The Proxy-Pointer RAG architecture integrates document structure into a vector index, achieving enhanced retrieval accuracy without the scalability issues of traditional systems. This article builds upon previous findings by applying Proxy-Pointer to complex financial documents, specifically 10-K filings from AMD, American Express, Boeing, and PepsiCo, answering 66 questions across two benchmarks. The results demonstrate its capability in handling structured documents, improving upon typical vector RAG methods that often produce sub-optimal responses. The article also includes a comprehensive open-source pipeline for users to replicate the results and adapt the system for their own documents.
RAGNLPOpen Source+1
RAGNLPOpen SourceFine-Tuning
Proxy-Pointer RAG Achieves 100% Accuracy by Leveraging Document Structure for Improved Retrieval
Towards Data Science· Partha Sarkar· Monday, April 20, 2026
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