AI Document-Processing Tool for a Professional Services Firm

What We Built

Python, FastAPI, LLM integration, document parsing, cloud deployment

We began with a fixed-scope proof of concept to test feasibility on a sample of real documents. Once the results justified investment, we built a production tool in Python that ingested documents, extracted structured data using a combination of parsing and large language models, classified each item, and routed low-confidence cases to a human reviewer. Guardrails and a review queue kept a person in the loop wherever a decision carried risk.

The Approach

We defined a clear success metric up front and evaluated the proof of concept against it before committing to the full build. Getting the data and evaluation right came before any talk of sophisticated models, which kept the project honest and avoided over-engineering.