LlamaIndex
Also known as: LlamaIndex.ai, GPT Index
In one sentence
An open-source framework designed for building LLM applications that connect to your own data, with particular strength in retrieval-augmented generation (RAG) systems and data indexing.
Explain like I'm 12
Like a super-organised librarian for AI—it takes all your messy documents, sorts them into a system the AI can search through, and helps it find exactly the right information to answer your questions.
In context
LlamaIndex excels at connecting private data to large language models. It handles the full RAG pipeline: ingesting documents from dozens of sources (PDFs, databases, Notion, Slack, Google Drive), splitting them into chunks, creating embeddings, storing them in vector databases, and retrieving the most relevant pieces when a user asks a question. Compared to LangChain, which is a general-purpose orchestration framework, LlamaIndex is more focused on the data retrieval side of AI applications.
See also
Related Guides
Learn more about LlamaIndex in these guides:
Orchestration Options: LangChain, LlamaIndex, and Beyond
IntermediateFrameworks for building AI workflows. Compare LangChain, LlamaIndex, Haystack, and custom solutions.
12 min readAI Workflows and Pipelines: Orchestrating Complex Tasks
IntermediateChain multiple AI steps together into workflows. Learn orchestration patterns, error handling, and tools for building AI pipelines.
7 min readRetrieval 201: Chunking, Indexing, and Hybrid Search
IntermediateGo beyond basic RAG. Advanced techniques for chunking documents, indexing strategies, re-ranking, and hybrid search.
12 min read