IBM’s Granite Docling 258M & Its DocTag Revolution: The Model That Doesn’t Flatten Your Data

A storytelling journey into how IBM turned vision, language, and structure into a layout-preserving AI built for the RAG era

Section 1 — Cold Open

“The invoice was unreadable. But it wasn’t the ink’s fault.”

The insurance adjuster squinted at the PDF. It wasn’t blurry. It wasn’t corrupted. It was just… flattened. The form had three columns. Two nested tables. A signature box with micro-font legalese. But when the AI parser ran its course, everything came out as mush. No headings, no rows, no visual hierarchy. Just a blob of misordered text — like it had been shuffled in a blender and poured into a TXT file.

And this wasn’t an edge case. It was the 47th time this month.

Enterprise AI teams face this every day. Document-heavy workflows — contracts, pharma trials, government filings, manufacturing blueprints — rely on information being where it should be. OCR doesn’t get that. Even tokenizers don’t. They don’t “see” layout. They hallucinate structure where there is none.