Beyond the Check Engine Light: How AI Transforms Vehicle Service
- Industry
- Automotive
- Tech Stack
- Next.js · Python
- Timeline
- 14 weeks
- AI Effective Rate
- 85%
A dashboard light tells a driver something is wrong. It rarely tells them what, how urgent it is, or what it will cost — and that gap is where trust in a service network is lost.
We rebuilt the diagnostic journey around one question: what does this specific car, with this specific history, need next? Telemetry that already existed was being discarded at the depot. Surfacing it changed the conversation before the customer ever picked up the phone.
From warning light to work order
- Capture
- Fault codes stream from the vehicle continuously rather than at service intervals.
- Classify
- A model ranks each fault by urgency and likely root cause, trained on completed work orders.
- Quote
- Parts and labour are estimated up front, so the booking screen shows a price, not a question mark.
The result is a service desk that opens with a recommendation instead of a diagnosis fee. Advisors spend their time on the exceptions, which is the work only a person can do.
What changed
First-time fix rate rose because the right parts were on the shelf before the car arrived. The measurable win was throughput; the durable one was that customers stopped feeling sold to.