Normalize to structured data
Messy text → clean vehicle record.
Convert noisy strings into structured vehicle fields (make/model/trim/year/etc.) with traceable decisions.
Best for
Common places this service fits well.
- Search
- De-duplication
- Analytics
- Exports
Inputs
What you provide.
- Raw text (OCR or user input)
- Optional: locale/market
Outputs
What you get back.
- Structured vehicle object
- Field-level confidence
- Source trace (what influenced what)
Try normalize
Send a noisy vehicle description text and see normalized fields.
Limited demo. For higher volume and auth, sign up and use your API key.
Output
JSON viewer and cURL you can copy.
// Run the demo to see a live // JSON response here. // For full docs, sign up and // open the API reference.
Part of a pipeline?
Structured vehicle data is the clean input that valuation and search depend on.
- Photo input
- 1OCR
- 2Normalize
- 3Valuation
Explore
Related services
Most teams start with one capability, then add the ones that remove friction next.
OCR
Read what’s on the car, not what the camera wished it saw.
Extract text from photos (dash, documents, stickers, part numbers, plates/VIN) with layout-aware results.
Damage recognition
Turn “looks fine” into measurable findings.
Detect and highlight visible damage areas, returning locations and severity signals you can review.
Car Side Recognition
Know which side you’re looking at, and where the car actually is.
Classify the vehicle side/orientation and return stable geometry for downstream tasks (cropping, alignment, QA).