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RAG-RLM Hybrid Architecture

RAG and RLM solve different problems in the same system.

  • RAG optimizes focused retrieval and fast response.
  • RLM optimizes exhaustive corpus analysis and synthesis.

The hybrid architecture combines both behind a router that dispatches each query to the right path.

  • Query router: classifies query scope and synthesis needs.
  • RAG path: selective retrieval over indexed chunks, then answer generation.
  • RLM path: recursive or programmatic corpus exploration, then synthesis.
  • Unified answer surface: user receives one response regardless of route.
  • Similarity is not the same as relevance for broad analytical questions.
  • Fixed top-k retrieval can omit important long-tail evidence.
  • Large stuffed contexts degrade synthesis quality.
  • It has no native exhaustive mode.
  • Higher latency due to multi-step recursive execution.
  • Higher cost per query.
  • Unnecessary complexity for simple lookups.
  • Speed where lookup dominates.
  • Completeness where synthesis dominates.
  • Better cost efficiency via selective use of expensive reasoning paths.
  • Higher trust on “analyze everything” style questions.