AMPS works with the manufacturer or importer to define one programme: brands, repair areas, capture scope, data use and deliverables. The OEM then offers that programme into its dealer network, so repair, maintenance and service data is captured the same way across many dealer workshops.
Each dealer that takes part agrees the capture scope and data terms for its own site in writing, and an AMPS programme lead coordinates the start site by site. Every site runs the same method, so the data from one dealer can be compared with the next.
A programme can be scoped for a dealer group’s own sites. Where the group’s brands are part of an OEM programme, we align the capture scope and method with it.
The data captured in your bays is not only useful to physical AI. It also makes your own workshops easier to run, easier to train for and better prepared for automation.
Independent chains service many brands across many branches. An AMPS programme captures that multi-brand repair, maintenance and service work with one method, so data from one branch can be compared with the next.
Which repair areas and branches are in scope is agreed during scoping and written into your agreement.
Tyre changes, balancing, TPMS service and alignment, plus quick-service maintenance jobs. The work is short, frequent and repeatable, exactly the kind of task where physical AI tends to arrive first, and where good motion data shortens the path.
Smart repair, bumper and plastic repair and dent removal depend on fine motor skills and judgement of the surface, which is why recorded expert technique is so valuable for physical-AI systems learning this work.
Maintenance, service and repair of trucks, buses and trailers: air brakes, hydraulics and commercial-vehicle electronics. The work involves large parts and shared tasks, so capturing it builds the data for robot-assisted handling of heavy components, and supports safer manual work today.