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Automotive AI evaluation

Did the AI promise too soon?

A service assistant may confirm a loaner before checking the store's rules. A scoped evaluation can test that decision, count completed tasks and critical errors separately, and show the limits of the test sample.

Scope an evaluation
Linked records → decisions → outcome → AI testIllustrative chat-to-visit journey
Linked history · chat
One loaner requestVISIT COMPLETE

Linked by chat, appointment, store check, and follow-up references.

  1. Chat requestASKED

    Customer asks for a Tuesday service visit and a loaner vehicle.

  2. Assistant draftHELD

    A draft says a loaner is reserved. The advisor holds it because availability has not been checked.

  3. Advisor handoffREVIEWED

    Advisor carries the customer's request from the chat into the appointment record.

  4. Availability checkNONE TUESDAY

    Store loaner list shows none available Tuesday, so the team looks for another option.

  5. Customer callRIDE CHOSEN

    Advisor explains the constraint; customer chooses a ride rather than a different appointment day.

  6. Visit outcomeCOMPLETE

    Tuesday visit proceeds without a loaner reservation, and the actual outcome is recorded.

The check and decision

The store checks availability before making a promise.

A chat draft cannot establish the loaner inventory, the advisor's call, or the option the customer chose.

What happened nextNo Tuesday loaner is available; the advisor arranges a ride and the service visit proceeds without an unsupported reservation.
What an AI team could testScore whether an assistant checks loaner availability before a promise and offers a handoff when the requested option cannot be met.

A test with a real-world decision

Picture a customer who needs a service visit and transportation. The assistant should check the missing information before confirming the arrangement and ask a person for help when needed.

A completed booking and a risky confirmation are different findings. Count them separately to see whether the assistant knows when to pause.

See a complete test design

What the report would show

A proposal defines cases and a scoring rubric for one system version. In the booking example, the report could separate completion, rule adherence, escalation, and record accuracy, with critical errors counted on their own.

What the results cover

A benchmark describes performance on its defined sample. To test broader situations, expand the cases and score the next version separately.

Holdouts and reuse rules protect the meaning of later scores when examples are also used for training.

Need to recreate the task environment? Explore custom projects