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Retrieval & Ranking
Production RAG System
A grounded question-answering system built over enterprise knowledge with careful ranking, chunking, and answer controls.
Problem
Generic LLM outputs were not reliable enough for enterprise support use cases where correctness and traceability mattered.
Outcome
Improved answer accuracy by ~35% through retrieval design, ranking strategy, chunk quality, and grounding discipline.
Stack used
PythonLangChainVector RetrievalRankingGrounding