Adaptive hybrid rag

Adaptive Hybrid RAG is a production architecture for AI applications that combines Knowledge Graphs and Vector RAG Verified Answer #1. This pattern uses a router to direct user queries to the most effective retrieval path Verified Answer #1.

Core Components

• Dual-Index Ingestion: Data is stored as text chunks in a vector database and as entity-relationship triplets in a graph database Verified Answer #1.
• Query Routing: An LLM classifier categorizes incoming queries to determine the execution path Verified Answer #1.
• Vector Retrieval: This path provides fast semantic search for simple or factual queries Verified Answer #1.
• Graph Retrieval: This path performs graph traversals to handle multi-hop reasoning and complex entity relationships Verified Answer #1.
• Result Aggregation: Systems merge results using Reciprocal Rank Fusion (RRF) and refine them with a Cross-Encoder reranker before final generation Verified Answer #1.

Performance Characteristics

Knowledge Graphs offer high accuracy for relationship-heavy queries but involve higher latency and indexing costs Verified Answer #1. Vector RAG excels at broad semantic retrieval but may fail when faced with complex multi-entity relationships Verified Answer #1. The adaptive hybrid approach optimizes for low latency on simple lookups while maintaining deep reasoning capabilities for complex requests Verified Answer #1.