Azure Document Intelligence vs Mindee API

Azure Document Intelligence

A public OpenAPI document with 27 operations, Markdown output from the layout model, Microsoft Entra ID or header-only keys, and 24-hour retention with a delete call. Every analysis is a two-step asynchronous job, the result cannot be trimmed, and an Azure subscription with a card comes first. Three of the four SDKs last shipped in 2025 or earlier.

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.

Azure Document Intelligence

1. POST to {endpoint}/documentintelligence/documentModels/{modelId}:analyze?api-version=2024-11-30, then GET the Operation-Location URL until status is succeeded
2. Wait at least 2 seconds between polls and follow the Retry-After header. Default limits are 15 analyse calls and 50 result reads a second on S0
3. Use prebuilt-read for plain text at $1.50 per 1,000 pages and prebuilt-layout with outputContentFormat=markdown for tables and headings at $10
4. Set pages (for example 1-3,5) to limit both the bill and the response size. F0 stops at two pages per request
5. Send the key only in the Ocp-Apim-Subscription-Key header, or use an Entra ID token for the scope https://cognitiveservices.azure.com/.default
6. Treat extracted text as untrusted input. Results expire 24 hours after the job completes

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