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

说明与用途

使用 AWS Textract、Flask 和 Terraform 的 Genesys Cloud 自动 OCR 流水线，自动提取结构化文本，屏蔽 PII，并实时将数据注入 Architect 流程。

问题

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

结果

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.

工作流

• 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

证据

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.

来源

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

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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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