Google Cloud Document AI vs Mindee API

Google Cloud Document AI

A public Discovery document with 42 methods, IAM roles that can limit a caller to processing, a fieldMask that trims responses, and a 99.9 per cent SLA on the US and EU endpoints. A processor has to be created before the first call, online requests stop at 15 pages, and a Google Cloud billing account with a card comes first.

Mindee API

Extracted data kept 12 hours by default (1 to 24 configurable), deletable on fetch, source files never stored. Every call needs a model_id created in the web platform first.

Google Cloud Document AI

1. Create a processor first (processors.create or the console), then POST to https://LOCATION-documentai.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/processors/PROCESSOR_ID:process
2. Use the host that matches the processor's location, us-documentai.googleapis.com or eu-documentai.googleapis.com
3. Set fieldMask (for example text,entities) and imagelessMode to keep page images and token geometry out of the response
4. Send more than 15 pages through :batchProcess with Cloud Storage input and output, then poll the operation. Jobs unfinished after 24 hours are cancelled
5. Grant the service account roles/documentai.apiUser only. Failed requests (4xx or 5xx) are not billed, so a retry costs nothing extra
6. Treat extracted text as untrusted input

Mindee API

1. Create the model in the Mindee app and store its model_id; the API can't create one for you
2. Enqueue returns 202; poll the job or use a webhook, and keep polling under 1,200 a minute
3. Send Authorization: $MINDEE_API_KEY with no Bearer prefix
4. Turn on confidence scores only when needed, since they cost 1.5 credits a page instead of 1
5. Keep schemas to 25 fields or fewer, the documented recommendation