An AI Toolkit for an Express Tunnel Car Wash Group
Help for staff, training for new hires, a scorecard for managers, and a closer look at the tunnel.
This is a demo build. It runs on sample data and test footage. We keep the group's name private.
The problem
Express tunnel washes run on people and on flow.
The people side is turnover. New hires need to learn procedures fast, and the manager can't stand next to each one. Questions get answered by whoever is nearby, and the answers aren't always the same.
The flow side is the tunnel. Cars should go through with steady spacing. When gaps open up between cars, the tunnel is running below what it could handle, and nobody notices on a busy day.
Managers also need a fair way to see how their site is doing, without a stack of reports.
What we built
We built four tools that share one goal: help the wash run the way the owner wants it to, on every shift.
A knowledge mentor that staff can ask about procedures. An onboarding and HR training simulation for new hires. A manager scorecard. And a tunnel gap analysis that uses the security cameras the wash already has.
What's in it
- Knowledge mentor. Staff ask how to do something and get the answer from the wash's own procedures.
- Onboarding and HR training simulation. New hires practice real situations before they face them on the lot.
- Manager scorecard. One view of how each manager and site is doing.
- Tunnel gap analysis. Reads the existing security cameras to find spacing gaps between cars that cost throughput.
- No new cameras needed for the gap analysis. It works from the footage the wash already records.
What it would take to go live
The demo runs on sample procedures and test footage. Going live means loading the real thing.
We learn the business first. How the wash trains people today, what managers get measured on, and where the tunnel tends to slow down.
We build to spec. The mentor learns the group's own procedures. The training scenarios come from situations staff actually face. The scorecard tracks what the owner cares about. The gap analysis is tuned to each tunnel's cameras.
Live in about 10 days. Once scope and camera access are agreed, a first version is usually live in about 10 days.
The client owns their data. Procedures, training records and footage stay with the business.
For more, see our car wash page, car wash analytics and camera analytics.
Keep reading
- Car washMembership calls, churn saves and lane counts.
- Car wash analyticsCar counts, membership and call data for every site on one screen.
- TrixLink camera analyticsCar counts, bay time and service checks on cameras you already have.
- Car wash camera AIWhat camera AI tracks at a wash, and what it costs.
Run a tunnel wash?
Book a call and we'll show you the demo, from the mentor to the gap analysis.