End-of-life or not? From the image finding to a reasoned determination

A damaged vehicle is offered for purchase: front damage, airbags deployed, high mileage. The dealer wants to know whether a repair pays off, the recycler whether the vehicle may be sold at all. Both questions hinge on the same classification — and the new European end-of-life vehicle rules require it to be reasoned.

The chain joins two surfaces with separate roles: the Hub delivers an image finding and a revenue estimate, the Compliance surface records the classification at the receiving facility — by an independent, qualified person. The image finding grounds the suspicion; it is determined only in the file.

What this case requires

• Photos from several angles. The classification takes one to ten image addresses; what was not photographed appears in coverage.viewsMissing.
• Market value and repair estimate where known. Without the market value the economic axis remains nicht_beurteilbar.
• A receiving, recognised facility. The Compliance surface belongs to the facility taking the vehicle in; it is the sole legal issuer.
• An independent, qualified person for the assessment. The Annex I assessment requires a signed-in person in the compliance lead role.
• The entitlement to query the vehicle. With the call you confirm that you are the keeper, the owner or demonstrably authorised or otherwise legally entitled, and that you use the identification number solely for the stated permissible purpose.

The sequence

The table names the responsible call per stage and what exists afterwards. The reasoning for why a stage cannot be skipped follows below it.

Why each stage is needed

1. Obtain the image finding. POST /vision/vehicle/elv-classification takes imageUrls and optionally vehicle with firstRegistration, mileageKm, marketValueEur, repairEstimateEur and damageDescription. Back come classification, technicallyIrreparable, economicallyIrreparable, per criterion finding, confidence and observation, plus economicAssessment, coverage and visualOnly.
2. Estimate the parts revenue. GET /vin/{vin}/economic-evaluation returns revenuePotential and purchaseRecommendation. The recommendation deliberately rests on the price minimum — a buyer pays before a single part is sold.
3. Open the case at the receiving facility. POST /compliance/cases takes facilityId, jurisdiction, legalProfile with DE_FZV_ANNEX_9_CURRENT or EU_ELV_2028, and the vehicle. From here the classification is no longer an estimate but part of a file with an event chain.
4. Have it assessed by an expert. POST /compliance/cases/{id}/annex-i-assessments takes expertPartyId, qualificationId, independenceAttestationId, partACriteria, partBCriteria and conclusion. A signed-in person carries out this action; the image finding can prepare it but not replace it.

curl -X POST \
  -H 'X-Api-Key: <API_KEY>' \
  -H 'Content-Type: application/json' \
  -H 'Idempotency-Key: altfahrzeug-pruefung-0917' \
  -d '{"imageUrls":["https://example.com/front.jpg","https://example.com/seite-links.jpg","https://example.com/innenraum.jpg"],"quality":"standard","vehicle":{"firstRegistration":"2011-04","mileageKm":236000,"marketValueEur":1500,"repairEstimateEur":4200,"damageDescription":"Frontschaden nach Wildunfall, Airbags ausgelöst"}}' \
  'https://api.tapinomahub.com/vision/vehicle/elv-classification'

What you end up with

What remains is a classification that starts with a traceable image finding, has an economic basis and ends with a reasoned determination by a qualified person. Whether the vehicle is sold or recycled can then be defended.

Where to find this in the documentation

The binding field lists, error codes and sample responses live in this surface’s OpenAPI contract at docs.tapinomahub.com (tapinoma-hub, tapinoma-compliance). All use cases arranged by surface and role: overview of the use cases.