🔍 Free n8n Workflow
Free AI Document Extraction Automation
Turn any document into structured data in seconds. This workflow uses AI vision and language models to extract information from contracts, receipts, invoices, forms, and any document type automatically.
What This Workflow Does
Everything included in this n8n automation template:
- Automatic document detection from email attachments or cloud folders
- AI vision processing for scanned documents, images, and PDFs
- Intelligent field extraction for dates, amounts, names, and custom fields
- Structured JSON output ready for CRM, database, or spreadsheet integration
- Confidence scoring with human review queue for uncertain extractions
- Multi-language support with automatic language detection
Frequently Asked Questions
What types of documents can this process?
The workflow handles contracts, invoices, receipts, forms, ID documents, bank statements, medical records, and virtually any document type. It works with PDFs, scanned images, photos, and digital documents. The AI adapts to your specific document formats.
How accurate is the AI extraction?
Modern AI vision models achieve 90-98% accuracy on common document types. The workflow includes confidence scoring—high-confidence extractions process automatically while uncertain ones route to a review queue. Accuracy improves as the AI learns your document patterns.
Which AI models does this use?
The workflow supports OpenAI GPT-4 Vision, Claude, and Google Gemini for document analysis. You choose based on your existing subscriptions and accuracy requirements. All models are accessed through n8n's native AI nodes.
Can I define custom fields to extract?
Yes. You specify exactly which fields you need extracted—standard fields like dates and amounts, plus custom fields specific to your documents. The AI uses your field definitions to structure the output consistently across all documents.
How does this differ from OCR-only solutions?
Traditional OCR extracts raw text without understanding context. This workflow uses AI to understand document structure, identify field relationships, and extract meaningful data. It knows that '01/15/2025' in the top right is likely the invoice date, not a random number.
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