Traditional vector-based RAG often struggles with retrieval accuracy because it optimizes for similarity, not relevance. But what we truly need in retrieval is relevance, which requires reasoning. When working with professional documents that require domain expertise and multi-step reasoning, vector-based RAG and similarity search often fall short.So we started exploring a more reasoning-driven approach to RAG. Reasoning-based RAG enables LLMs to think and reason their way to the most relevant d...