LlamaIndex
Open-source data framework for building LLM applications with RAG over external data.
Updated April 2026
Overview
- Website
- llamaindex.ai
- Founded
- 2022
- Headquarters
- San Francisco, CA
- Segment
- RAG & Retrieval
Product overview
LlamaIndex provides a developer framework for ingesting, indexing, and querying private data with LLMs via retrieval-augmented generation (RAG), alongside enterprise tools like LlamaParse for agentic document parsing/extraction and Workflows for AI orchestration.. Used by banks, hedge funds, insurance firms, healthcare providers, and tech teams at Salesforce for financial analysis, claims processing, and customer support agents, processing over 1B documents. Distinct for its modular agent framework, high-accuracy OCR on complex docs (tables/charts/handwriting), and 100+ integrations, bridging data to production AI agents faster than general tools like LangChain.
Revenue model
Open-source core (free); LlamaCloud tiers: Free (10K credits/mo), Starter ($50/mo, 40K credits), Pro ($500/mo, 400K credits), Enterprise (custom) with pay-as-you-go credits at $1.25/1K for parsing/indexing; startup program; volume discounts.
Moat
LlamaIndex's key competitive moat is its industry-leading document parsing technology (LlamaParse), which excels at handling complex unstructured data like PDFs, tables, images, and handwritten notes across 90+ file types, delivering superior accuracy for RAG pipelines that competitors struggle to match. This is reinforced by massive scale advantages—1B+ documents processed, 25M+ monthly package downloads, and 300k+ LlamaParse users—creating high switching costs for developers reliant on its customized retrieval pipelines and a strong open-source community of 1.5k+ contributors.