How I Built an Automated OCR Pipeline for Genesys Cloud using AWS Textract, Flask & Terraform

Description and use

An automated OCR pipeline for Genesys Cloud that uses AWS Textract, Flask, and Terraform to extract structured text, mask PII, and inject data into Architect flows in real time.

Problem

End‑users send documents via Web Chat or Email and agents must manually transcribe data, causing delays.

Outcome

Zero‑maintenance, zero‑fixed‑cost OCR pipeline that processes multi‑page PDFs and images, masks SSNs and credit cards, and delivers data to Genesys Cloud in under 5 minutes of deployment.

Workflow

• Upload attachment in Chat/Email/Flow → Genesys sends HTTPS request with document URL → AWS App Runner hosts Python Flask microservice → In‑memory split and pre‑processing → AWS Textract performs OCR → Regex PII redaction → Return structured payload to Genesys Agent/Interaction Scope

Evidence

Genesys Cloud OCR Blueprint— a production‑ready, zero‑maintenance pipeline that automatically extracts structured text, masks sensitive PII (SSNs, credit cards), and injects the parsed data directly into Genesys Architect Flows or Agent Scripts in real time.

Source

AWS App Runner + Python Flask: Scales down to zero when idle—costing around ~$5/month for low-to-medium enterprise workloads.

Source

Automated PII Masking: Built-in regex filters detect and mask Social Security Numbers (SSNs) and Credit Card numbers prior to returning payloads.

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