Klaaro vs Claude

Can I extract data from documents in Claude?

The short answer is: you can, but you shouldn't. Agentic Document Processing (ADP) solutions like Klaaro are built for this job and handle it efficiently. Stop wasting time and tokens in Claude, and find a workflow that automates your document processes.

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Klaaro versus Claude for extracting structured data from documents

Key insights

For an extraction of few short and simple documents of one type, using Claude directly in the chat is your fastest option.
For recurring, high-volume, long or varied documents, a dedicated ADP like Klaaro is more accurate and token-efficient.
To avoid the tedious uploading and downloading of documents manually, Klaaro plugs neatly into your stack via n8n, API, MCP & SDKs.

Klaaro scales with your document load

With Klaaro, you don't need to type a new prompt for every new document type you want to extract structured data from. Tokens per page remain stable, no matter if your document has 1 or 1,000 pages.

Pages processed

110501005001,00010,000

Time until result

Claude (Sonnet 5)

21 min

ADP solution (Klaaro)

4 min

1 min5 min10 min30 min1.0 h1.5 h2.0 h

Spendings

Claude (Sonnet 5)

30.50€

ADP solution (Klaaro)

6.10€

1.00€5.00€10.00€50.00€100.00€500.00€5,000.00€

Illustrative estimates for orientation — your real numbers depend on document length and complexity.

When to use Claude

Using Claude makes sense when you process one short document every now and again

Best for
ADP solutions like
Klaaro
Repeatable, high-volume document processing
Claude (chat interface / API)
One-off document questions and analysis
Setup per document type
ADP solutions like
Klaaro
Schema is detected or reused automatically
Claude (chat interface / API)
You write and maintain a prompt for each type
Cost model
ADP solutions like
Klaaro
Per page, predictable at any volume
Claude (chat interface / API)
Paid plans include token limits. Long documents hit these limits fast
Model routing
ADP solutions like
Klaaro
Right model per step, per document region
Claude (chat interface / API)
One model for the whole job
Validation
ADP solutions like
Klaaro
Schema enforcement and confidence flags
Claude (chat interface / API)
None — you trust it or review manually
Long documents
ADP solutions like
Klaaro
Split and chunked with context preserved
Claude (chat interface / API)
Middle pages get read least carefully, higher risk of hallucinations
Low-quality scans or phone photos
ADP solutions like
Klaaro
Preprocessed before extraction
Claude (chat interface / API)
Inconsistent results run to run
Multi-document PDFs
ADP solutions like
Klaaro
Auto-split into separate records
Claude (chat interface / API)
No splitting, therefore understood as one document type
Integration
ADP solutions like
Klaaro
n8n node, MCP server, API, TS & Python SDKs
Claude (chat interface / API)
Raw API — you build the pipeline
Data residency
ADP solutions like
Klaaro
EU hosting, GDPR, no training on your data
Claude (chat interface / API)
Depends on your API configuration

	ADP solutions likeKlaaro	Claude (chat interface / API)
Best for	Repeatable, high-volume document processing	One-off document questions and analysis
Setup per document type	Schema is detected or reused automatically	You write and maintain a prompt for each type
Cost model	Per page, predictable at any volume	Paid plans include token limits. Long documents hit these limits fast
Model routing	Right model per step, per document region	One model for the whole job
Validation	Schema enforcement and confidence flags	None — you trust it or review manually
Long documents	Split and chunked with context preserved	Middle pages get read least carefully, higher risk of hallucinations
Low-quality scans or phone photos	Preprocessed before extraction	Inconsistent results run to run
Multi-document PDFs	Auto-split into separate records	No splitting, therefore understood as one document type
Integration	n8n node, MCP server, API, TS & Python SDKs	Raw API — you build the pipeline
Data residency	EU hosting, GDPR, no training on your data	Depends on your API configuration

The manual Claude workflow

The tedious workflow of processing a new document type in Claude's chat

Download document (mail, DMS, local etc.) and upload in Claude

Write long prompt to instruct which data you need from the doc

Demand the format in which you need the data (JSON, .xlsx, CSV…)

Manually check extraction for mistakes or hallucinations

Download structured data and upload in your ERP, SAP etc.

Wonder why you hit your usage limit

Download document (mail, DMS, local etc.) and upload in Claude

Write long prompt to instruct which data you need from the doc

Demand the format in which you need the data (JSON, .xlsx, CSV…)

Manually check extraction for mistakes or hallucinations

Download structured data and upload in your ERP, SAP etc.

Wonder why you hit your usage limit

Exceptions

To be honest, not all document processing workflows need a dedicated solution. If you are reading one contract and want to reason about it, a strong model in a chat window is the fastest tool.

You process a very limited number of documents (1–5 per week)
These documents are relatively short (about 1–3 pages)
The document type hardly varies (i.e. you process predominantly invoices or quotations)
The documents are not very complex (no nested tables, mostly English, not handwritten etc.)
Manual fact-checking takes a minute or two

The Klaaro ADP workflow

If you need accuracy & scalability in extractions, you might want to try Klaaro

ADPs like Klaaro are for the other case: you process varying document types of different lengths, new documents come in every day, and you have no room for wrong numbers or hallucinations. If you want a seamless workflow out of the box that automatically ingests your documents when they arrive, an ADP is the better fit.

Preprocessing first

Every document is preprocessed and, where needed, split and classified before a single field is read.

Token-efficient pipeline

Klaaro splits the entire extraction into its original steps and uses the most efficient model for each of them.

Auto-generated schema

For every new document class, Klaaro auto-generates a new schema as basis for extraction. Refine the schema if needed.

Every page, equal attention

Long documents are chunked so page 27 gets the same attention as page 1.

Quality through validation rules

Human-in-the-loop as an integrated feature, not a manual task. Set deterministic validation rules to ensure quality, forcing AI to flag unknown fields.

Works in your ecosystem

Klaaro exports extracted data to your ERP automatically. We have official nodes on n8n, but you can also use our powerful API that includes an MCP server and multiple SDKs.

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FAQ

Frequently Asked Questions

Everything you need to know about Klaaro and how it works.

Throw the documents Claude has struggled with at me. I'll show you our results.

If you think Claude might not be your most efficient solution to automatically process and extract documents, book your 20-minute slot and let's hop on a personal call. Or try it out for free, no credit card required.