Keywords AI
Docling vs Unstructured
Compare Docling and Unstructured side by side. Both are tools in the RAG Frameworks category.
Quick Comparison
| Category | RAG Frameworks | RAG Frameworks |
| Pricing | Open Source | Freemium |
| Best For | Developers and researchers who need accurate document parsing with layout and table understanding | Enterprises that need to extract structured data from large volumes of unstructured documents |
| Website | github.com | unstructured.io |
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When to Choose Docling vs Unstructured
- PDF to structured data conversion
- Academic paper processing
- Financial report extraction
- Enterprise document ingestion pipelines
- RAG data preparation from PDFs and docs
- Financial document processing
About Docling
Docling is IBM's open-source document conversion toolkit that transforms PDFs, DOCX, PPTX, and other document formats into structured JSON or markdown. It uses advanced layout analysis and table structure recognition to preserve document structure, making it ideal for preparing documents for RAG and LLM applications. Docling integrates with LlamaIndex and LangChain for seamless pipeline construction.
About Unstructured
Unstructured is the leading data ingestion platform for AI applications, transforming unstructured data—PDFs, Word documents, HTML, images, emails—into clean, structured formats ready for LLM consumption and RAG pipelines. The platform handles document parsing, OCR, table extraction, and chunking with high accuracy. Available as open-source and a managed API service, Unstructured is used by enterprises to prepare large document corpora for AI processing.
What is RAG Frameworks?
Frameworks and tools for building retrieval-augmented generation pipelines—document parsing, chunking, indexing, and query engines that connect LLMs to your data.
Browse all RAG Frameworks tools →