LangSmith vs Lunary
Side-by-side comparison of LangSmith and Lunary: pricing, features, API access, and community ratings.
LangSmith is the stronger choice if you're heavily invested in the LangChain/LangGraph ecosystem, offering zero-config integration and more sophisticated evaluation tools with built-in dataset management for regression testing. Lunary distinguishes itself with enterprise security certifications (SOC 2 Type II, ISO 27001) and self-hosting options via Kubernetes/Docker, making it better suited for organizations with strict compliance or data residency requirements. LangSmith offers a free tier while Lunary is paid-only, though both target similar observability and monitoring use cases. Choose LangSmith for tighter LangChain workflows and free experimentation, or Lunary when security certifications and deployment flexibility are priorities.
LangSmith The end-to-end platform for building, testing, and monitoring LLM-powered applications | ||
|---|---|---|
| Category | AI observability | AI observability |
| Pricing | Freemium | Paid |
| Starting price | USD 20/mo | |
| Free tier | ||
| Audience | Technical | All audiences |
| API available | ||
| Open source | ||
| Self-hostable | ||
| Model provider | LangChain (model-agnostic) | |
| Founded | 2023 | |
| Headquarters | San Francisco, USA | |
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