IBM is contributing 3 open-source projects—Docling, Data Prep Kit and BeeAI—to the Linux Foundation. This move signals not only the potential growth of these projects but also IBM’s ongoing commitment to open-source AI.
“We’re continuing our long history of contributing open-source projects to ensure that they’re easy to consume and that it’s easy for others—not just us—to contribute,” says Brad Topol, IBM Distinguished Engineer and Director of Open Technologies, in an interview. Topol also chairs the Governing Board of the LF AI & Data Foundation, a group hosted under the Linux Foundation focused on advancing open-source innovation across artificial intelligence and data technologies.
Each project is focused on an essential part of the AI development stack. As the industry matures, innovation driven by the broader developer community in these areas is key to making AI enterprise ready.
Docling, which launched and open-sourced a year ago, addresses a limit that many foundation models have for enterprise use. While the models have been trained on every scrap of publicly available information, much of the data valuable to businesses lies in documents that are not accessible online: PDFs, annual reports, slide decks.
Docling streamlines the process of turning unstructured documents into JSON and Markdown files that are easy for large language models (LLMs) and other foundation models to digest.
Since its release, Docling has gained traction, earning more than 23,000 stars on GitHub. When combined with retrieval-augmented generation (RAG) techniques, Docling improves LLM outputs. “Docling can make the LLMs answer much better and much more specific to their needs,” says Topol. In addition to gaining traction in the open-source community, Docling helps power Red Hat® Enterprise Linux® AI, where it enables context aware chunking and supports the platform’s new data ingestion pipeline.
