LangSmith vs Vellum

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

LangSmith

🔴Developer

AI Observability

LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.

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Starting Price

Free

Vellum

🔴Developer

Testing & Quality

LLM development platform for prompt engineering, evaluation, workflow orchestration, and deployment of production AI applications. Helps engineering teams build, test, and ship LLM-powered features with version control and observability.

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Starting Price

Free

Feature Comparison

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FeatureLangSmithVellum
CategoryAI ObservabilityTesting & Quality
Pricing Plans59 tiers8 tiers
Starting PriceFreeFree
Key Features
  • Tracing for any LLM stack via Python/TypeScript SDKs or OpenTelemetry
  • LLM-as-judge, code-based and pairwise evaluations
  • Versioned prompts with production A/B traffic splits
  • Prompt engineering playground with multi-model comparison
  • Automated evaluation and regression testing pipelines
  • Visual workflow builder for multi-step AI pipelines

💡 Our Take

Choose Vellum if you want an integrated prompt-to-deployment platform with visual workflow building and managed infrastructure. Choose LangSmith if your stack is built on LangChain and you need deep tracing and observability for LangChain-specific constructs. Vellum offers a broader development lifecycle; LangSmith offers tighter LangChain integration.

LangSmith - Pros & Cons

Pros

  • Best-in-class integration if you already use LangChain or LangGraph.
  • Eval suites are practical enough to actually gate releases on, not just dashboards.
  • Self-hosted Enterprise tier covers SOC 2 and regulated environments.

Cons

  • Per-trace pricing on Plus surprises teams that scale production traffic quickly.
  • Non-LangChain stacks work but trade ergonomic polish for SDK overhead.
  • Some eval features require additional LLM spend on top of the platform fee.

Vellum - Pros & Cons

Pros

  • Complete LLM development lifecycle in one platform — from prompt engineering through production monitoring
  • Automated evaluation pipelines catch prompt regressions before they reach users
  • Visual workflow builder enables complex AI pipelines without orchestration code
  • Model-agnostic approach supports OpenAI, Anthropic, Google, and other providers side by side
  • SOC 2 Type II certified with HIPAA compliance available for regulated industries
  • Strong API and SDK support (Python, TypeScript) for CI/CD integration

Cons

  • Learning curve for teams new to structured LLM development practices
  • Pro tier at $89/seat/month is higher than some competitors, and Enterprise requires custom sales engagement
  • Adds a dependency layer between your application and LLM providers
  • Workflow builder may be less flexible than code-first orchestration for very complex pipelines
  • Evaluation framework effectiveness depends on teams defining good test criteria

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🔒 Security & Compliance Comparison

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Security FeatureLangSmithVellum
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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