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LlamaIndex
RAG and agent framework with managed cloud
Consider with caveatsAPIFree tierSOC 2
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
| Tier | Monthly | Annual /mo | Billing | Notes |
|---|---|---|---|---|
| Self-hosted (OSS) | — | Free | flat | Full framework;BYOK models and stores · MIT licensed core |
| Free (LlamaCloud) | — | Free | usage_based | 1K free pages/day;Limited indices;Community support |
| Starter | $50 | $50 | usage_based | Higher page allotment;Production indices;Email support · Approximate usage-metered |
| Enterprise | — | — | seat_based | 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
- MVP → Growth
- Founded
- 2023
- Status
- active
- SOC 2
- yes
- GDPR
- yes
- Data residency
- customer_choice
- External rating
- 4.6 on GitHub (36000 reviews)
- Last verified
- May 2026
Reviews
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