{
  "slug": "llamaindex",
  "name": "LlamaIndex",
  "url": "https://www.llamaindex.ai",
  "cat": "ai",
  "group": "ai",
  "tagline": "RAG framework and doc parsing",
  "price": "Framework free and open source. LlamaCloud credits: Free 10,000 credits, Starter $50/mo (40k credits), Pro $500/mo (400k credits), Enterprise custom. 1,000 credits = $1.25.",
  "tier": "mixed",
  "pick": false,
  "what": "An open-source data <b>framework</b> for connecting LLMs to your documents — ingestion, chunking, indexing, retrieval and agent workflows. LlamaCloud is the commercial side, mainly LlamaParse, which turns messy PDFs, tables and slides into clean model-ready text.",
  "why": "If the app is 'chat with my documents', this is the shortest path from a folder of PDFs to a working retriever. LlamaParse handles the tables and scanned pages that break naive text extraction.",
  "warn": "Parsing credits burn faster than expected — agentic LLM-backed parsing costs many credits per page versus one for basic mode, so a large corpus blows through the free 10,000 quickly.",
  "install": "pip install llama-index",
  "category": {
    "key": "ai",
    "name": "Model APIs, routers & observability",
    "desc": "Providers, gateways, inference hosts and eval layers — constantly conflated, listed separately here.",
    "group": "ai",
    "groupName": "Put AI inside it"
  },
  "freshness": null,
  "health": {
    "ok": true,
    "status_code": 200,
    "final_url": "https://www.llamaindex.ai/",
    "checked_at": "2026-08-18T23:43:12.623+00:00"
  },
  "corrected_at": null,
  "upstream_changed_at": null
}