Keywords AI
LlamaIndex vs Unstructured
Compare LlamaIndex 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 building data-intensive LLM applications who need flexible ingestion and retrieval | Enterprises that need to extract structured data from large volumes of unstructured documents |
| Website | llamaindex.ai | unstructured.io |
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When to Choose LlamaIndex vs Unstructured
- Building RAG pipelines from any data source
- Enterprise knowledge base creation
- Multi-source data integration for AI
- Enterprise document ingestion pipelines
- RAG data preparation from PDFs and docs
- Financial document processing
About LlamaIndex
LlamaIndex (formerly GPT Index) is a data framework for connecting LLMs with external data sources. It provides connectors for 160+ data sources, document parsers, indexing strategies, and query engines that make it easy to build RAG applications. LlamaIndex supports advanced retrieval patterns including recursive retrieval, knowledge graphs, and multi-document agents. The LlamaCloud managed service handles document ingestion and parsing at scale.
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 →