LLM observability & evaluation · LangChain

LangSmith

Tracing, evaluation, and deployment platform for LLM applications, built by the team behind LangChain and LangGraph.

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LangSmith is LangChain's platform for tracing, debugging, evaluating, and monitoring LLM applications in development and production. It captures full traces of chains, agents, and tool calls (including from LangChain/LangGraph or any instrumented app), letting a team inspect prompts, intermediate steps, and token usage for a given run. Its evaluation side supports offline test suites, dataset-based regression testing, and human or LLM-as-judge scoring, distinct from the tracing/monitoring side that watches live production traffic. Usage is billed on LangChain Compute Units (LCU) and Storage Units (LSU) consumed by tracing, evaluators, and deployment, on top of a per-seat platform fee. Cloud, hybrid, and self-hosted/on-prem deployment are available on Enterprise plans; smaller teams use the hosted cloud service.

At a glance

Vendor LangChain
Pricing model Usage-based
Free tier Yes
Deployment Cloud, Self-hosted
Open source No
Best for Teams already building on LangChain/LangGraph that want tracing and evaluation from the same vendor.

Pricing

Free Developer tier includes a monthly trace allowance per seat, then usage-based charges for compute (LCU) and storage (LSU); Plus adds paid seats and deployment features; Enterprise is custom with self-hosted options.

Plan Price Notes
Developer $0/seat/month Up to 5,000 base traces/month, then usage charges; single seat; community support
Plus $39/seat/month Up to 10,000 base traces/month, then usage charges; unlimited seats; deployment and advanced features
Enterprise Custom Self-hosted/hybrid deployment, custom SSO/RBAC, support SLA

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • Full request tracing for chains, agents, and tool calls
  • Offline evaluation with datasets and regression test suites
  • Human annotation queues and LLM-as-judge scoring
  • Production monitoring dashboards and alerting
  • Prompt playground and prompt version management
  • Self-hosted and hybrid deployment on Enterprise

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

Langfuse Open-source LLM tracing and evaluation platform, available self-hosted for free or as a metered hosted cloud service. Helicone Open-source LLM observability platform that logs and analyzes requests via a proxy or async SDK, with a free-tier hosted cloud. Braintrust Evaluation-first platform for testing, scoring, and comparing LLM application changes, with production tracing built in. Portkey AI gateway that routes and load-balances LLM calls across providers while logging traces, prompts, and feedback for observability.

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Terms to know

Data observability Continuous automated monitoring of pipelines and datasets to catch freshness, volume and quality problems early. Machine learning Building models that learn patterns from data to make predictions or decisions, rather than following hand-coded rules. LLM observability Monitoring a language model's live behavior in production, tracking its inputs, outputs, latency, cost, and failure patterns. Distributed tracing Following a single request across multiple services in a distributed system to see where time was spent or an error occurred.

Related guides

How to choose an LLM observability tool Pick an LLM tool by whether you need tracing, scoring or a gateway first — most teams eventually need all three, rarely from one vendor.