ai-validation.workflow

Document intake, storage, OCR, AI checks, and human review in one repeatable flow.

step_01
Upload flow validates documents and stores the original files through AWS S3 integration.
step_02
Asynchronous processing sends work through OCR and AI providers without blocking the user experience.
step_03
Validation results are structured so people can review, correct, and trust the final output.

Architecture sketch for the OCR and AI validation workflow

OCR / AI Validation System

TypeScript
Node.js
AWS S3
OCR / AI
Full-Stack

Project Overview

I designed and implemented a full-stack document validation system where uploaded files move through storage, asynchronous processing, OCR extraction, AI-assisted checks, and human-reviewable output. The important part was not just connecting providers, but making the workflow predictable: clear inputs, visible status, structured results, and enough guardrails for the team to verify behavior repeatedly.

Technical Implementations & Highlights

  • Built backend upload and processing flows around document intake, storage boundaries, and status visibility.
  • Integrated AWS S3 for file storage and designed the handoff between UI, backend services, and external OCR/AI providers.
  • Structured asynchronous validation so long-running document checks did not block the product experience.
  • Shaped AI-agent validation outputs into a format that could be reviewed by humans instead of treated as a black box.
  • Owned the integration boundaries and verification loops across the full stack.