Parse difficult files, extract structured fields, and build managed document indexes for AI workflows
Who should use this?
RAG teams processing complex documents and Schema extraction from varied business files.
Who should avoid it?
Sensitive files without an approved hosted-data path, Simple text PDFs handled well by cheaper parsers
What problem does it solve?
LlamaCloud is LlamaIndex's hosted document platform for parsing complex files, extracting schemas, and building searchable indexes for agents and retrieval applications.
Would I recommend it?
LlamaCloud earns a pilot when document preparation and retrieval quality—not the chat interface—is the binding constraint. Test the ugliest real files, validate every business-critical field against page evidence, isolate sensitive corpora, and compare cost per accepted document with a simpler parser before committing the index layer.
Advisor score
Premium review framework
LlamaCloud is LlamaIndex's hosted document platform for parsing complex files, extracting schemas, and building searchable indexes for agents and retrieval applications.
LlamaCloud earns a pilot when document preparation and retrieval quality—not the chat interface—is the binding constraint. Test the ugliest real files, validate every business-critical field against page evidence, isolate sensitive corpora, and compare cost per accepted document with a simpler parser before committing the index layer.
Build a frozen set of 300 permitted files spanning clean text, scans, tables, handwriting, diagrams, multi-column layouts, and malformed pages. Define field-level and citation-level gold labels. Compare LlamaCloud modes with the current pipeline on extraction F1, table fidelity, reading order, retrieval recall, citation accuracy, processing failures, p95 time, human correction minutes, exportability, and total credit cost per accepted document.
Personal Recommendation
LlamaCloud earns a pilot when document preparation and retrieval quality—not the chat interface—is the binding constraint. Test the ugliest real files, validate every business-critical field against page evidence, isolate sensitive corpora, and compare cost per accepted document with a simpler parser before committing the index layer.
Try the recommendation
Parse, structured extraction, and indexing in one service
Overall Score
Editorial Review Framework
Who should use this?
RAG teams processing complex documents, Schema extraction from varied business files, Developers wanting managed ingestion and retrieval.
Who should avoid it?
Sensitive files without an approved hosted-data path, Simple text PDFs handled well by cheaper parsers
What problem does it solve?
LlamaCloud is LlamaIndex's hosted document platform for parsing complex files, extracting schemas, and building searchable indexes for agents and retrieval applications.
Would I recommend it?
LlamaCloud earns a pilot when document preparation and retrieval quality—not the chat interface—is the binding constraint. Test the ugliest real files, validate every business-critical field against page evidence, isolate sensitive corpora, and compare cost per accepted document with a simpler parser before committing the index layer.
Overall Score
8.2
Ease of Use
8.0
AI Quality
8.2
Features
8.6
Speed
8.0
Integrations
8.4
Value for Money
8.0
Customer Support
7.6
Learning Curve
7.4
Recommended Because…
Parse, structured extraction, and indexing in one service
Scores use a 0-10 editorial scale. The source data is maintained as 5-point review dimensions, then normalized for reader-friendly comparison.
Reusable trial worksheet
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: RAG teams processing complex documents; Schema extraction from varied business files; Developers wanting managed ingestion and retrieval
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Complete three to five representative tasks with known acceptable outcomes and compare them with your current process.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: LlamaCloud uses credits across Parse, Extract, Index, and related processing, with a free allowance and paid credit bundles shown on its live pricing page. Charges vary by parsing mode, page volume, extraction configuration, indexing, storage, retrieval, and model work, so a single per-page headline is not a reliable total. Enterprise deployment, support,…
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.3/5; AI quality 4.1/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: Python, TypeScript, LlamaIndex, Google Drive, Microsoft SharePoint, Amazon S3
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Credit pricing requires workload-level measurement; Document accuracy still varies by class; Managed indexes increase data and portability dependencies
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Evaluation
Research-based
Price posture
From $0/month
Reviewed
2026-09-09
No authentic product screenshot is published for this review. DiscoverAI does not use generated interface images as product evidence.
LlamaCloud uses credits across Parse, Extract, Index, and related processing, with a free allowance and paid credit bundles shown on its live pricing page. Charges vary by parsing mode, page volume, extraction configuration, indexing, storage, retrieval, and model work, so a single per-page headline is not a reliable total. Enterprise deployment, support, security, and volume terms are quote-based. Record the live credit schedule and end-to-end job estimate before a production trial. Reviewed September 9, 2026.
Free plan: Yes. LlamaCloud offers a limited recurring free credit allowance suitable for representative document tests; sustained workloads consume paid credits.
Editorial freshness
Pricing and material product claims were checked September 9, 2026.
Community evidence
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
No approved community evidence yet. Be the first verified user to contribute.
LlamaCloud is LlamaIndex's hosted platform for parsing documents, extracting structured data, and building managed indexes for retrieval and AI agents.
No. LlamaIndex is an open-source framework, while LlamaCloud is a managed service that includes LlamaParse, Extract, Index, and hosted APIs.
LlamaCloud uses free and paid credits whose consumption varies by product, mode, pages, storage, retrieval, and model work; Enterprise terms are custom.
No. Teams should validate reading order, tables, fields, and citations against a labeled set of their hardest real documents.
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