txtfetch vs Azure AI Document Intelligence
Azure AI Document Intelligence is microsoft's prebuilt-model document api, billed per 1,000 pages. Here's the honest comparison — pricing math, capabilities, and where each tool actually wins.
at a glance
Azure AI Document Intelligence
- Billing
- per 1,000 pages (tiered by model)
- Rate used below
- $0.0015/pagedirectional
- 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 | 1,000+ formats (Apache Tika) |
| OCR for scans / images | + | + |
| Table extraction | + | +* |
| Complex layout fidelity | ~ | ~* |
| Structured field extraction | + | not yet* |
| Self-hosted option | – | – |
| Single HTTP endpoint | ~ | + |
Vendor-published benchmarks are marked directional throughout — see sources below. * txtfetch notes: Tables come back as structured rows/cells, not flattened text: ?format=markdown renders GFM pipe tables, ?format=json returns table elements with a cells array. Output is clean linear/structured text, not a visual layout reconstruction — by design, but worth knowing. Structured markdown and element-JSON document output ship today (?format=markdown / ?format=json). Schema-defined field extraction — pulling typed fields per your own schema — is on the roadmap, not shipped. We won't claim it early.
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.
Azure AI Document Intelligencedirectional
—
Read/OCR tier ($1.50 per 1,000 pages — consensus figure, see caveat) · $0.0015/page
txtfetch
—
Azure AI Document Intelligence's figure is their cheapest OCR/base tier — forms, tables, and higher-fidelity models cost more on top. txtfetch bills a flat monthly document quota: the page count inside a document doesn't change your bill.
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, which matters for regulated orgs already committed to that stack.
- Confidence scores and bounding boxes per extracted field for auditability.
where txtfetch wins
- Breadth: 1,000+ formats through Apache Tika, not a curated list of a dozen file types.
- One HTTP endpoint — pass a URL or upload a file, get text back. No SDK, 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.
Stop parsing. Start shipping.
Create an account and get an API key in minutes — the free Hobby plan needs no card.
Get started →