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LlamaIndex

RAG and agent framework with managed cloud

Consider with caveatsAPIFree tierSOC 2
Jack Phillips
Audited by Jack Phillips · Updated June 2026
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Overall score

3.8/ 5
SME fit3/5
usage-metered pricing + free tier
JTBD4/5
solid named JTBD
Integration4/5
API + 7 integrations
Trust3/5
growing, founded 2023
Quality5/5
4.6 on GitHub (36,000 reviews)
Compliance5/5
SOC 2 + GDPR + customer-choice residency

About

LlamaIndex is a Python and TypeScript framework for building RAG and agentic applications over private data, plus LlamaCloud for managed parsing, indexing, and extraction. It is best known for high-quality document parsing via LlamaParse.

Best for: Teams that need to ground LLMs in messy enterprise documents and want best-in-class parsing plus a flexible agent layer.

Pricing

  • Self-hosted (OSS)

    Monthly
    n/a
    Annual /mo
    Free
    Billing
    flat
    Notes
    Full framework;BYOK models and stores · MIT licensed core
  • Free (LlamaCloud)

    Monthly
    n/a
    Annual /mo
    Free
    Billing
    usage_based
    Notes
    1K free pages/day;Limited indices;Community support
  • Starter

    Monthly
    $50
    Annual /mo
    $50
    Billing
    usage_based
    Notes
    Higher page allotment;Production indices;Email support · Approximate usage-metered
  • Enterprise

    Monthly
    n/a
    Annual /mo
    n/a
    Billing
    seat_based
    Notes
    VPC deploy;SSO;Custom data residency;Dedicated support · Contact sales

Key features

  • LlamaParse for complex docs
  • Vector and hybrid retrieval
  • Workflow agents
  • Managed indices
  • Extraction templates
  • Broad vector DB support

Integrations

OpenAIAnthropicPineconeWeaviateQdrantSnowflakeS3

Trust & compliance

Stage range
Seed → Growth
Founded
2023
Status
active
SOC 2
yes
GDPR
yes
Data residency
customer_choice
External rating
4.6 on GitHub (36000 reviews)
Last verified
Jun 2026

Reviews

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