Demo scenarios on sample data. Honest by design.

A customer calls at 7:42pm with a check-engine light, needing to drop off before work tomorrow. After hours, the call would normally hit voicemail.

In the demo, Concierge answers, reads live bay availability, offers a 7:30am drop-off, confirms it on the call, and writes the appointment to the calendar with the vehicle and service summary attached.

The repair order that would have gone to voicemail is on tomorrow’s schedule before the owner wakes up.

Three booked services next week each need the same brake component, and current stock covers only one. A manual min/max alert would not fire until the shelf is already empty.

In the demo, Quartermaster projects the shortfall from booked work, drafts a purchase order to the right vendor with an idempotency key, and surfaces it for one-tap approval — well ahead of the stockout.

The bay never stalls waiting on a rush order, and a re-run can never double-order the part.

The owner wants to know whether the shop is trending the right way, but never has time to build a report from the raw numbers.

In the demo, Analyst compiles ARO, technician efficiency, bay utilization, car count, and agent-driven revenue overnight, then writes a short plain-language briefing — what moved, what to watch — delivered before open.

The owner starts the day knowing exactly where the shop stands, without decoding a dashboard.

A junior technician pulls a misfire code on an unfamiliar engine and would normally hunt across four separate database logins while the car waits.

In the demo, the technician photographs the code on a phone; the Diagnostician searches the unified canon and returns the most-confirmed fix with the OEM procedure and a confidence score, on the bay floor.

A junior tech reaches a master-level answer in seconds — and the guess that becomes a comeback is avoided.