LangSmith vs Phoenix by Arize

Detailed side-by-side comparison to help you choose the right tool

LangSmith

🔴Developer

Analytics & Monitoring

Tracing, evaluation, and observability for LLM apps and agents.

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Starting Price

Free
Full ReviewVisit Site

Phoenix by Arize

🔴Developer

Analytics & Monitoring

ML observability platform specialized for LLM applications, providing evaluation, monitoring, and debugging tools for AI agents in production.

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Starting Price

Free
Full ReviewVisit Site

Feature Comparison

Scroll horizontally to compare details.

FeatureLangSmithPhoenix by Arize
CategoryAnalytics & MonitoringAnalytics & Monitoring
Pricing Plans16 tiers24 tiers
Starting PriceFreeFree
Key Features
  • • Workflow Runtime
  • • Tool and API Connectivity
  • • State and Context Handling

    LangSmith - Pros & Cons

    Pros

    • ✓Best-in-class LLM tracing and debugging platform
    • ✓Deep integration with LangChain ecosystem
    • ✓Powerful evaluation and testing workflows for prompt development
    • ✓Dataset management for building evaluation harnesses
    • ✓Visual trace viewer makes debugging complex chains intuitive

    Cons

    • ✗Most valuable when used with LangChain — less useful standalone
    • ✗Paid plans required for team features and higher volume
    • ✗Data sent to LangSmith's servers — privacy considerations
    • ✗Can add overhead to development workflow

    Phoenix by Arize - Pros & Cons

    Pros

    • ✓Specialized for LLM applications with domain-specific metrics like hallucination detection and prompt drift analysis
    • ✓Open-source foundation ensures data privacy and customization flexibility for sensitive deployments
    • ✓Automatic instrumentation eliminates manual logging setup for popular AI frameworks
    • ✓Comprehensive evaluation suite covers both technical metrics and business outcomes for AI applications
    • ✓Strong visualization tools make complex AI behavior patterns understandable for non-technical stakeholders

    Cons

    • ✗Learning curve for teams unfamiliar with ML observability concepts and evaluation methodologies
    • ✗Limited integration ecosystem compared to general-purpose monitoring platforms like DataDog or New Relic
    • ✗Evaluation accuracy depends on quality of ground truth data and evaluation prompt design

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    🔒 Security & Compliance Comparison

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    Security FeatureLangSmithPhoenix by Arize
    SOC2✅ Yes—
    GDPR✅ Yes—
    HIPAA——
    SSO✅ Yes—
    Self-Hosted🔀 Hybrid—
    On-Prem✅ Yes—
    RBAC✅ Yes—
    Audit Log✅ Yes—
    Open Source❌ No—
    API Key Auth✅ Yes—
    Encryption at Rest✅ Yes—
    Encryption in Transit✅ Yes—
    Data ResidencyUS, EU—
    Data Retentionconfigurable—
    🦞

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    Ready to Choose?

    Read the full reviews to make an informed decision

    Review LangSmithReview Phoenix by Arize