LlamaCloud
Managed document parsing and RAG indexing from LlamaIndex
Overview
LlamaCloud is LlamaIndex's hosted platform for document parsing (LlamaParse), extraction, and retrieval — built for teams already on LlamaIndex who want production RAG without running their own ingestion stack.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 11 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- 10,000 credits/mo
- 100 users
- Basic support
- 40,000 credits/mo + PAYG to 400K
- 100 users
- Basic support
- 400,000 credits/mo + PAYG to 4,000K
- 100 users
- Slack support
- 5x higher rate limits
- SSO, dedicated account manager
- SaaS or hybrid deployment
Use cases
What you can produce with LlamaCloud
- LlamaParse — document parsing tuned for tables, scans, multi-column PDFs
- LlamaExtract — structured JSON extraction from documents
- Managed LlamaCloud Index for retrieval pipelines
- 48-hour parse cache to avoid re-billing repeat documents
- SOC 2 Type 2 certified
- EU data residency (early access)
- VPC deployment for enterprise
- Python and TypeScript SDKs
ASEAN Perspective
LlamaCloud in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
LlamaCloud is the commercial layer on top of the open-source LlamaIndex framework: hosted document parsing through LlamaParse, structured extraction via LlamaExtract, and managed retrieval indexes, all reachable from the same SDKs developers already use for RAG. LlamaParse has a solid reputation for handling PDFs that trip up naive extractors — dense tables, scanned pages, multi-column layouts — and the credit-based pricing (roughly $1.25 per 1,000 credits, with a free monthly allowance) lets teams start cheap and pay more only for documents that need the higher-accuracy Agentic modes.
The catch: it pulls you further into the LlamaIndex ecosystem, and as a managed service still expanding its enterprise features (VPC deployment, EU data residency now in early access) it's younger than alternatives from bigger vendors. The SDK surface has also been churning — the original llama_cloud_services package is being deprecated. Best fit for teams already building on LlamaIndex who want to stop maintaining their own parsing pipeline; less compelling if you're framework-agnostic.
What people say
LlamaCloud sits on top of LlamaIndex, the open-source RAG framework, and its main draw is LlamaParse — a document parser built specifically for the PDFs that defeat naive text extraction: nested tables, scanned pages, multi-column academic papers, documents mixing prose with charts and equations. LlamaParse v2 restructured pricing around four parsing modes — Fast, Cost Effective, Agentic and Agentic Plus — running from roughly $0.00125 to $0.05625 per page depending on how much LLM reasoning a document needs, with a 48-hour parse cache meaning re-processing the same file within that window costs nothing.
Independent review coverage specific to LlamaCloud (versus the broader LlamaIndex framework) is limited outside of vendor-published customer logos, but the adoption numbers are notable: the company says LlamaCloud has 300,000-plus registered users and LlamaParse alone has processed more than 500 million documents, with named enterprise customers including Rakuten, Carlyle, Salesforce and KPMG. Hacker News discussion of LlamaParse tends to be technical rather than complaint-driven — LlamaIndex's own CEO has engaged directly in threads defending its benchmark position against competitors, which cuts both ways: informative, but also self-reported.
On the business side, LlamaIndex (the company behind LlamaCloud) raised a $19M Series A in June 2026 led by Norwest Venture Partners with Greylock Partners participating, bringing total funding to $27.5M — modest next to document-parsing rivals like Reducto ($108M total), suggesting a leaner, more developer-led growth strategy. The company reached SOC 2 Type 2 certification and has GDPR-compliant EU data residency in early access, both recent additions rather than long-standing features.
A practical caveat worth flagging: LlamaIndex has been actively restructuring its SDK surface — the original llama_cloud_services package is deprecated as of a 2026 migration to newer llama-cloud packages for the same functionality. Nothing unusual for a fast-moving developer tool, but integration code written a year or two ago may need updating. For teams already invested in LlamaIndex's framework, LlamaCloud removes the operational overhead of self-hosting parsing infrastructure; for teams starting fresh and framework-agnostic, it's one of several credible options rather than an obvious default.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including LlamaCloud's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with LlamaCloud unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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