Traditional PDF parsing often extracts words while losing the charts, diagrams, and spatial relationships that carry meaning. A new guide argues that vision language models can act as richer PDF parsers for RAG systems by interpreting visual structure directly.
That is important for enterprise document intelligence, where reports, manuals, and filings often encode key information in tables or graphics. Better visual parsing can improve retrieval quality and reduce the gap between what a human sees on a page and what an AI system can use.