Traditional RAG has a critical flaw: flattening complex PDFs into plain text destroys tables, schematics, and charts.
The latest shift combines Vision Transformers (ViT) and Multimodal LLMs (like Claude) into pure Visual Document RAG.
Instead of brittle OCR parsers, models now index raw page screenshots into spatial visual embeddings. When you ask a question, the retriever matches your query directly to visual patches using Late Interaction (ColPali architectures) and feeds the high-res document straight to the chatbot.
Why it transforms enterprise
- AI:Perfect Table & Chart Retrieval: Retain exact visual layout and spatial context.
- Zero Parsing Overhead: No more complex chunking rules or lost diagrams.