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For dealerships and dealer groups

Your team knows why.

A repair order says the work is complete. Your advisors know the questions, handoffs, and exceptions that got it there. Daimon Lab examines whether that context could support a paid data or evaluation project.

Assess dealership dataHow the process works
Linked records → decisions → outcome → AI testIllustrative sales journey
Linked history · sales journey
One vehicle purchaseDELIVERED

Linked by lead, vehicle, appraisal, and deal references.

  1. Vehicle inquiryOPEN

    Shopper asks about a specific vehicle and mentions a possible trade-in.

  2. BDC callVISIT SET

    Representative clarifies the trade question and books a visit without promising a trade value.

  3. Store visitTEST DRIVE

    Shopper drives the vehicle; the team records a concern and the desired next step.

  4. Trade appraisalREVIEWED

    Appraiser checks condition and records a reviewed trade value rather than relying on the shopper's estimate.

  5. Desk quotePRESENTED

    Desk checks price, trade, and purchase terms before presenting a quote.

  6. DeliverySOLD

    Shopper accepts the terms, signs, and takes delivery; the purchase outcome is recorded.

The check and decision

A reply is the start of the sale, not its outcome.

The lead status cannot show what the shopper asked, what the appraisal found, why the quote changed, or whether a purchase followed.

What happened nextThe trade is appraised, a reviewed quote is accepted, and the vehicle is delivered.
What an AI team could testScore whether an assistant carries the trade question through the appraisal and quote instead of treating the first reply or a shopper estimate as a firm offer.

What an export leaves behind

A booked appointment can hide a requested time, a confirmed slot, or a visit that never happened. That distinction lives in the people and processes around the record. It can change what an AI system should learn or be tested against.

  • Service: requests, confirmations, advisor handoffs, and repair milestones.
  • Sales: lead responses, appointment coordination, and CRM follow-through.
  • Used vehicles: appraisal reasoning, pricing changes, and reconditioning decisions.
  • Team knowledge: approved checklists, training materials, and expert demonstrations.

What a buyer could use

An automotive AI team might need to test whether its service assistant knows when to confirm a booking and when to ask an advisor. A useful example would connect what the employee knew, the check performed, the response, and what happened next. The system status alone cannot answer that test.

See the dealer-group offersRead the evaluation method

The first look stays high-level

An assessment starts with the task, broad source categories, approximate history, and known restrictions. A high-level description is enough for that conversation. A later written plan would name the permitted sources, exclusions, recipients, and use.

Rights to use the source for a specific AI task are reviewed before any records are shared.