CodeComplete service history per vehicle
Every job done on a car is recorded against the vehicle, so when it returns, the full history — parts, work, dates — is on screen in seconds.
Case study — AI workshop management system
AutoCare AI
A workshop's memory: every car's service history in seconds, reminders on time, and diagnosis help on tap.
AI ProjectIn productionPHPMySQLFlutter
Overview
About this project
AutoCare AI is a management system for car workshops, built as a complete PHP and MySQL application — the technology stack that runs natively on the hosting workshops already have. It keeps customer and vehicle records, a complete service history for every car, maintenance reminders, and an AI fault-diagnosis assistant that gives mechanics a starting point on common faults. A Flutter app connects to the same system for work away from the desk.
The challenge
The problem it solves
A workshop's most valuable asset is its memory — what was done to this car, when, and what is due next — and in most workshops that memory lives in a paper register. Registers get lost; this one's owner lost his twice. When a car returned, nobody could pull up its history, follow-up maintenance was never reminded, and diagnosis started from zero every time. The challenge was to digitise the register without changing how a workshop actually works: fast entry at the counter, history in seconds, and reminders that bring customers back.
What we built
Features that do the work
Customer and vehicle records
Customers and their cars are kept as proper profiles, ending the search through register pages for a phone number or a number plate.
Maintenance reminders
The system tracks when a vehicle is due for its next service and flags it, turning the workshop's memory into repeat business.
AI fault-diagnosis assistant
Mechanics describe symptoms and get likely causes and checks for common faults — a starting point that speeds up diagnosis without replacing judgement.
Job and service records
Work in progress and completed jobs are recorded against each vehicle as the workshop's permanent, searchable register.
Staff accounts with private workshop data
The workshop's team signs in with staff accounts; every record is scoped to that workshop and invisible to anyone else (production upgrade, October 2026).
Technology stack
PHPMySQLFlutter appAI diagnosis chat
Project journey
How AutoCare AI got here
- October 2026
Concept & design
The concept was a register that cannot be lost: the workflows were mapped from the workshop counter — vehicle arrives, history opens, job is recorded, next service is due.
- October 2026
Build
The full PHP and MySQL application was built — records, service history, reminders and the diagnosis assistant — with the Flutter app connecting to the same backend.
- October 2026
Quality pass
The system was tested against workshop reality: returning cars, repeat customers, and history lookups under time pressure at a busy counter.
- 21 October 2026
Production upgrade
AutoCare AI was upgraded to production: staff login with per-workshop private data on every record, and the diagnosis chat moved to a server-side AI engine.
Current status
Where it stands today
Production-ready build complete — staff accounts, workshop-scoped data and the AI diagnosis engine are in place. Deployment is in progress.
Next step: Installation on the workshop's hosting with its MySQL database, followed by the Flutter APK build for the team.
Client words
What the client says
“Our service history was in a register that got lost. Twice. Now when a car returns I pull up everything we did on it in seconds, and the diagnosis assistant gives my mechanics a starting point on the common faults. That is all I asked for, and it does it.”
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