A new RAG workflow argues PDFs should become relational data, not flat text

A new document intelligence workflow argues that RAG systems should stop treating PDFs as flat text dumps.

The proposed approach turns one PDF into a relational set of dataframes covering lines, pages, tables of contents, images, captions, spans, cross-references, and parsing metadata. That gives retrieval systems more structure to work with.

The idea is practical for enterprise RAG: preserving document shape can make answers more grounded than simply chunking text and hoping context survives.