Overview
LlamaIndex is a data framework for building LLM applications over your own private data — the retrieval half of the RAG stack. A raw model only knows its training data; most useful business apps need it to answer from your documents, tickets, or knowledge base, and that requires a pipeline: ingest from many sources, parse into clean text, split and index, then retrieve the right chunks at query time. LlamaIndex supplies those building blocks, plus growing support for agents that reason over the same data. The open-source framework is free under a permissive license and self-hostable; LlamaCloud is the managed platform that turns the operationally painful parts — especially LlamaParse, its layout-aware PDF parser — into hosted services. It sits in the data/retrieval layer, complementary to orchestration frameworks like LangChain rather than a direct replacement.
Key Features
- High-level abstractions for ingestion, indexing, retrieval, and query engines
- LlamaParse: layout-aware parsing of complex PDFs, tables, and multi-column docs
- 300+ LlamaHub integrations (data loaders, vector stores, tools)
- Event-driven, async-first Workflows stable in Python and TypeScript
- Agents and multi-step orchestration over private data
- Self-hosted, LlamaCloud SaaS, or hybrid VPC deployment
Pricing
| Plan | Price | For |
|---|---|---|
| Open-source framework | $0 | MIT license, self-host, pay only your own LLM usage |
| LlamaCloud Free | $0 | ~10K credits/month, 1 user, community support |
| LlamaCloud Starter | $50/mo | ~40K credits, 5 users, pay-as-you-go up to 400K |
| LlamaCloud Pro | $500/mo | ~400K credits, 20 concurrent jobs, Slack support |
| Enterprise | Custom | SSO, VPC, 5x rate limits, dedicated manager |
Comparison
Compared to LangChain, LlamaIndex is narrower but deeper on data and retrieval — best when your hard problem is parsing and ranking ugly documents rather than chaining model calls. Versus Flowise, it is code-first and far more customizable, while Flowise wins on no-code visual building. For teams that want a managed no-code RAG product over a framework, Dify is the closer comparison.