Proxy-Pointer RAG: Achieving Vectorless Accuracy at Vector RAG Scale and Cost

Retrieval-Augmented Generation (RAG) systems face a significant trade-off between the high accuracy of structure-aware "Vectorless" methods and the scalability of traditional vector search. While techniques like PageIndex offer superior accuracy by creating a hierarchical summary tree for an LLM to navigate, their high cost and latency make them impractical for large document collections. A novel approach called Proxy-Pointer RAG aims to resolve this dilemma by integrating the structural reasoning principles of vectorless models into a scalable and efficient vector-based pipeline. This hybrid method promises to deliver the high-quality, context-aware answers of advanced RAG at the speed and cost of standard vector search systems.