Stop Returning Flat Text from a PDF: The Relational Shape RAG Needs

Standard RAG systems often fail by extracting flat, unstructured text from PDFs, which destroys important contextual information like table structures. A more effective method is to parse the document into a relational set of tables, modeling entities like the table of contents, pages, lines, images, and cross-references. This approach preserves the document's inherent structure, keeping columns in a table associated and labels connected to their values. Downstream retrieval and generation models can then query these structured tables instead of the raw PDF. This relational data model allows the AI to understand the document's layout and semantics, leading to significantly more accurate and reliable answers.