AI Document Processing with AWS Textract: A Real Case Study

A financial services team in Panama needed to extract data from thousands of loan packets every week. Manual review created backlogs and compliance risk.

Architecture at a glance

• Ingestion: Documents land in S3 with metadata tags for branch and product.
• Orchestration: Step Functions routes each file through Textract, custom business rules, and human review when confidence scores dip.
• APIs: A .NET 8 API exposes status, sends events to downstream systems, and writes structured records to DynamoDB.

Why Textract worked

1. Native table and form extraction reduced custom OCR code.
2. Managed scaling kept throughput stable during end-of-month peaks.
3. Built-in encryption and IAM policies satisfied auditors.

Lessons learned

• Create a clear fallback path for ambiguous fields—usually a short human-in-the-loop UI.
• Normalize outputs early to simplify analytics and compliance exports.
• Monitor throughput, error categories, and cost per document so finance teams stay aligned.

Automation only sticks when operations trust the data. With Textract, we cut processing time from days to hours while meeting the bank's audit requirements.