Hybrid Search: Best of Both Worlds
Combine semantic and keyword search for optimal results.
The Search Accuracy Problem
How Hybrid Search Works
Dual Search Execution
Your query runs through both BM25 (keyword) and dense vector (semantic) search engines simultaneously.
Reciprocal Rank Fusion
Results from both methods are intelligently merged using RRF algorithm for optimal ranking.
Configurable Weights
Fine-tune the balance between keyword and semantic search based on your specific use case.
Why Hybrid Search Matters
+40% Retrieval Accuracy
Combining keyword and semantic search dramatically improves finding the right information.
Zero Missed Keywords
Product codes, case numbers, and technical terms are found exactly when needed.
Sub-200ms Response
Parallel execution keeps searches fast despite running two engines simultaneously.
Customizable Weights
Adjust the BM25/vector balance to optimize for your specific document types.
Hybrid Search Capabilities
| Feature | RAG Engine | Chatbase | CustomGPT | Dify |
|---|---|---|---|---|
| Vector + BM25 Search | Partial | |||
| Configurable Weights | ||||
| RRF Fusion Algorithm | ||||
| Real-time Rebalancing | Partial |
Based on publicly available feature lists as of 2024
Perfect For
Legal Document Search
Find case citations by exact number while understanding legal concepts.
Technical Documentation
Match API endpoint names exactly while finding related functionality.
Customer Support
Find tickets by ID while understanding the customer issue.
Research Papers
Search by author names and IDs while exploring related topics.
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