Knowledge Base Search & Usage Analytics

Overview

Architected a retrieval-augmented generation system that surfaces accurate answers from a large internal document corpus. Combined semantic chunking, vector embeddings, and a re-ranking layer to maximize relevance. Built a lightweight chat interface for non-technical users to query complex documentation. Deployed with latency under 800ms on average.

Approach

Research, definition, design, and delivery were developed as one connected system, with each decision tested against the project goals.

Outcome

A considered digital experience with a clear foundation for continued iteration and growth.