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Overview

This tutorial walks you through building a production-ready invoice processing system with Documind. You’ll learn how to extract invoice data, handle reviews, and build a complete automation pipeline.

What You’ll Build

By the end of this tutorial, you’ll have:
  • A robust invoice extraction system
  • Automated review workflow handling
  • Error handling and retry logic
  • Batch processing capabilities
  • Cost optimization strategies

Prerequisites

  • Documind API key
  • Python 3.8+ or Node.js 16+
  • Basic understanding of REST APIs
  • Sample invoices (we’ll provide examples)

Step 1: Design the Invoice Schema

First, create a comprehensive schema for invoice data:
invoice_schema.json
Schema Design Tips:
  • Mark only critical fields as required (invoice_number, total)
  • Include descriptions for better extraction accuracy
  • Use proper data types (number for amounts, string for text)
  • Nest related data (vendor, customer) for better organization

Step 2: Create the Invoice Processor

Build a Python class to handle invoice processing:

Step 3: Handle Batch Processing

Process multiple invoices efficiently:

Step 4: Add Error Handling

Robust error handling for production:

Step 5: Validate and Store Results

Validate extraction results and store them:

Step 6: Build a Complete Pipeline

Put it all together:

Next Steps

Form Extraction

Learn to extract form data

Batch Processing

Scale to thousands of documents

Schema Design

Master schema design patterns

Error Handling

Build robust production systems

Complete Example Repository

Download the complete working example:
Production Tips:
  • Use environment variables for API keys
  • Implement proper logging and monitoring
  • Add database storage for results
  • Set up alerts for failed extractions
  • Monitor credit usage daily