How do you extract data from an ID or passport with AI?
You extract fields from an ID, passport, or driver's license by sending the image to a vision model with a schema — name, date of birth, document number, expiry. The prototype is easy; the production risk is single-character errors, like a wrong digit in a document number, that general models make and can't flag. For KYC you want a model that returns per-field confidence and the location it read each value from.
Last updated 2026-07-20
The basic approach
Send the ID image to a vision model with a structured-output schema of the fields you need. It handles varied ID formats without templates, and it's enough for a demo.
Why it's risky in production
IDs are dense, glossy, and fixed-pitch. A general model misreads a character and gives you no way to know. In KYC a silent error is both a compliance problem and a fraud vector — and you can't audit an answer with no provenance.
The safer pattern
Use a model that returns confidence and bounds (Interfaze exposes these in precontext), route low-confidence fields to manual review, and keep each bounding box as provenance for your audit trail.
FAQ
Can ChatGPT read a driver's license?
Yes, but with occasional single-character errors and no confidence signal, which is hard to defend in a KYC pipeline.