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LangSmith

AI Observability · Evaluated by Moneda AI

Teams building on LangChain who need tracing and evals

CategoryAI Observability

FromFree tier

Best forTeams building on LangChain who need tracing and evals

Wins0 of 2

What it’s for

  • LLM tracing and evaluation
  • Dataset and experiment workflows
  • LangChain/LangGraph ecosystem fit

Pricing

  • Free tier
  • Plus and enterprise plans

Job fit, data protection, and security

Sourced entity notes for buyers who need more than a feature list. Claims link to vendor docs — re-check before regulated or privileged use.

Deploymentcloud · self-host · hybrid

Data protection

Training on customer data
No, customer data is not used for training models.Sourcechecked 29 Aug 2026
Retention
Configurable data retention policies available; default retention tiers based on plan.Sourcechecked 29 Aug 2026
Residency
EU data residency available.Sourcechecked 29 Aug 2026

Security

Certifications / controlsGDPR compliant · ISO (via GCP Assured Workloads) · HIPAA (via GCP Assured Workloads)checked 29 Aug 2026

Would not choose if

  • Requires a low-code or no-code solution for LLM application development.
  • Lacks a solid understanding of LLM tools and DevOps processes.
  • Needs pre-built tests, drift detection, or runtime guardrails natively within the platform.

Where LangSmith appears — and how it did

vsLangSmith vs Arize (2026): LangChain Tracing or Broad AI Observability?Included2026-08-30best ofArize AI Alternatives: Find the Right LLM Observability PlatformIncludedn/a

LangSmith is evaluated on Moneda for buyer-job fit — not as a universal star ranking across unrelated categories.