The premier data framework for connecting LLMs to private data. By 2026, its 'LlamaCloud' managed service (featuring LlamaParse) became essential for production
LlamaIndex is the data framework for LLM applications: best-in-class document parsing (LlamaParse), ingestion pipelines, indexes, and agentic retrieval, plus LlamaCloud for managed parsing/extraction. Where LangChain centers on orchestration, LlamaIndex centers on getting enterprise data RAG-ready.
Pricing: Open-source framework is free; LlamaCloud (parse/extract) runs credit-based freemium with usage tiers for production volumes (published pricing, mid-2026).
LangChain vs LlamaIndex (2026): They compose rather than compete: LlamaIndex leads on the data side, document parsing (LlamaParse), ingestion, and retrieval quality, while LangChain/LangGraph leads on orchestration: stateful agents, checkpoints, and human-in-the-loop control. Many production stacks use exactly that split.
They compose: LlamaIndex for document pipelines and retrieval quality, LangChain/LangGraph for agent orchestration. Many production stacks use exactly that split.
It treats parsing as a model problem: complex tables, multi-column layouts, and embedded structures come out RAG-usable where naive PDF extraction produces noise, often the single biggest RAG quality fix.