Comparison
VisionParse vs Azure AI Document Intelligence
Microsoft’s document service, and the broadest language coverage here — 300 for printed text. Cheaper per page than us for plain OCR. Their product documentation does not say whether your documents train their models.
Microsoft · every figure below comes from their own documentation, linked and dated · last checked 2026-08-08
Where Azure AI Document Intelligence is the better choice
- 300 languages for printed text against our 161.
- $1.50 per 1,000 pages for plain text against our $9.50 — and our $9.50 assumes the whole 2,000-page allowance is used. At 500 pages a month ours is effectively $38 per 1,000.
- Around 34 Azure regions, and a genuine on-premises option: the same models ship as containers you can run on your own hardware.
- Documents and results are deleted after 24 hours, with an API to delete them immediately.
- Azure compliance programmes, and it fits an existing Azure estate.
Where we are
- We say plainly that your documents are never used to train models. Microsoft’s Document Intelligence documentation does not answer that question either way — the only public assurance we could find is an employee’s reply on a forum.
- Uploads are deleted within the hour rather than after 24 hours.
- Our free tier reads the whole document. Azure’s free tier analyses only the first two pages of any request, which makes it hard to evaluate on real paperwork.
- One price instead of separate meters for Read, Layout, prebuilt models, custom models, add-ons and query fields — a prebuilt invoice with add-ons reaches $26 per 1,000 pages.
- No Azure subscription, resource group or SDK — an API key and one POST.
Side by side
| VisionParse | Azure AI Document Intelligence | |
|---|---|---|
| Text extraction price | $19/month for 2,000 pages — $9.50 per 1,000 | Read (plain text OCR) on the S0 pay-as-you-go tier: $1.50 per 1,000 pages for 0–1M pages, dropping to $0.60 per 1,000 pages above 1M pages. Note that this Read rate buys text only — Layout (tables, structure, selection marks) is billed at the $10 prebuilt rate, not this one.| S0 - Web/Container | Read | 0-1M pages - $1.50 per 1,000 pages<br>1M+ pages - $0.60 per 1,000 pages |source, checked 2026-08-08 |
| Structured field extraction | 1 AI credit a document; 250 included on the $19 plan | $10 per 1,000 pages for all prebuilt models — invoice, receipt, ID, W-2, 1098 tax forms, health insurance card, contract, general document AND Layout. Custom extraction and custom generative extraction are $30 per 1,000 pages; custom classification $3 per 1,000 pages. Add-ons cost extra: $6 per 1,000 pages for high resolution/font/formula, $10 per 1,000 pages for Query Fields. Custom neural model training is free for a total of 10 hours (not per month), then $3 per hour with a 30-minute minimum per job.| All Prebuilt Models: Document, Layout, Receipt, Invoice, ID, W-2, 1098 Tax forms, Health insurance card, Contract. | $10 per 1,000 pages |source, checked 2026-08-08 |
| Free tier | 100 pages a month with an account; 5 conversions a day with none | Free F0 tier: 500 pages per month, recurring monthly (not a time-limited trial), covering all document types. Severely constrained: only the first two pages of any request are analyzed, 4 MB max file size, 1 analyze transaction/second, no premium features and no Query Fields meter. Separately, a new Azure account gets a $200 credit to use within 30 days.| Free - Web/Container1 | All | 0 - 500 pages free per month | […] 1Does not support premium features, and does not include Query Meter.source, checked 2026-08-08 |
| Languages | 161 recognition languages, counted on the production host | 300 languages for printed text and 12 for handwriting (English, Chinese Simplified, French, German, Italian, Thai, Japanese, Korean, Portuguese, Spanish, Russian, Arabic) in the v4.0 Read model; the v4.0 Layout printed list is the same 300. The two are not the same list — the headline breadth is print-only. Counts are ours, from Microsoft's published tables; Microsoft publishes no headline number.The read model enables extraction and analysis of printed and handwritten text. […] The following table lists read model language support for extracting and analyzing **handwritten** text.source, checked 2026-08-08 |
| Where it runs | Hosted API, documents processed in Frankfurt, Germany | Runs in Azure; the resource is created in a region and documents are processed in that region. Microsoft's retail price API lists the core S0 page meters in 32 commercial Azure regions across the Americas, Europe, Middle East, Africa and Asia-Pacific (31 for Read — jioindiawest carries no Read meter), plus 2 Azure Government regions (US Gov Arizona, US Gov Virginia); 35 commercial regions carry at least one Document Intelligence meter. A genuine on-premises option exists: the same models ship as Docker containers for AKS, Azure Container Instances, Azure Stack or your own hardware, in connected (metered) or fully disconnected (offline, annual commitment) form. Pay-as-you-go container pricing matches cloud pricing.Recognize forms at the edge, on-premises, and in the cloud with container support. The portable architecture can be deployed directly to Azure Kubernetes Service (AKS) or Azure Container Instances, or to a Kubernetes cluster deployed to Azure Stack.source, checked 2026-08-08 |
| What happens to your documents | Uploads deleted within the hour on every plan; never used to train models | Retention: submitted documents and results are stored temporarily in Azure Storage in the same region and auto-deleted after 24 hours; a Delete Analyze Result API deletes them immediately. Training: NOT VERIFIED in product documentation — as of 2026-08-08 we checked the Document Intelligence privacy page (both the /azure/ai-foundry/ and /legal/cognitive-services/ URLs, which now serve identical content), the transparency note, the product FAQ's own "Security and privacy" section, and the Foundry Tools section of the Azure Product Terms. None of them says whether customer documents are used to train or improve Microsoft's models. However, a Microsoft employee answered exactly this question on Microsoft's own Q&A site in August 2024 — "Your data is your data and is not used to train or improve our models" — and the asker accepted that answer. That is a forum reply, not a product commitment, and the doc update the employee promised has still not appeared in the page's 07/28/2026 revision.**Deletes data**: The service stores submitted input data and analyze results for 24 hours after an analysis operation completes. Document Intelligence automatically deletes both after this retention period. To delete the data earlier, call the [**Delete Analyze Result**] API. This operation permanently deletes the submitted input data and analyze result associated with the request. This action applies to all models.source, checked 2026-08-08 |
What this page does not claim
We have never run a document through Azure AI Document Intelligence, so there is no accuracy comparison here and no chart showing us winning. Our own figures are measured and reproducible — the method is on the benchmark, including the cases where our default engine gets things wrong. Azure AI Document Intelligence's figures are theirs, quoted from their documentation with the date we read it.
Most comparison pages of this kind include an accuracy table. Ours cannot, honestly, so it does not.
Try it on your own documentSee pricing
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