LangSmith
LangChain platform for tracing, testing, and evaluating agent performance with production monitoring.
What LangSmith is for
LangSmith sits in the safety & observability category of the agent stack. Safety and observability tools are how teams ship agents without losing sleep: guardrails, evals, tracing, and monitoring for systems that act autonomously. As agents touch production data, this category moves from optional to mandatory.
Typical use cases
- Tracing and debugging multi-step agent runs
- Guardrails against prompt injection and unsafe outputs
- Continuous evals that catch regressions before users do
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FAQ
What is LangSmith?
LangSmith is a tool in the safety & observability category. LangChain platform for tracing, testing, and evaluating agent performance with production monitoring.
What is LangSmith used for?
Tools in this category are commonly used for: tracing and debugging multi-step agent runs; guardrails against prompt injection and unsafe outputs; continuous evals that catch regressions before users do.
What are alternatives to LangSmith?
Popular alternatives in the safety & observability category include Agent OS, AgentDoG, AgentGuard, agenttrace, APort Agent Guardrails. Compare them all on the Safety & Observability category page.
Alternatives & related in Safety & Observability
Agent OS
Kernel architecture for governing autonomous AI agents with policy enforcement.
AgentDoG
Diagnostic guardrails that analyze full agent execution trajectories to detect instruction hijacking and tool misuse.
AgentGuard
Runtime observability and guardrails for AI agents with loop detection and anomaly alerts.
agenttrace
Local-first TUI for AI coding agent session observability with tokens, cost, latency, tool failures, anomalies, reports, diffs, and CI health gates.
APort Agent Guardrails
Pre-action authorization plugin for agent frameworks with policy-based access control.
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