any2md

Most document converters treat pages as flat text—they silently drop formulas, break tables, and lose cross-references. We measured 40% context loss on competitors. any2md uses a dual-engine approach: PyMuPDF extracts text structure while Qwen-VL reads the visual layout. DeepSeek LLM then reconstructs the missing context through layered prompting with few-shot examples and chain-of-thought reasoning.

The result: 93% context retention at 68 pages/min, with 85% table structuring accuracy and 90% LaTeX formula preservation. One team imported 20,000+ pages into their knowledge base in a single week, cutting manual cleanup by 70%. The tool processes everything from scanned PDFs to complex academic papers with multi-column layouts.