LlamaIndex is the leading data framework for building LLM applications over custom data, providing the tools needed to ingest, structure, index, and query any data source as context for language models. It handles the complete RAG pipeline — from data connectors for 100+ sources, to chunking strategies, to retrieval optimization, to response synthesis — with production-grade reliability. AI engineers building enterprise knowledge assistants, document Q&A systems, and agentic research applications use LlamaIndex to build the data layer of their LLM applications with best-practice patterns rather than reimplementing complex retrieval workflows from scratch.