How to Build an Intelligent Document Processing System on AWS Cloud
End-to-end automated document classification and PII extraction pipeline using AI.
1Project Objective
This system automates insurance FOI requests, achieving 90% efficiency gain over manual processing. It extracts PII from PDFs, Word docs, and ID card images using AI, significantly reducing human intervention in document review workflows.
2System Architecture
Built on AWS services, the solution integrates Gmail API, Lambda functions, Textract OCR, and Bedrock AI models. EventBridge triggers daily automated runs, while encrypted PDF outputs ensure secure data delivery to requestors.
3Data Pipeline
Attorney-submitted email attachments get processed in S3 buckets. After Textract performs OCR, Claude AI classifies document types and extracts fields. Human-in-the-loop verification provides final quality control.
4Privacy Management
PII data remains encrypted via AWS Secrets Manager. Documents progress through raw, textract, and audit folders, with unrecognized files quarantined. IAM policies enforce least-privilege access throughout the workflow.
5OCR Integration
Amazon Textract accurately reads unstructured text from passports, licenses, and statements. The AI model processes these outputs to extract PII like addresses and birth dates into structured JSON format.
6AI Classification
Bedrock's Claude Sonnet model identifies document types (passports, bills etc.) with 98% accuracy. Careful prompt engineering minimizes false positives while handling variations in international ID formats.
7Workflow Automation
Step Functions orchestrates Lambda executions with state management. Failed processes trigger automatic admin alerts, while CloudWatch retains comprehensive audit logs for compliance purposes.
8Gmail Integration
OAuth 2.0 securely accesses email attachments labeled 'DocumentProcessing'. The system scales to handle 10,000+ daily emails with built-in spam filtering and parallel processing capabilities.
9Security Layers
IAM policies apply principle of least privilege. S3 buckets use encryption-at-rest, while result PDFs employ AES-256 encryption with passwords delivered separately. VPC endpoints protect data in transit.
10Cost Optimization
Spot instances and Lambda's pay-per-use model keep monthly costs under $50. Textract and Bedrock charge per page processed, making the solution economical for mid-volume document workloads.
11Scalability
The architecture processes 100+ documents concurrently using S3 triggers and DynamoDB for transaction management. Auto-scaling handles peak periods without manual intervention.
12Industry Applications
This template adapts to banking KYC, healthcare records, and government FOI systems. Built-in audit trails address GDPR compliance needs, positioning AI document automation as the new operational standard.
Original article: Towards Data Science — Bulut Üzerinde Akıllı Belge İşleme Sistemi Kurma Rehberi