IBM-Born Docling Library Converts PDFs and Docs into Clean AI-Ready Data

Docling is an open-source Python library originally created by IBM Research Zurich and now maintained under the LF AI & Data Foundation, designed to convert messy documents into structured, AI-ready output. It supports a wide range of input formats — including PDF, DOCX, PPTX, images, and even audio — and exports everything into a unified internal format that can be rendered as Markdown, HTML, or JSON. Unlike basic text extractors, Docling uses machine learning models to detect page layout, preserve reading order, and accurately reconstruct tables and code blocks, with OCR support for scanned files. The library integrates directly with popular AI frameworks such as LangChain, LlamaIndex, and Haystack, making it easy to plug into existing RAG pipelines. It runs entirely locally with no data leaving the user's machine, though its ML-based approach means a heavier install and slower CPU performance on large document batches compared to lightweight alternatives.