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Document Intelligence Pipeline
Automated pipeline that extracts, classifies, and summarizes documents using LLMs, reducing manual review time by 80%.
The problem
A back-office team was manually reading, classifying, and summarizing a high volume of incoming documents — a slow process prone to inconsistency.
The approach
I built a Python pipeline behind a FastAPI service that extracts document text, classifies it against the team’s taxonomy, and produces a structured summary using the Claude API, with a review step for anything below a confidence threshold.
The outcome
Manual review time dropped by roughly 80%, and the team now spends its time verifying edge cases instead of processing every document from scratch.