By @IBMResearch
Publication Date: 2026-08-12 12:00:00
AI is upending how we live and work, but the data that could really transform how businesses run is often locked away in outdated or proprietary formats.
Docling, IBM’s open-source document parser, has helped to make this information more accessible, allowing enterprises to lift new insights from old charts, customer files, and annual reports.
With 32 million downloads and 64,000 stars on GitHub, Docling is IBM’s most successful open-source project ever. It’s been integrated into everything from LangChain to Red Hat’s OpenShift, and even IBM’s own Granite family of LLMs.
Now, the researchers behind Docling are introducing its complement: DocLang, a sub-language of XML that has the potential to lower latency and inferencing costs by telling an AI model in fewer tokens where things like a headline ends and a chart caption begins.
XML stands for Extensible Markup Language, which was designed to store and move data across apps, databases, and web services. In the 1990s, front-end…