#4287 Vectorless RAG with PageIndex
#4287 Vectorless RAG with PageIndex #4287 Tell me about PageIndex for AI and RAG PageIndex is a vectorless, reasoning-based retrieval framework designed to overcome the limitations of traditional Retrieval-Augmented Generation (RAG). Developed by VectifyAI , it mimics how a human expert navigates a document—using a table of contents and logical reasoning rather than mathematical "vibe-matching" via vector similarity. It gained significant attention for achieving 98.7% accuracy on FinanceBench , a benchmark where traditional RAG often struggles due to the complexity and length of financial documents. ## How PageIndex Differs from Traditional RAG The core shift is moving from Search (Similarity) to Navigation (Reasoning) . Feature Traditional Vector RAG PageIndex Logic Mathematical similarity (cosine distance). LLM-driven logical reasoning. Storage Requires a Vector Database (Pinecone, Chroma). No vector database required; uses a JSON tree. Granularity Fixed-size chunks (e...