LlamaIndex
verifiedPaidLeading framework for building LLM knowledge assistants over enterprise data.
What it does
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data. It offers document parsing, data extraction, knowledge management, and an agent framework to build production agents that can find information, synthesize insights, generate reports, and take actions over the most complex enterprise data.
How to use: LlamaIndex can be used to connect, transform, and index enterprise data into an agent-accessible knowledge base. It allows users to orchestrate and deploy multi-agent applications over their data using the agent framework. Users can also leverage LlamaCloud for end-to-end tooling to ship context-augmented AI agents to production.
Core features
- ✦Document parsing with LlamaParse
- ✦Data extraction with LlamaExtract
- ✦Knowledge management
- ✦Agent framework for multi-agent orchestration
- ✦LlamaCloud for deploying AI agents
Use cases
- →Building a leveraged buyout agent to automatically fill structured values from unstructured 10-Ks and earnings decks.
- →Handling customer FAQs and order cancellations with a chatbot.
- →Building an internal knowledge and automation platform.
Pricing
Reviews
Big-picture takes: what it's for and whether it delivers. High-engagement videos from YouTube — not sponsored.
Building AI Agents that actually automate Knowledge Work - Jerry Liu, LlamaIndex
AI Engineer · 126K views
Announcing LlamaIndex Gen AI Playlist- Llamaindex Vs Langchain Framework
Krish Naik · 77K views
Introduction to LlamaIndex with Python (2025)
Alejandro AO · 71K views
Tutorials
Step-by-step: exactly how to get things done with it.
Build a RAG pipeline in LlamaIndex (simple)
AWS Developers · 459K views
Python Advanced AI Agent Tutorial - LlamaIndex, Ollama and Multi-LLM!
Tech With Tim · 172K views
End to end RAG LLM App Using Llamaindex and OpenAI- Indexing and Querying Multiple pdf's
Krish Naik · 132K views