> Source: https://txtfetch.com/compare/azure-document-intelligence
> Plain-text twin — every page on txtfetch.com has one. https://txtfetch.com/text

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# txtfetch vs Azure AI Document Intelligence

Azure AI Document Intelligence is microsoft's prebuilt-model document api, billed per 1,000 pages. Here's an honest comparison: pricing math, capabilities, and where each tool wins.

at a glance

Azure AI Document Intelligence

**Billing**: per 1,000 pages (tiered by model)

**Rate used below**: $0.0015/page directional

**Free tier**: 500 pages/month free.

txtfetch

**Billing**: per document, regardless of page count

**Rate used below**: flat monthly quota (see plans)

**Free tier**: 500 documents/month, free, ongoing (Hobby plan)

capability table

| Capability | Azure AI Document Intelligence | txtfetch |
| --- | --- | --- |
| Billing unit | per 1,000 pages | per document |
| Format coverage | PDF, images, limited Office formats | 615 formats (Apache Tika, checked) |
| OCR for scans / images | yes | yes |
| Table extraction | yes | yes* |
| Complex layout fidelity | partial | partial* |
| Structured field extraction | yes | not yet* |
| Self-hosted option | no | no* |
| Single HTTP endpoint | partial | yes |

Vendor-published benchmarks are marked directional throughout. See sources below. \* txtfetch notes: Tables come back as structured rows and cells, not flattened text. Use ?format=markdown for GFM pipe tables, or ?format=json for table elements with a cells array. Output is clean linear or structured text, not a visual layout reconstruction. That's by design, but worth knowing. Structured markdown and element-JSON document output ship today (?format=markdown / ?format=json). Schema-defined field extraction means pulling typed fields per your own schema. That feature is on the roadmap, not shipped yet. We won't claim it early. No shipped self-host or VPC artifact today. It is on the roadmap. Apache Tika itself is free to run yourself. See the page below for what that takes.

Weighing self-hosting against either API? See [what running Apache Tika yourself actually takes](https://txtfetch.com/compare/self-hosted-tika).

the cost calculator

## Per page vs per document, worked out.

A 300-page PDF is 300 units of billing to Azure AI Document Intelligence. It's one document to txtfetch. Adjust the numbers to your own workload.

[Interactive cost calculator — adjust pages per document and documents per month to compare pricing against Azure AI Document Intelligence]

where document intelligence wins

-   Prebuilt models for common structured documents (invoices, receipts, IDs, W-2s) that extract named fields out of the box.
-   Deep integration with the rest of Azure Cognitive Services and enterprise Microsoft procurement.
-   This matters for regulated organizations already committed to that stack.
-   Confidence scores and bounding boxes per extracted field for auditability.

where txtfetch wins

-   Breadth: 615 formats, each with a real Apache Tika parser behind it. That's [checked against the exact build we run](https://txtfetch.com/formats/coverage), not a curated list of a dozen file types.
-   One HTTP endpoint. Pass a URL or upload a file, and get text back. No SDK and no async job polling required.
-   Priced per document, so a 300-page report doesn't cost 300x a one-pager.
-   A durable free tier (500 documents/month, ongoing) rather than a time-boxed trial.

What we don't claim yet: schema-defined structured field extraction, or an uptime SLA. Those ship later. See the capability table above.

next step

Ready to switch? See [what your code looks like after migrating from Azure AI Document Intelligence](https://txtfetch.com/migrate/azure-document-intelligence): the call you run today, the call that replaces it, and a drop-in adapter.

sources

-   [Azure AI Document Intelligence: Pricing](https://azure.microsoft.com/en-us/pricing/details/document-intelligence/) Accessed 2026-07 directional
-   [Microsoft Q&A: Document Intelligence per-page rate consensus](https://learn.microsoft.com/en-us/answers/questions/tagged/azure-ai-document-intelligence) Accessed 2026-07 directional

## Check the numbers yourself.

The benchmark runs against a committed corpus. You can re-run it.

[See the benchmarks →](https://txtfetch.com/benchmarks)

[Get an API key →](https://app.txtfetch.com/signup)