About
What is LangSmith?
LangSmith is a comprehensive AI agent and LLM observability platform designed to give developers complete visibility into their AI applications. It offers robust tracing capabilities to quickly identify failures and pinpoint issues affecting latency, cost, and response quality. The platform includes real-time monitoring dashboards for tracking performance metrics like token usage, error rates, and cost breakdowns, with configurable alerts. LangSmith also provides insights through automated analysis and clustering of traces to detect usage patterns, common agent behaviors, and failure modes. It supports various LLM frameworks and offers flexible hosting options, including managed cloud, bring-your-own-cloud (BYOC), and self-hosted solutions for data residency requirements.
Best used for
Ideal for developers and product managers who need to understand AI agent behavior, debug complex failures, and optimize LLM performance. Especially valuable for teams requiring real-time monitoring, cost tracking, and advanced evaluation capabilities to ship and scale agents in production.
Common actions
AI developmentAI toolsLLMperformance monitoringdebuggingMLOpsobservabilitytesting
Capabilities
Key features
- AI agent tracing
- Real-time monitoring
- Cost tracking
- Online evaluations
- Automated insights
- Flexible hosting
- API support
Target Audience
developerproduct managerstartup founder
Integrations
openai-sdkanthropic-sdkvercel-ai-sdkllamaindexopentelemetrypagerduty
Pricing & Plans
Freemium · Paid · Enterprise · Usage-based
FAQs
What is the difference between base and extended traces in LangSmith?
Base traces have a 14-day retention period and are ideal for quick debugging, costing $2.50 per 1k traces. Extended traces are retained for 400 days, include valuable feedback, and cost $5.00 per 1k traces, making them suitable for ongoing improvement and model tuning.
Can LangSmith be self-hosted for data residency requirements?
Yes, LangSmith offers managed cloud, bring-your-own-cloud (BYOC), and self-hosted options. For Enterprise plans, it can run on your Kubernetes cluster in AWS, GCP, or Azure, ensuring data never leaves your environment.
Will LangSmith add latency to my AI application?
No, the LangSmith SDK uses an async callback handler that sends traces to a distributed collector. This design ensures that your application's performance is not impacted, and agents continue running normally even during incidents.
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