Docling is an open-source Python and TypeScript library for advanced document processing of unstructured data. It addresses the often overlooked "last mile" problem of converting real-world documents — like PDFs and PowerPoints — into clean, machine-readable formats. Unlike traditional extractors, Docling uses a computer vision–based approach to interpret document layout and semantic structure, which makes its output particularly valuable for retrieval-augmented generation (RAG) pipelines. It converts complex documents into structured formats such as JSON or Markdown, supporting techniques like structured output from LLMs. This contrasts with ColPali, which feeds page images directly to a vision-language model for retrieval.
Docling's open-source nature and Python core, built on a custom Pydantic-based data model, provide a flexible, self-hosted alternative to proprietary cloud tools such as Azure Document Intelligence, Amazon Textract and Google Document AI. Backed by IBM Research, the project’s rapid development and plug-and-play architecture for integrating with other frameworks like LangGraph make it well worth assessing for teams building production-grade AI-ready data pipelines.
