Document Intelligence
A processing engine that extracts, understands and routes information from thousands of unstructured files.
Reference and concept systems built internally. Figures describe system scope, not client results.
- Industry
- Financial services
- Discipline
- AI / Documents
- Status
- Reference system
CH.01Overview
The system at a glance
- 06
- document types
- 04
- extraction stages
- Review
- queue built in
CH.02Problem
Where it was breaking
This reference scenario models a document workflow that depends on manual classification and data entry. Variations in format make fixed-rule automation fragile and expensive to maintain.
CH.03Architecture
The life of a document
Every extracted value keeps a path back to the region of the page it came from, which is what makes review cheap and correction permanent.
CH.04System
Built for real operation
The system can classify, parse, check and route documents. Ambiguous fields enter a focused review queue, and corrections remain attached to their source context.
CH.05Approach
Design the decision, then automate it
The extraction sequence combines layout understanding, domain validation and deterministic business rules, with a visible review state at every step.
CH.06Results
What this build demonstrates
The build demonstrates how document volume can move through a controlled extraction pipeline, with reviewers focused on fields the system marks as uncertain.
Technology
- Python
- OpenAI
- Document AI
- PostgreSQL
- FastAPI
- AWS
Next / 001AI Automation / Enterprise