Using Hybrid Search to Deliver Fast and Contextually Relevant Results

Hybrid Search is a powerful approach for search-centric applications, combining the strengths of semantic and keyword-based search to enhance precision and recall. It captures user intent and finds exact keyword matches, making it suitable for fields like legal research, customer support, knowledge management, and enterprise search. Ragie's Hybrid Search system integrates semantic retrieval with keyword retrieval using BM25 scoring, storing document chunks in both a vector and a full-text index. The results are weighted, merged using reciprocal rank fusion, and reranked with an LLM-based approach to optimize relevance. This method supports hierarchical summarization, ensuring seamless integration with Ragie's advanced RAG setup, and is fully partition-aware, maintaining accuracy across different data partitions. Developers can configure Hybrid Search via Ragie's API, allowing adjustments to refine retrieval scope and results.

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