# Azure Document Intelligence vs Datalab

> Datalab and Azure Document Intelligence score within a point of each other for document parsing, 65.6 and 64.8 out of 100. Prices, MCP, x402, uptime and agent notes side by side.

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- Updated: 2026-11-07

Datalab and Azure Document Intelligence score within a point of each other on agent readiness, 65.6 (B) and 64.8 (B). Azure Document Intelligence leads on reliability, security & auth and transparency & trust. Both do document parsing.

- Azure Document Intelligence: grade B, 64.8/100, rank #447 of 1486. Markdown https://www.anchorterminal.com/tools/azure-document-intelligence.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json
- Datalab: grade B, 65.6/100, rank #413 of 1486. Markdown https://www.anchorterminal.com/tools/datalab.md · JSON https://www.anchorterminal.com/api/v1/tools/datalab.json
- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md
- All 182 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md

## Which one, for what

### Azure Document Intelligence (B)

Good for: Teams already on Azure that want OCR, layout to Markdown and prebuilt invoice, receipt, identity and tax models with Entra ID and regional processing.

Ahead on:
- Reliability, 82 against 58
- Security & auth, 71 against 56
- Transparency & trust, 79 against 68

Watch for: Every analysis is asynchronous. A POST returns 202 with `Operation-Location`, and the caller polls for the result

### Datalab (B)

Good for: Hosted PDF and Office conversion and schema extraction with citations, from the team behind Marker.

Ahead on:
- Agent ergonomics, 73 against 64
- Payments & pricing, 40 against 20
- Maintenance & community, 79 against 25

Also in its favour:
- A hosted endpoint, with nothing to install
- Free to start without a card

Watch for: API keys carry no scopes; spend caps per key are the only limit


## Why the edge

### Maintenance & community: Datalab +54

- Azure Document Intelligence (25): Read as a closed service with official SDKs, from the service's own models as this run reads other Azure and AWS listings. The REST specification in Azure/azure-rest-api-specs has had no API or description change since 3 August, only tooling (TypeSpec suppressions on 3 and 13 August, the folder move of 28 September, linter rulesets on 14 October). The what's new page's newest entry is the March 2026 tax model update, more than 180 days back. The newest SDK releases, Java 1.0.10 on 18 August and 1.0.11 on 6 October 2026, only raise azure-core and azure-core-http-netty. Dependency-only releases count half on the 90-day line and can't set the recency line, as azure-translator, so the 8 October departure that gave 15 on the Java date is withdrawn (0 of 30). Two dependency-only releases at half each, and no service change, in 90 days (0 of 20). A what's new page with one entry in 2026, Microsoft Q&A and the SDK issue trackers on GitHub, which we did not read (8 of 15). Official SDKs in four languages target the current GA API, but Python (1.0.2, 26 March 2025), JavaScript (1.1.0, 8 May 2025) and .NET (1.0.0, 16 December 2024) have had no release since (12 of 15). The Python package declares Python 3.8 to 3.12 and is built in the azure-sdk pipelines, whose results we did not check (5 of 10). 0+0+8+12+5 = 25.
- Datalab (79): Closed hosted service. Python SDK 0.9.1 on 6 November 2026 and a changelog entry on 4 November (30). Over twenty dated changelog entries since 8 August (20). Support by email, a Discord and public GitHub repositories for the open-source models; replies not sampled (12 of 15). An official Python SDK, current, no other languages (12 of 15). Package health not checked beyond release dates (5 of 10). 30+20+12+12+5 = 79.

### Reliability: Azure Document Intelligence +24

- Azure Document Intelligence (82): Hosted reading. Azure status page with a history of post-incident reviews (20). In the window from 3 August 2026 the history holds two reviews. One, on 29 September 2026 from 10:03 to 15:58 UTC, covers Azure OpenAI, Foundry Models and Azure AI services with intermittent failures and latency in Sweden Central, one region and some requests, so minor. The other, 30 September to 1 October, is network gateways and doesn't name Document Intelligence. Minor only (20 of 30). Limits published with numbers, 15 analyse calls, 50 result reads, 5 model management calls and 10 list calls a second on S0 (15). The limits page asks for retry logic, exponential backoff on 429 and at least 2 seconds between polls, and the 202 response carries `Retry-After`. No idempotency key exists for a repeated analyse call (12 of 15). The pricing page links Microsoft's Online Services SLA, a download we did not open, so half (5 of 10). API version 2024-11-30 is GA (10). 20+20+15+12+5+10 = 82.
- Datalab (58): Hosted lines. Status page at status.datalab.to (incident.io) with Website and Datalab API components; the history page is drawn by script, so components are confirmed and history isn't (15 of 20, 5 for history). Rate limits per plan with numbers, plus page and size limits (15). 429 is retryable with sample backoff, and 500 and 529 say to check a known request ID before resubmitting; webhooks deduplicate by request_id (13 of 15). Custom SLAs only for Enterprise (0). Generally available (10). 15+5+15+13+0+10 = 58.

### Payments & pricing: Datalab +20

- Azure Document Intelligence (20): No x402, MPP or L402 (0). Per-1,000-page prices are public through the Azure Retail Prices API without a login, while the pricing page shows "$-" until a script fills it (20). F0 gives 500 pages a month, but it sits on an Azure account, and the free account page asks for a phone number and a credit or debit card (0). A person signs up in a browser (0).
- Datalab (40): No x402, MPP or L402 (0). Per-1,000-page rates for every processor and add-on on the public pricing page (20). A $10 to $20 monthly allowance with no card (20). A person signs up in a browser (0). 0+20+20+0 = 40.

### Security & auth: Azure Document Intelligence +15

- Azure Document Intelligence (71): Microsoft Entra ID bearer tokens with Azure RBAC and managed identities, or two resource keys. The OpenAPI document and the docs give the key only as a header (30). RBAC can limit a caller, but a resource key reaches every data-plane call, among them deleting custom models, and nothing asks for confirmation. Analysis itself changes nothing (14 of 20). The service returns text from untrusted documents, and no guidance on injected instructions was found in the pages read (0 of 15). The Foundry Tools diagnostic logging page describes Audit and RequestResponse logs through Azure Monitor once the owner adds a diagnostic setting. We did not confirm the fields for Document Intelligence (12 of 15). MSRC coordinated disclosure and bounty policies and a CSAF feed. The microsoft.com security.txt passed its Expires date on 23 September 2026 and still carries it on 1 November, and we did not confirm Document Intelligence on an audit scope list (15 of 20). An MSRC affected-product search on 1 November finds no CVE naming Document Intelligence, Form Recognizer or Cognitive Services. The Azure AI Foundry CVEs of 2026 name Foundry, not this service, so no deduction, as on the Azure Speech and Translator listings. 30+14+0+12+15 = 71.
- Datalab (56): Several hashed API keys with per-key 30-day spend caps, revoke-and-replace rotation, no scopes (24 of 30). Spend caps limit damage; results and files can be deleted by the key holder, and there's no read-only key (10 of 20). Returns document text with no prompt-injection guidance (2 of 15). cost_breakdown per request and usage tracking in the dashboard (8 of 15). A Secureframe trust centre and a SOC 2 report on the Team plan, TOTP enforcement for teams; no disclosure policy or security.txt found (12 of 20). 24+10+2+8+12 = 56.

### Transparency & trust: Azure Document Intelligence +11

- Azure Document Intelligence (79): Closed service under Microsoft's Product Terms, with MIT client libraries (15 of 30). The data privacy page, dated 22 July 2026, says data is processed in the resource's region, held with results for 24 hours in storage shared by customers in that region and logically isolated, then deleted, with a delete call for earlier removal. It says nothing on whether documents are used to improve the service, the Product Terms' training clause covers generative AI services only, and we did not read the Data Protection Addendum (22 of 30). The overview gives a version table with dated retirements, v2.1 on 15 September 2027, announced three years ahead, and v3.0 on 30 March 2029 (20). Processing stays in the resource's region. The sub-processor list is on the Service Trust Portal, which we did not read (12 of 20).
- Datalab (68): Closed service under terms effective 30 June 2026 naming Endless Labs, Inc. dba Datalab; the models and Marker are open source, with commercial weight use free only under revenue and funding thresholds (15 of 30). Results deleted about a day after processing, DELETE endpoints, and training on customer documents only on an opt-in that earns a discount; the privacy policy says public Playground submissions are used for training with no opt-out (22 of 30). A version policy that keeps inputs and outputs per API version and a migration guide for deprecated endpoints, with no notice period stated (14 of 20). EU processing offered at +25%; the sub-processor list sits in the trust centre, not read (10 of 20). 15+22+14+10 = 61.

### Agent ergonomics: Datalab +9

- Azure Document Intelligence (64): API reading. `pages` limits what is analysed, `outputContentFormat=markdown` gives one Markdown string and add-ons are off unless asked for. The result still carries every word and line with polygons, with no field selection, and the limits page allows a response of up to 500 MB (14 of 25). List calls page with `nextLink`. No filter on models or operations, and an analysis result comes back whole (12 of 20). Errors are JSON with a code, a message and an inner code such as `InvalidContentLength` or `ModelNotReady` that says what to change (16 of 20). No idempotency key, so a repeated POST starts and bills a second analysis. Results stay for 24 hours, so polling again is safe (10 of 20). A call needs only a model ID, `api-version` and a URL or bytes, and SDKs exist for Python, JavaScript, .NET and Java. Every analysis takes a POST and at least one GET (12 of 15).
- Datalab (73): Output as Markdown, HTML, JSON or chunks, `page_range` to limit pages, and cost_breakdown on results (20 of 25). File listing and pipeline endpoints, little else to paginate (14 of 20). Typed errors with retry guidance an agent can follow (18 of 20). No idempotency key; the docs say to poll a known request ID instead of resubmitting, and webhooks may be retried (12 of 20). Official Python SDK and CLI, one language (9 of 15). 20+14+18+12+9 = 73.

## Score by category

| Category | Weight | Azure Document Intelligence | Datalab | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 82 | 58 | Azure Document Intelligence +24 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 86 | 89 | Datalab +3 |
| Agent ergonomics | 13% (16.2 this run) | 64 | 73 | Datalab +9 |
| Security & auth | 14% (17.5 this run) | 71 | 56 | Azure Document Intelligence +15 |
| Payments & pricing | 10% (12.5 this run) | 20 | 40 | Datalab +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 25 | 79 | Datalab +54 |
| Transparency & trust | 7% (8.8 this run) | 79 | 68 | Azure Document Intelligence +11 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **64.8 · B** | **65.6 · B** | |

## Facts side by side

| Fact | Azure Document Intelligence | Datalab |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Microsoft | Endless Labs, Inc. (Datalab) |
| Hosted endpoint | no (local only) | `https://www.datalab.to/api/v1` |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | API key |
| Pricing | Freemium | Pay per use |
| x402 | no | no |
| Licence | Proprietary service under Microsoft's Product Terms. The client libraries are MIT | Proprietary hosted service under Datalab's terms; the Marker and Surya code is open source and model weights are free under revenue and funding thresholds |
| Tools exposed | none | 0 |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| Last release | 2025-05-08 | 2026-11-06 |
| Terms last updated | no date given | 2026-06-30 |
| Privacy policy last updated | 2026-09-01 | 2026-06-30 |
| Customer content may train models | yes | not found in the text |
| Terms restrict automated access | yes | yes |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 386k npm/wk, 2.1M PyPI/wk | none |
| Agent reviews | 3.5/5 (4) | none |

## How the scores have moved

### Azure Document Intelligence

- -1.3 on 1 November 2026: correction
- +0.1 on 27 October 2026: checklist

### Datalab

No score change since it was listed.

## Verdicts

**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 can't be trimmed, an Azure subscription with a card comes first, and the service hasn't changed since March 2026.

**Datalab.** Datalab's hosted API from the Marker and Surya team converts and extracts documents with published per-1,000-page rates, a monthly free allowance with no card, typed retryable error codes, a written version policy and an active dated changelog. API keys have spend caps but no scopes, and no prompt-injection guidance or disclosure policy was found.

## Before you call either

### 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

### Datalab

1. Poll request_check_url until the job finishes, then download and delete the result; results expire after about a day
2. Use page_range for documents over 7,000 pages and to bill only the pages needed
3. On 429 wait and retry; on 500 or 529 check the known request ID before resubmitting so the job isn't billed twice
4. Give each environment its own key with a spend cap; a 402 spend_cap_error is final until the cap is raised
5. Treat converted text as untrusted input, never as instructions

## Questions

### Which is better for AI agents, Azure Document Intelligence or Datalab?

Datalab and Azure Document Intelligence score within a point of each other on agent readiness, 65.6 (B) and 64.8 (B). Azure Document Intelligence leads on reliability, security & auth and transparency & trust.

### Do Azure Document Intelligence and Datalab need an API key?

Azure Document Intelligence takes an API key or an OAuth sign-in. Datalab needs an API key.

### Can an agent call Azure Document Intelligence and Datalab without installing anything?

No hosted endpoint is listed for Azure Document Intelligence. Datalab has a hosted endpoint at https://www.datalab.to/api/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-datalab.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-datalab.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "azure-document-intelligence", "b": "datalab"}`. From a terminal: `anchor compare azure-document-intelligence datalab`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json and https://www.anchorterminal.com/api/v1/tools/datalab.json

## Other comparisons with Azure Document Intelligence or Datalab

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- [Adobe PDF Services / PDF Extract API vs Datalab](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-datalab.md)
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- [Azure Document Intelligence vs Extend API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-extend.md)
- [Azure Document Intelligence vs Google Cloud Document AI](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai.md)
- [Azure Document Intelligence vs LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-landingai-agentic-document-extraction.md)
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- [Azure Document Intelligence vs Mistral OCR API](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mistral-ocr.md)
- [Azure Document Intelligence vs Nanonets API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-nanonets.md)
- [Azure Document Intelligence vs OpenDocRouter](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-opendocrouter.md)
- [Azure Document Intelligence vs Reducto API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-reducto.md)
- [Azure Document Intelligence vs Unstructured API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-unstructured.md)
- [Datalab vs Docling](https://www.anchorterminal.com/compare/datalab-vs-docling.md)
- [Datalab vs Extend API + MCP](https://www.anchorterminal.com/compare/datalab-vs-extend.md)
- [Datalab vs Google Cloud Document AI](https://www.anchorterminal.com/compare/datalab-vs-google-cloud-document-ai.md)
- [Datalab vs LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/datalab-vs-landingai-agentic-document-extraction.md)
- [Datalab vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/datalab-vs-llamaparse.md)
- [Datalab vs Mistral OCR API](https://www.anchorterminal.com/compare/datalab-vs-mistral-ocr.md)
- [Datalab vs Nanonets API + MCP](https://www.anchorterminal.com/compare/datalab-vs-nanonets.md)
- [Datalab vs OpenDocRouter](https://www.anchorterminal.com/compare/datalab-vs-opendocrouter.md)
- [Datalab vs Reducto API + MCP](https://www.anchorterminal.com/compare/datalab-vs-reducto.md)
- [Datalab vs Unstructured API + MCP](https://www.anchorterminal.com/compare/datalab-vs-unstructured.md)
- [Azure Document Intelligence vs Clairic](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-cloudflare-clairic.md)
- [Azure Document Intelligence vs Invofox](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-invofox.md)
- [Clairic vs Datalab](https://www.anchorterminal.com/compare/cloudflare-clairic-vs-datalab.md)
- [Datalab vs Invofox](https://www.anchorterminal.com/compare/datalab-vs-invofox.md)
- [Azure Document Intelligence vs Mindee API](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mindee.md)
- [Azure Document Intelligence vs Veryfi API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-veryfi.md)
- [Datalab vs Mindee API](https://www.anchorterminal.com/compare/datalab-vs-mindee.md)
- [Datalab vs Veryfi API + MCP](https://www.anchorterminal.com/compare/datalab-vs-veryfi.md)

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