Financial services · AI & automation
AI Document Intake.
An automation pipeline that reads, classifies and extracts data from incoming documents, with a human review step for edge cases.
Concept project. This is an illustrative demonstration of our approach, not a client engagement. It contains no client data or reported results.
- Python
- LLM integration
- FastAPI
- Queues
The challenge
Document-heavy back offices spend hours re-keying data from forms and statements. The concept shows how AI extraction can be paired with human review to stay accurate and auditable.
Our approach
- 01Classify documents and route each type to a dedicated extraction schema.
- 02Score extraction confidence and send low-confidence fields to a reviewer.
- 03Log every decision so outputs remain traceable and auditable.
Architecture
- Queue-based processing pipeline with retry and dead-letter handling
- Schema-validated LLM extraction with deterministic post-processing
- Review interface with keyboard-first workflows for operators