Iteration Layer vs Google Document AI
Google Document AI extracts entities from processor-specific models — not general markdown from any document.
Why developers switch from Google Document AI
Document AI requires a GCP project, processor selection, and S3-equivalent storage before you get any text out.
Markdown from any document, one call
Google Document AI requires choosing a processor, configuring it in the GCP console, and handling async upload for larger files. We take any document and return clean markdown in a single synchronous call.
Image description included
When you send an image file, we return both OCR markdown and a natural language description of the image. Document AI returns entity blocks from a configured processor — no readable markdown, no image description.
No GCP account required
Google Document AI requires a GCP project, service accounts, enabled APIs, and billing configuration. Iteration Layer gives you a direct HTTP API with shared credits, EU processing, n8n, and MCP.
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 | Google Document AI |
|---|---|---|
| Markdown output |
Clean markdown
Returns well-structured markdown with preserved headings, tables, and lists from any document |
Entity blocks
Returns extracted entities from the configured processor — not human-readable markdown |
| Image description |
Yes
Returns a natural language description of image content alongside OCR markdown for image files |
No
Processor-based entity extraction with no semantic image description |
| Processor setup required |
No
Automatically handles any document type — no processor selection or setup |
Yes
Must choose and configure a specific processor type in the GCP console for each document type |
| 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 image files, with GCS upload required for async processing above 15 pages |
| GCS bucket dependency |
No
Accepts files directly via URL or upload with no intermediate storage step |
For large files
Async processing for files over 15 pages requires uploading to a GCS bucket first |
| GCP integration |
Standalone
Independent API with no cloud ecosystem dependency |
Deep
Integrates with BigQuery, Vertex AI, and Cloud Workflows for complex pipelines |
| EU hosting |
EU only
All processing happens exclusively on EU-hosted servers |
EU available
EU regions are available but the service is not restricted to EU-only processing |
| Pricing model |
Per page
Simple, predictable per-page pricing |
Per page
Per page with separate pricing per processor type and GCS storage costs for async |
| Infrastructure required |
None
Fully managed API with no deployment or infrastructure to manage |
None
Fully managed GCP service with no infrastructure to manage |
| GDPR / Data privacy |
Zero retention
No files or results stored beyond temporary 90-day logs |
GCP data policies
Subject to Google Cloud data processing terms with configurable retention policies |
| Data used for training |
Never
Your data is never used to train or improve AI models — guaranteed for all plans |
No
Google Cloud does not use customer data for model training under its Cloud terms |
Pricing
Start usage-based. Switch to a subscription when your volume becomes predictable.
Usage-based
Graduated pricing. Your effective rate decreases automatically as monthly usage grows.
- No monthly commitment
- Pay only for credits used
- Automatic volume discounts as usage grows
Predictable volume
Fixed recurring credit packs with lower effective credit prices for steady usage.
- Lower effective per-credit prices
- Fixed recurring credit packs
- Predictable monthly budget
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