Automotive
How we installed a private AI workforce inside a real automotive business
McGuire · August 2026 · 9 min read
Jackson Hole. Repair, collision, detailing, glass. Local hardware, an operator OS, a CCC EMS bridge, and the software the shops already ran.
Detail Driven Enterprises runs repair, collision, detailing, and glass in Jackson Hole. Each line already had software. We did not replace Tekmetric. We did not replace CCC ONE. We installed an operator OS and a workforce on top of what they already ran.
The stack on the ground: Tekmetric for repair, CCC ONE for collision, Omega EDI, GoHighLevel, QuickBooks, Stripe, Google Ads, Meta, Google Business Profile, GA4, Search Console, Slack. Four shop types. A person was still the integration.
The architecture is boring on purpose. Private Linux hardware at the bottom. Collectors and a local CCC EMS bridge. An operator OS in the middle: command, inbox, quotes, bookings, shop views, money, demand. A manager, the orchestrator, assigns work. Specialized agents watch follow-up, monitoring, and reporting. None of them get a master login to the company.
Collision is the honest hard part. CCC will export EMS estimates and a Final Bill. It will not export the schedule. The bridge reads the folder CCC already writes. It does not scrape DATA.DAT.
Inference is hybrid. Routine work stays local. When a job needs a stronger model, it goes to the cloud. That is a routing decision, not a brand position. Operators care about the morning report landing, not about where the tokens ran.
What we will not put on this page yet: hours saved, dollars recovered, owner quotes. Those go here when they are measured and the operator is willing to stand behind them. Until then, the facts are the story.
If you want the same shape inside your shops, start with the audit. We will tell you if the stack and the volume of leftover work actually justify a build.