RAG Knowledge Base Modernization
The Challenge
A professional services firm had decades of institutional knowledge scattered across legacy documentation systems. Staff spent significant time searching for answers that existed but were hard to find.
Our Approach
We built a Retrieval-Augmented Generation pipeline with semantic chunking, hybrid search (vector + keyword), and a conversational interface. The system respects access controls and provides source citations for every answer.
Outcome
Internal support queries are now answered in seconds with source attribution. The system continuously improves as new documents are ingested, and staff adoption has been strong due to the familiar chat interface.