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LlamaCloud

Managed document parsing, extraction, indexing, and retrieval for production RAG.

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About

LlamaCloud is LlamaIndex's managed platform for the document side of RAG, distinct from the open-source framework. Three products cover the pipeline: LlamaParse, a GenAI-native parser that converts complex PDFs, DOCX, PPTX, and spreadsheets across 130+ formats into LLM-ready Markdown or JSON; LlamaExtract, which turns documents into typed JSON against a Pydantic or JSON schema; and LlamaCloud Index, a fully managed ingestion, embedding, and hybrid-retrieval endpoint with reranking.

In September 2026 LlamaIndex CEO Jerry Liu signaled the company's strategic bet: the primary focus shifted to LlamaParse, the newer LiteParse, and the ParseBench/ExtractBench benchmarks, with the open-source framework continuing as a toolkit. Developers should note the SDK transition: the classic llama-cloud-services v1 API is legacy and maintained only through May 1, 2026, while the new llama-cloud v2 SDK is the current path for new projects. The two APIs are not drop-in compatible.

For teams whose RAG quality lives or dies on parse quality, managed parsing beats maintaining OCR and layout pipelines. The risk is platform concentration: the vendor's center of gravity is moving toward parsing products, and retrieval-heavy roadmaps should account for the slowing open-source framework cadence.

What it can do

  • LlamaParse: GenAI-native document parsing to Markdown/JSON
  • LlamaExtract: schema-driven structured extraction
  • LlamaCloud Index: managed ingestion with hybrid retrieval and reranking
  • Auto-syncing data sources with a single retrieval endpoint

Setup

Sign up at cloud.llamaindex.ai, get an API key, use the llama-cloud v2 SDK or REST API.

Prerequisites

A LlamaCloud account and API key; documents to parse or index.

Use cases

ragdocument-parsingstructured-extraction

Works with

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 87; Trending score 82/100 from researcher assessment.

Sources

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