Building a Document Processing Pipeline with S3, Textract, Step Functions and EventBridge

This is one of my favorite AWS patterns to demo because it is both visually compelling and production-relevant. It shows event-driven architecture, orchestration, asynchronous AI/ML service integration, scale-out processing, human-in-the-loop review, and operational discipline in one workflow. In this post, I will walk through an end-to-end implementation of a document processing pipeline built with: Amazon S3 for document ingress and result storage Amazon Textract for OCR and structured extraction AWS Step Functions for orchestration (including Distributed Map for batch scale) Amazon EventBridge for event routing and downstream integration I will also cover: Async Textract orchestration Batch scaling with Distributed Map Result storage and audit trail Human review step Cost and throughput tuning Architecture and code walkthrough Why this pattern is so effective In real teams, document processing is rarely just “OCR a file and store JSON.” We usually need to handle: Multi-page PDFs and