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Google Document AI

Google Document AI is a cloud-based service that uses advanced machine learning to extract structured data from documents, enabling automated document processing and intelligent data extraction.

Overview​

The Robomotion Google Document AI package provides comprehensive integration with Google's Document AI API, enabling you to automatically extract and process data from various document types including PDFs, scanned documents, images, invoices, receipts, forms, and more.

Document AI uses optical character recognition (OCR) combined with machine learning to:

  • Extract text content from documents with high accuracy
  • Detect and extract tables with their structure preserved
  • Identify and extract form fields as key-value pairs
  • Process both digital and scanned documents
  • Handle multiple document formats and languages

Key Features​

Text Extraction​

  • OCR Technology: Accurate optical character recognition for scanned and image documents
  • Page Organization: Text organized by page with full document output
  • Multi-Format Support: PDF, PNG, JPG, TIFF, GIF, and more
  • Language Support: Supports 200+ languages with automatic detection
  • Layout Preservation: Maintains reading order from the original document

Table Extraction​

  • Structure Detection: Automatically detects table boundaries and structure
  • Header Recognition: Identifies column headers for proper data organization
  • Cell-Level Extraction: Extracts individual cell values with row/column mapping
  • Multi-Table Support: Handles multiple tables per page
  • Complex Layouts: Works with nested tables and merged cells

Form Processing​

  • Key-Value Detection: Identifies form fields and their corresponding values
  • Label Recognition: Recognizes common form labels (Name, Date, Amount, etc.)
  • Checkbox Support: Detects and extracts checkbox states
  • Multi-Page Forms: Processes forms spanning multiple pages
  • Custom Forms: Works with both standard and custom form layouts

Authentication Options​

The package requires Google Cloud Service Account credentials:

  1. Service Account Key: JSON credentials file from Google Cloud Console
  2. Required Permissions: Document AI API access enabled
  3. Processor Configuration: Pre-configured Document AI processor in your project

Getting Started​

  1. Create Processor: Set up a Document AI processor in Google Cloud Console
  2. Configure Credentials: Add Service Account credentials to Robomotion vault
  3. Select Node: Choose the appropriate extraction node (Text, Tables, or Key Values)
  4. Process Document: Provide document file path and processor details
  5. Use Results: Access extracted data through output variables

Common Use Cases​

Invoice Processing​

  • Extract invoice numbers, dates, amounts, and line items
  • Identify vendor information and payment terms
  • Process invoices from multiple vendors with varying formats
  • Automate accounts payable workflows

Receipt Digitization​

  • Extract merchant name, date, total amount, and line items
  • Process expense reports automatically
  • Categorize expenses for accounting systems
  • Archive digital copies with searchable text

Form Automation​

  • Extract data from application forms, surveys, and registrations
  • Process insurance claims and medical forms
  • Automate data entry from paper forms
  • Validate form completeness and accuracy

Contract Analysis​

  • Extract key terms, dates, and parties from contracts
  • Identify clauses and obligations
  • Compare contract versions
  • Build searchable contract databases

Document Digitization​

  • Convert paper archives to searchable digital documents
  • Extract structured data from historical records
  • Preserve document layout and formatting
  • Enable full-text search across document collections

Processor Types​

Google Document AI offers specialized processors for different use cases:

General Processors​

  • OCR Processor: Basic text extraction from any document
  • Form Parser: Generic form field extraction
  • Document OCR: Enhanced OCR with layout analysis

Specialized Processors​

  • Invoice Parser: Optimized for invoice data extraction
  • Receipt Parser: Specialized for receipt processing
  • US Driver License Parser: Extracts data from US driver licenses
  • W2 Parser: Processes W2 tax forms
  • Custom Processors: Train custom models for specific document types

Supported File Formats​

  • PDF: Portable Document Format (single and multi-page)
  • Images: PNG, JPG, JPEG, TIFF, GIF, BMP, WEBP
  • Maximum File Size: 20MB per document
  • Page Limit: Up to 15 pages per request

Best Practices​

Document Quality​

  • Use high-resolution scans (300 DPI or higher)
  • Ensure proper lighting for photographed documents
  • Avoid skewed or rotated images when possible
  • Use grayscale or color (not pure black and white) for best OCR results

Processor Selection​

  • Choose specialized processors for known document types
  • Use generic OCR processor for mixed document types
  • Consider creating custom processors for high-volume specific formats
  • Test with sample documents before processing large batches

Error Handling​

  • Implement retry logic for transient API errors
  • Validate extracted data against expected formats
  • Use confidence scores to identify low-quality extractions
  • Maintain original documents for manual review when needed

Cost Optimization​

  • Use appropriate processor types to avoid unnecessary features
  • Batch process documents when possible
  • Cache results to avoid reprocessing
  • Monitor quota usage in Google Cloud Console

Regional Availability​

Document AI processors are available in multiple regions:

  • us: United States (default)
  • eu: European Union
  • asia: Asia Pacific

Select the region closest to your data processing location for optimal performance and compliance with data residency requirements.

Available Nodes​