The article introduces PageIndex, a reasoning-based retrieval framework designed to enhance long document processing by overcoming the limitations of traditional vector-based Retrieval-Augmented Generation (RAG) methods. Unlike conventional approaches that rely on static semantic similarity, PageIndex utilizes a dynamic, iterative reasoning process to navigate document structures and extract relevant information more effectively. This innovative model aims to improve the accuracy and relevance of responses generated by large language models in complex contexts.