Is Keyword Search Dragging Your Hybrid Relevance Down?
Whether you are working on a RAG pipeline or a standalone retrieval system, the ability of your hybrid search to surface relevant documents may mean the difference between your agent performing a meaningful next step or sending your system (or user) down a rabbit hole, wasting tokens and time. For the end-user, the difference between a helpful response and a frustrating experience may be one relevant document showing up at the top of the results.
When search behavior is suboptimal, the tendency is to look for, train, or tune a better model. But with hybrid search it takes two to dance. Keyword search and semantic search must work together to surface the best results. Keyword search is often treated as a solved problem, and in many ways it may be. But no two keyword search solutions are the same. Even while implementing similar tokenization, the ranking and fusion math could be drastically different. Leaving your keyword signals unexamined may cause weeks of work focused on the wrong problem.