Power agents with searchable knowledge bases
LlamaCloud Index makes your data ready for retrieval with intelligent chunking and embedding to ensure accuracy at scale
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500M+
Documents processed
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200k+
LlamaCloud users
Why Index
Ensure data is ready for high-quality retrieval
Durable data pipelines
Leverage connectors to popular data sources and destinations with incremental syncs to keep data fresh
Embedding model choice
Flexibly define your favorite embedding model or use our recommended settings
Advanced retrieval
Ensure high-accuracy and context relevance for an efficient and accurate knowledge system
Multimodal indexing
Index text and images for high accuracy retrieval across modalities
Test and evaluate
Test and evaluate you index with OTEL and other integrations
Context-aware agents
Use indexed data for downstream workflow automation with AI agents
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Designed for developers. Documented for clarity
Trusted by leading AI builders and enterprise teams
We’ve helped leading teams go from prototype to production with real-world results.
Testimonials
Leading our organization's internal RAG assistant development, LlamaIndex’s rich ecosystem of connectors and thoughtful abstractions has enabled us to rapidly iterate on complex data pipelines and LLM-powered solutions. What truly sets LlamaIndex apart is their team's ability to rapidly integrate cutting-edge research and embrace community contributions, enabling us to continuously experiment with state-of-the-art approaches. Their recent focus on Workflows demonstrates their forward-thinking approach, helping us stay at the forefront of generative AI innovation.
LlamaCloud's capabilities have played a significant role in helping standardize the development of enterprise knowledge assistants at KPMG. The platform's intuitive interface for configuring RAG pipelines allows us to leverage cutting-edge techniques while maintaining consistency.
LlamaCloud’s ability to efficiently parse and index our complex enterprise data has significantly bolstered RAG performance. Prior to LlamaCloud, multiple engineers needed to work on maintenance of data pipelines, but now our engineers can focus on the development and adoption of LLM applications.