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Tool Comparison

LangSmith

LangSmith

Debug, test, and monitor your LLM apps — full trace visibility for every run.

Free-Limited
VS
Evidently AI

Evidently AI

Open-source ML/LLM monitoring — data drift reports and quality test suites.

Open Source
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At a Glance

AttributeLangSmithEvidently AI
License / PricingFree-LimitedOpen Source
Typeaiai
GitHub Stars
Rating4.5/54.3/5
Key Features6 listed6 listed
Integrations5 listed5 listed
Categories
AI Observability
AI Observability

Key Features

LangSmith

  • Full trace visualization for every LLM call and chain step
  • Dataset management for evaluation benchmarks
  • Automated evaluators with LLM-as-judge
  • Prompt versioning and A/B testing
  • Production monitoring with latency and error tracking
  • Human annotation workflows for labeling

Evidently AI

  • Data drift detection across tabular, text, and embeddings
  • LLM evaluation metrics: faithfulness, relevance, toxicity
  • Interactive HTML reports for sharing with stakeholders
  • Test suites for automated data quality CI checks
  • Evidently Cloud for production monitoring dashboards
  • Supports sklearn, pandas, and any ML framework

Real-World Use Cases

LangSmith

Debug a hallucinating RAG pipeline

Add LANGSMITH_API_KEY to your environment

Evidently AI

Add ML model monitoring to CI/CD

Load reference (training) and current (production) data

Integrations

LangSmith

langchainllamaindexopenaianthropicpinecone

Evidently AI

mlflowwandbairflowkubeflowlangchain

🏆 Which should you choose?

Choose LangSmith if…

  • you want a managed or commercial offering with enterprise support and SLAs
Full LangSmith guide →

Choose Evidently AI if…

  • you need a fully open-source, self-hosted solution with no vendor lock-in
Full Evidently AI guide →