This article details the construction of a production-ready Retrieval-Augmented Generation (RAG) pipeline designed to accurately answer questions from complex PDF documents. The pipeline focuses on structural retrieval, enabling it to pinpoint specific information within a 45-page car insurance policy. It parses PDFs into structured tables, routes queries to relevant sections by name instead of relying solely on embeddings, and provides typed answers with direct citations to the source lines for verification. AI
IMPACT Enhances the accuracy and verifiability of information retrieval from complex documents like insurance policies.
RANK_REASON Article describes a specific technical implementation of a RAG pipeline for PDF processing, which is a tool or method rather than a core AI release or research.
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