Iteration Layer vs Google Document AI
Google Document AI is built around GCP infrastructure — and comes with that ecosystem's complexity.
Why developers switch from Google Document AI
Document AI is full-featured, but requires a GCP project, service account, and storage bucket to get started.
Schema in, no processor selection needed
Google Document AI requires choosing a processor type (OCR, form parser, custom extractor) for each document type, then configuring it in the GCP console. We auto-select the right approach from your schema — no processor setup.
No GCS bucket dependency
Google's async processing (required above a certain file size) requires uploading to a GCS bucket first. We accept files directly — URL or base64 — with no intermediate storage step.
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 |
|---|---|---|
| Schema-defined extraction |
Yes
Define the fields you want in a schema and the API selects the right extraction approach automatically |
Processor-based
Requires choosing and configuring a specific processor type in the GCP console for each document type |
| Typed field support |
17 types
Choose from 17 typed schema fields including date, IBAN, currency, address, phone, email, and URL |
Processor-dependent
Available field types depend on which processor type is selected |
| Confidence scores |
Per field
Confidence score between 0 and 1 for every extracted schema field |
Per entity
Confidence scores provided per extracted entity |
| Source citations |
Yes
Verbatim source citation from the document for every extracted field |
No
No source citation linking extracted values back to document text |
| Multi-file support |
Up to 20 files
Process up to 20 files in a single API request with merged extraction results |
1 file
Each API request processes a single file |
| 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 |
| Training required |
No
Schema-based extraction works immediately without any training step |
For custom types
Custom document extractors require training on labelled example documents |
| 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 |
| OCR quality |
Benchmark-backed
OCR benchmark scored 0.93 across forms, invoices, scans, tables, charts, and photos |
Industry-leading
Best-in-class OCR for scanned documents and handwriting recognition |
| Pre-built processors |
Any document
Schema-based approach works with any document type without pre-built processors |
Specialized
Pre-built processors for US tax forms, identity documents, and other common types |
| 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 |
$0.033
1 credit per page |
Per page
Processor-specific pricing |
| 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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