LlamaParse turns documents into clean data for AI apps, with a large developer community. 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.
Documents must stay on your own servers, even without internet.
Choose LlamaParse if
Your engineers build AI search or agents and already use LlamaIndex.
You want to start cheap and pay by credit.
A managed cloud in North America or the EU meets your data policy.
In short
→In LlamaExtract you pick a tier, not a model, and the models are not named. Documind has three AI models from different families read the same value, and they must agree before it is approved.
→LlamaExtract confidence is opt-in, and its docs say a score of 0.8 does not always mean an 80% chance of being right.
→Documind reads print and handwriting in many languages. It checks tax IDs and IBANs by check digit, plus HS codes and container numbers. Built-in ID checks are not listed for LlamaParse.
→LlamaParse starts cheap: 1,000 credits cost $1.25, and the Free plan includes 10,000 credits.
At a glance
Documind and LlamaParse compared by capability. LlamaParse facts come from its public pages, checked on 12 October 2026. Each LlamaParse cell links to its source.
Capability
Documind
LlamaParse
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.
"Parse transforms messy documents into AI-ready data at scale." Parse, Extract and Index, from the team behind the LlamaIndex framework.
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
You choose an extraction tier (cost_effective, agentic, agentic_plus, turbo). The models behind each tier are not named. An agreement rule between models is not listed.
Open-weight models from three different families, on your servers.
Partial
Managed service: models are chosen by LlamaIndex. Self-hosted: LLM calls go from your cluster to outside providers with your own keys. Local open-weight models are not listed.
Managed SaaS, single-tenant SaaS, your own cloud (BYOC) or self-hosted. Self-hosting is on Enterprise plans, with password-protected docs. Air-gapped is not listed.
In LlamaExtract you choose a tier, and the models behind it are not named. Its confidence is opt-in and not fully calibrated. Documind has three AI models from different families read the same value. If they do not agree, a person decides.
In LlamaParse's words
“Calibration varies by tier and version, so a score of 0.8 does not always mean an 80% probability of correctness.”
LlamaParse turns documents into data for AI apps. Your team builds the checks and the next steps. Documind checks tax ID and IBAN check digits, HS code formats and container numbers. A failed check blocks the value. Then it writes the result to your system.
Self-hosted LlamaParse sends AI calls from your cluster to outside providers. Air-gapped use is not listed. Documind runs on your servers, even without internet, on AI models you own.
In LlamaParse's words
“All LLM calls go directly from your cluster to providers using your own API keys and contracts.”
LlamaParse is a strong choice for developers who feed documents into AI apps. It has a large community, clear credit pricing and a low entry price. Extract returns citations with page and box. If a managed cloud fits your policy and you build your own review steps, LlamaParse is quick to start.
Your engineers build AI search or agents and already use LlamaIndex.
You want to start cheap and pay by credit.
A managed cloud in North America or the EU meets your data policy.
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.
Documents must stay on your own servers, even without internet.
Document-type fit
LlamaParse turns many file types into Markdown and fields for AI apps. 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
LlamaParse
1,000 credits = $1.25. Free: $0 with 10,000 credits. Starter: $50 per month with 40,000 credits, pay as you go up to 400,000. Pro: $500 per month with 400,000 credits. Enterprise: custom. Parse uses 1 (Fast), 3 (Cost-effective), 10 (Agentic) or 45 (Agentic Plus) credits per page. Extract Agentic uses 25 credits per page with its default parse, which is about $0.031 per page (our calculation). USD list prices, checked 12 October 2026. Source: LlamaIndex: Pricing, checked on 12 October 2026 (opens in new tab)
How to switch
Move from LlamaParse 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 LlamaExtract schema. Documind drafts the steps and the checks, and you approve them.
STEP 3
Run an evaluation set
The evaluation agent tests the workflow on documents you have already checked. You see the score before you go live.
Frequently asked questions
What is LlamaParse?
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LlamaParse is a hosted platform from LlamaIndex. It parses documents into Markdown and pulls out fields for AI apps. The LlamaIndex framework is open source, but LlamaParse is a paid service.
Does LlamaParse give confidence scores?
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Yes, as an opt-in option in Extract. Its docs say calibration varies by tier and version, so 0.8 does not always mean an 80% chance of being right. Documind has three AI models from different families read each value, and they must agree.
Does LlamaParse read many languages and handwriting?
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LlamaParse claims more than 100 languages, and its product page names handwriting. Test your own samples. Documind reads print and handwriting in many languages, with tax ID, IBAN and HS code checks built in.
Can LlamaParse run on-premises or air-gapped?
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Self-hosting is available on Enterprise plans, and its setup docs are password-protected. AI calls go from your cluster to outside providers. Air-gapped use is not listed. Documind runs on your servers, even without internet.
How much does LlamaParse cost?
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1,000 credits cost $1.25. Plans are Free (10,000 credits), Starter ($50 per month) and Pro ($500 per month). Parse uses 1 to 45 credits per page. 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.
Does LlamaParse show where each value came from?
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Yes. With citations turned on, Extract returns the page number, matching text and box for each field. Documind does this too. The difference is how a value gets approved: Documind needs three AI models to agree first.
Map your process with us. Go live in the demo.
We look at how your team handles this work today. Then we put your first workflow live in the demo, on your own content and systems.