AI AGENTS
LlamaIndex
by LlamaIndex
Overview
Framework for building LLM-powered agents and workflows over private or external data, with tools, memory, RAG, and multi-agent patterns.
Details
LlamaIndex is described by its official website, documentation, and GitHub source metadata as a framework for building LLM-powered agents and workflows over private or external data. The supplied sources specifically associate it with agents, workflows, tools, memory, RAG, and multi-agent patterns, making it relevant for teams evaluating agent frameworks that need to connect LLM behavior with data-aware workflows.
When to Use
Use when building LLM-powered agents or workflows over private or external data. Use when evaluating agent frameworks that support tools memory RAG or multi-agent patterns.
Getting Started
- Open the official LlamaIndex website for the product overview.
- Read the LlamaIndex agent deployment documentation.
- Review the run-llama/llama_index GitHub repository before implementation.
Key Features
- •LLM-powered agent and workflow framework
- •Designed for private or external data use cases
- •Supports tools
- •memory
- •RAG
- •and multi-agent patterns
Capabilities
- •LLM-powered agents
- •workflows
- •tools
- •memory
- •RAG
- •multi-agent patterns
Last updated Jun 9, 2026