predictive maintenance reduces lost transports and lost work
No fines, no vehicle running with invalid insurance
No excess stock and no idle time caused by missing parts
Worksheets and registries without manual spreadsheets
A lost transport is direct lost revenue — prediction and expiry watching pay off fastest here.
Field teams’ vehicles stay deployable — with the mobile view the status is visible on the go.
A transparent cost picture and automatic expiry handling without administrative burden on the fleet manager.
Every service event, stock movement and document change is logged — and can be looked up later.
The AI warns and explains — the maintenance decision stays with the fleet manager.
Driver, mechanic, fleet manager and executive each with their own permissions, in an isolated company environment.
Full EU GDPR compliance. The company builds its own AI context: your data never trains external large language models and is never passed to third parties — your business secrets remain yours for the long term.
Already at a few dozen vehicles: the first avoided breakdown or forgotten expiry usually costs more than the system. In larger fleets the benefit of prediction and stock optimization grows proportionally.
It learns from your own fleet’s historical service events and mileage data: it forecasts risks from the failure patterns of similar vehicles under similar use — together with an explanation.
Yes. Your own workshop and external service partners are managed in one system — worksheets and costs are tracked per vehicle in both cases.
Yes. Besides the management dashboard there is a mobile view for field staff — vehicle status and worksheets are available on the go.
No. The system operates with full EU GDPR compliance, and the company builds its own, isolated AI context. Your data never flows into the training of external large language models and is never handed to third parties — the company knowledge you build remains exclusively yours.
In the pilot we set up the vehicle registry, switch on expiry watching, and show from the first months of data what predictive maintenance would deliver.