Iteration Layer vs DocuPipe
DocuPipe is a structured extraction platform — it outputs JSON fields, not clean markdown for LLM pipelines.
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Why developers switch from DocuPipe
DocuPipe extracts structured fields from documents — it doesn't produce clean, readable markdown.
Clean markdown, not structured fields
DocuPipe outputs structured JSON matching a schema. If you need clean, readable markdown for LLM context, RAG pipelines, or human review, you need to convert that structured output yourself. We return well-formatted markdown directly.
Image description included
When you send an image file, we return both OCR markdown and a natural language description of the image content — what the photo shows, what the chart communicates. DocuPipe returns field-level extraction only.
EU hosting with GDPR compliance
DocuPipe is US-based with no EU cloud hosting option. We process all documents on EU servers with zero data retention and a Data Processing Agreement available for every customer.
Feature-by-feature comparison
We went through the docs so you don't have to. Here's how every feature compares — including the ones where we're not the better choice.
| Feature | Iteration Layer | DocuPipe |
|---|---|---|
| Markdown output |
Clean markdown
Returns well-structured markdown with preserved headings, tables, and lists from any document |
Structured JSON
Outputs structured JSON fields matching a schema — not human-readable markdown of the full document |
| Image description |
Yes
Returns a natural language description of image content alongside OCR markdown for image files |
No
Field-based extraction with no semantic description of image content |
| Supported input formats |
40+ formats
Process 40+ formats — PDF, Office, EPUB, RTF, LaTeX, email, Jupyter, images, and more — in a single API endpoint |
PDF, images
Supports PDF and scanned document images |
| Table preservation |
Markdown tables
Tables are extracted and rendered as clean markdown table syntax |
Structured data
Tables extracted as structured data fields, not markdown table syntax |
| MCP server |
Yes
MCP server available for integration with AI agents and assistants |
No
No MCP server available for AI agent integration |
| Document classification |
Not applicable
Markdown conversion does not require document classification |
Built-in
Built-in document classification to categorize documents before extraction |
| Human review UI |
Not applicable
Markdown output needs no confidence-based review routing |
Built-in
Built-in visual review interface with source highlighting |
| EU hosting |
EU only
All processing happens exclusively on EU-hosted servers |
US only
US-based cloud hosting only — on-premises deployment available on Enterprise plans |
| Pricing model |
Per page
Simple, predictable per-page pricing |
Credits per page
3 credits per page with monthly plans ranging from free to $499/month |
| Infrastructure required |
None
Fully managed API with no deployment or infrastructure to manage |
None
Fully managed cloud API with no infrastructure to manage |
| GDPR / Data privacy |
Zero retention
No files or results stored beyond temporary 90-day logs |
US-based processing
Documents processed on US infrastructure — on-premises option available for Enterprise |
| Data used for training |
Never
Your data is never used to train or improve AI models — guaranteed for all plans |
Not documented
No public policy on whether customer data is used for model training |
Pricing
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Developer
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Still evaluating?
See how we compare — and where the competition still wins. Choosing the right tool shouldn't require a week of research.
Reducto
Reducto outputs markdown from US servers and charges per page — without an image description field.
LlamaParse
LlamaParse is US-based and per-page — and doesn't describe image content.
Mistral OCR
Mistral has best-in-class OCR and returns markdown, but doesn't describe image content and processes files from US servers.
Nanonets
Nanonets DocStrange outputs markdown, but has no image descriptions and no EU hosting option.
Unstructured
Unstructured is built for ETL pipelines and RAG ingestion — not a simple document-to-markdown API.
AWS Textract
Textract returns raw strings and bounding boxes — not a markdown document ready to read or embed.
Azure Document Intelligence
Azure outputs model-specific field values, not clean markdown — and requires model selection or training first.
Google Document AI
Document AI requires a GCP project, processor selection, and S3-equivalent storage before you get any text out.
OlmOCR
OlmOCR requires a GPU, only supports English, and intentionally strips headers and footers.
PaddleOCR
PaddleOCR outputs markdown, but requires the PaddlePaddle framework and self-hosted infrastructure.
Tesseract
Tesseract outputs raw text — no headings, no tables, no document structure preserved.
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