Datalab builds strong open-weight OCR models and a developer API. Documind automates the whole content workflow. Three different AI models read each value and must agree, then the result goes into your systems.
A value must be approved by three AI models that agree, not by one model's confidence score.
You need tax IDs, IBANs and HS codes checked before a value is approved.
Your team needs a ready review screen, not only an API.
Choose Datalab if
Your engineers want open-weight OCR models to run and tune themselves.
You need cheap, high-volume conversion of documents to Markdown or JSON.
You plan to build your own review screen and business rules.
In short
→Datalab's Extract can run a verification pass with its own models. Documind has three AI models from different families read the same value, and they must agree before it is approved.
→Datalab publishes its own 43-language OCR benchmark. Documind reads many languages too, and it checks what it reads: tax IDs and IBANs by check digit, HS codes and container numbers.
→Both can run without internet. Datalab's model weights are free for commercial use only below $2M (Chandra) or $5M (Marker and Surya) in revenue or funding.
→Datalab is an API and a set of models. A review screen for people is not listed; Documind includes one.
At a glance
Documind and Datalab compared by capability. Datalab facts come from its public pages, checked on 12 October 2026. Each Datalab cell links to its source.
Capability
Documind
Datalab
Overview
Positioning
Enterprise content workflow automation. Three AI models from different families read every value and must agree before it is approved. Tax ID, IBAN and HS code checks are built in.
"High-precision document intelligence." A hosted API (Convert, Extract, Segment, Eval, Pipelines) and its own open-weight models: Chandra, Marker and Surya.
Three models from different families read the same content. A value is approved only when all three agree and no rule check fails.
Not published
Balanced and accurate modes run "independent verification" with per-field reasoning. The docs do not describe it as a check by other model families or an approval rule.
Four separate checks per value: can it be read, was it read right, do the other models agree, do the rules pass.
Partial
Per-field score from 1 to 5, in beta and only in fast mode. Turbo, balanced and accurate modes return no numeric confidence. Convert gives a page-quality score.
Runs inside Documind on your servers, on AI models you own.
Code: Apache 2.0. Weights: modified OpenRAIL-M. Free for commercial use below $2M (Chandra) or $5M (Marker, Surya) in revenue or funding; above that, a paid licence.
Three AI models must agree, not one family checking itself
Datalab's verification runs inside its own extraction modes. Its docs do not say other model families check the value. Documind has three AI models from different families read the same value. If they do not agree, a person decides.
In Datalab's words
“Extraction with independent verification, per-field reasoning, and citations.”
Datalab reads many languages well on its own benchmark. Documind also checks what it reads. Tax ID and IBAN check digits, HS code formats and container numbers are checked. A failed check blocks the value.
Datalab gives a numeric score only in fast mode, and it is in beta. A review screen is not listed. Documind scores every value with four checks and sends unsure ones to a person, with the reason.
Datalab is a strong choice for engineering teams that want open-weight OCR models. Its results on its own 43-language benchmark are good. Prices are low and published, and it can run without internet. If you will build the review screen and the rules yourself, Datalab gives you strong parts.
Your engineers want open-weight OCR models to run and tune themselves.
You need cheap, high-volume conversion of documents to Markdown or JSON.
You plan to build your own review screen and business rules.
When to choose Documind
Choose Documind when a wrong value is costly. Three different AI models read each value and must agree before it is approved. Built-in ID checks can block a value. Your team gets a review screen, the result goes into your systems, and Documind runs on your own servers.
A value must be approved by three AI models that agree, not by one model's confidence score.
You need tax IDs, IBANs and HS codes checked before a value is approved.
Your team needs a ready review screen, not only an API.
Document-type fit
Datalab turns any document into clean text and fields, in many languages. Documind is built for business and trade documents: invoices, e-invoices, delivery notes, customs packets, LC sets and handwritten forms. It checks local tax IDs, IBANs and HS codes before a value is approved.
Free Starter plan with 1,000 credits a week. Enterprise pricing on request. See /pricing
Datalab
Free: $0 per month with a $20 usage allowance (work email) or $10 (personal email). Team: $400 per month including $400 of usage. Enterprise: custom, with VPC or air-gapped deployment. Per 1,000 pages: Convert $4 (fast/balanced) or $10 (accurate); Extract $6 (turbo/fast), $15 (balanced) or $20 (accurate), plus fees. EU processing costs 1.25 times as much. USD list prices, checked 12 October 2026. Source: Datalab: Pricing, checked on 12 October 2026 (opens in new tab)
How to switch
Move from Datalab in three steps
You can run both systems side by side until the results satisfy you.
STEP 1
Connect your source
Point an inbox (IMAP), SFTP folder or S3 bucket at Documind, or send documents through the REST API from your code.
STEP 2
Import your schema
Start from your Datalab JSON schema. Documind drafts the steps and the checks, and you approve them.
STEP 3
Run an evaluation set
Use documents you already checked as ground truth. The report shows the weakest fields before you go live.
Frequently asked questions
What is Datalab?
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Datalab trains document AI models and sells a hosted API. Its models are Chandra, Marker and Surya. The API converts documents to text and pulls out fields.
Is Datalab open source?
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The code is Apache 2.0. The model weights use a modified OpenRAIL-M licence. Commercial use is free below $2M (Chandra) or $5M (Marker and Surya) in revenue or funding. Above that, you need a paid licence.
Does Datalab read many languages and handwriting?
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Yes. Datalab's own benchmark covers 43 languages, and its README claims "Excellent handwriting support". Built-in tax ID or HS code checks are not listed on the pages we read. Documind reads many languages, including handwriting, and checks tax IDs, IBANs and HS codes.
Does Datalab give a confidence score?
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Datalab gives a per-field score from 1 to 5 in fast mode, in beta. Turbo, balanced and accurate modes return no numeric score. Documind scores every value with four separate checks.
Can Datalab run air-gapped?
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Yes. Datalab Enterprise runs on-prem and air-gapped with full model weights. Documind also runs on your servers without internet.
How much does Datalab cost?
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Free includes a $20 monthly allowance with a work email. Team is $400 per month. Extract costs $6 to $20 per 1,000 pages. These are USD list prices, checked on 12 October 2026. Documind has a free Starter plan with 1,000 credits a week. Enterprise pricing is on request.
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