LlamaIndex
In one line
LlamaIndex is an LLM framework focused on RAG and data integration — a toolkit for indexing diverse documents, databases and APIs and connecting them to a model.
Going deeper
LlamaIndex started life as 'GPT Index' and stayed RAG-centric as it grew. It indexes heterogeneous sources — PDFs, Notion, Google Drive, Slack, SQL — and standardises the RAG pipeline pieces around them: chunking, embedding, routing, reranking.
The cleanest mental model is that LangChain and LangGraph emphasise the agent workflow side, while LlamaIndex emphasises the data side. Their feature surfaces overlap, but multi-source retrieval and evaluation tooling tend to be more polished in LlamaIndex.
Recent direction goes beyond plain RAG into managed infrastructure (LlamaCloud) and multi-agent patterns. For B2B teams that want an agent layer sitting cleanly on top of a real RAG stack, it has become an obvious starting point.
Related terms
LangGraph
LangGraph is the graph-based agent workflow framework from the LangChain team — built so that branches, loops and human-in-the-loop steps are first-class.
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CrewAI is a multi-agent framework that lets you stand up role-based agents that work as a team, with role, goal and task defined declaratively.
AI AgentAutoGen
AutoGen is Microsoft Research's multi-agent framework, built around conversational agents that exchange messages and divide work between themselves.
LLMRAG
RAG (Retrieval-Augmented Generation) lets an LLM fetch external documents at answer time and ground its response in them — the technique behind ChatGPT Search, Perplexity and most AI search products.
AI AgentTool Use
Tool use is an LLM calling external APIs, calculators or search systems directly to ground its answers — the foundational behaviour of every agent.