Convert documents into structured data for AI
Overview
Your data is trapped in complex documents
Docling for IBM watsonx® is a document intelligence tool that turns complex, unstructured documents into structured, AI-ready data. It converts PDFs, images, slide decks and other formats into outputs that search, RAG and agent workflows can use more effectively, helping teams get more accurate and reliable results.
Built on the open source Docling toolkit developed by IBM, Docling for IBM watsonx gives teams a faster way to move from experimentation to production through a managed service. It also offers simple UI and API access for automated document processing.
Features
Everything you need to prepare documents for AI
Turn raw documents into structured formats like Markdown, JSON and HTML that are easier for search, RAG and agent workflows to use. With cleaner, more consistent inputs, teams can improve retrieval quality and get more accurate, reliable results from downstream AI systems.
Basic extraction can strip away the structure that makes a document understandable. Docling is designed to retain context like layout, hierarchy, tables and reading order so the original document’s meaning remains intact.
Process PDFs, images, slide decks, forms, spreadsheets, audio files and more in a single platform. Instead of stitching together multiple approaches, teams can work with many types of formats in a more consistent way, reducing tool sprawl and simplifying how content moves into AI workflows.
Start quickly in the UI to upload documents, test conversion settings and inspect results. When you’re ready to scale, use the API to embed and automate document processing across applications, data pipelines and AI workflows.
Explore Docling for IBM watsonx
Use cases
Put your enterprise knowledge to work
Convert PDFs, images, presentations, forms and more into structured outputs for downstream AI use.
Extract the fields that you need from unstructured documents into standardized formats for easy AI use.
Clean, structure, chunk, enrich and validate document content for reliable use in AI applications and workflows.
Analyze and preserve the structure, layout and meaning of complex documents so AI systems can better interpret them.
Improve retrieval quality by turning documents into structured, chunk-ready content for RAG pipelines.
Help users find the right content by converting documents into search-ready data for better indexing and retrieval.
Enable AI agents to act more reliably with inputs they can interpret and use more effectively.
Improve training data quality by converting raw data into cleaner, standardized outputs at scale.
Open at the core
Docling started as an open source toolkit developed by IBM and donated to the Linux Foundation. Today, it’s a community-driven project with more than 40 million downloads and ongoing contributions from IBM.
Docling for IBM watsonx builds on this foundation delivered as a managed service for teams who want a faster path to production.
Pricing
Explore pricing
Docling for IBM watsonx pricing is based on Resource Units, or RUs, to make usage simple across different document types.
1 RU equals 1,000 pages or objects (for files like PDFs, images, or slides) or 50 million characters (for files like plain text or spreadsheets).
*Docling is a trademark of LF Projects, LLC. For more information about Docling, see docling.ai.