Extract Structured Data - Quick Start

Turn any documents into organized data tables. Extract invoices, receipts, forms into structured information.

Instead of just converting text, extract specific information into organized tables:

Before (OCR): Raw text document
After (Structured): Organized data table with columns and rows

Invoice → Data Table:

Receipt → Expense Data:

Perfect for beginners

1. Upload 1-2 sample documents
2. Describe what data you want: "Extract item names, quantities, and prices from invoices"
3. AI creates the schema automatically
4. Review and adjust if needed

Example prompt:

"Extract customer name, invoice date, line items with descriptions and amounts, and total from these invoices"

Quick setup for common documents

Choose from pre-built schemas:

• Invoice Template - Items, quantities, prices, totals
• Receipt Template - Date, merchant, amount, category
• Form Template - Name, email, phone, address
• Business Card - Name, title, company, contact info

Full control for custom needs

Use the visual schema editor:

• Add fields with drag-and-drop
• Set field types (text, number, date)
• Configure validation rules
• Preview with sample data

Accounting & Finance:

• Invoice processing
• Expense report automation
• Receipt digitization
• Tax document organization

HR & Administration:

• Resume parsing
• Form processing
• Document archiving
• Contact management

E-commerce:

• Product catalog creation
• Inventory management
• Order processing
• Customer data extraction

Restaurants:

Receipt → Expense Tracking
Date | Vendor | Category | Amount | Tax
 

Real Estate:

Property Docs → Listing Data
Address | Bedrooms | Price | Features
 

Healthcare:

Forms → Patient Records
Name | DOB | Insurance | Conditions
 

1. Project Setup (one-time)

   • Create project
   • Design or choose schema
   • Test with sample documents

2. Document Upload

   • Drag and drop files
   • Batch upload supported
   • Multiple formats (PDF, images)

3. AI Extraction

   • Automatic data extraction
   • Schema-based field mapping
   • Confidence scoring

4. Review & Edit

   • Check extracted data
   • Correct any errors
   • Validate completeness

5. Export & Use

   • Download as CSV/Excel/JSON
   • API access for integrations
   • Connect to business systems

Structured extraction costs:

• Schema creation: 0.5 credits per page (one-time)
• Schema updates: 0.1 credits per change/pre page
• Data extraction: 1 credit per page processed

Example:

• Create invoice schema with 2 sample pages = 1 credits
• Update schema created above 3 times to meet your needs = 0.6 credits
• Then you process 100 invoices = 100 credits
• Total = 101.6 credits

• Let AI design your schema - Describe what you want to extract. And then refine the schema based on the results.
• Use clear names - Use terms from your documents, e.g., "Invoice Date" not "Date1"
• Set proper types - Number for amounts, Date for dates
• Test thoroughly - Test with sample documents before processing a batch of documents.
• Reuse schema - You can reuse the schema that you created for the same type of documents in different projects.

• Good quality - Clear, high-resolution scans.
• Complete documents - Include all relevant sections you wanna extract.

• Review extractions - Check first few documents carefully.
• Refine schema - Adjust based on results.

Ready to extract structured data?

Transform your documents into actionable data! Start your first project now.