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LangSmith offers the deepest observability into LLM applications with end-to-end tracing, evaluation datasets, and production monitoring that integrates seamlessly with the LangChain ecosystem.
LangSmith helps developers trace, evaluate, test, and monitor applications built with language models and agent workflows.
LangSmith helps developers trace, evaluate, test, and monitor applications built with language models and agent workflows.
LangSmith provides tracing, evaluation, testing, and production monitoring for LLM and agent applications. See enhancedDescription for the full researched review.
LangSmith is the obvious pick if you live in the LangChain ecosystem and want one product for tracing, evals and prompt management — evaluate Langfuse first if self-hosting is non-negotiable.
Token-level cost, latency and payload capture for every LLM call, tool use and retrieval.
LLM-as-judge templates, deterministic code checks, pairwise comparisons and human review queues.
Version prompts independently of code, ship A/B splits in production, let PMs iterate without redeploys.
Promote interesting traces into datasets and run regressions on every PR.
Enterprise add-on for managed agent deployment, persistence and human-in-the-loop workflows.
Manual verification required
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We believe in transparent reviews. Here's what LangSmith doesn't handle well:
AI agent testing automation with synthetic data generation and regression detection.
LangSmith has expanded integration with LangGraph Platform for deploying agent workflows, and added deeper support for evaluating multi-agent systems including trajectory-based evaluators. The platform also continues to expand OpenTelemetry support, making it easier to instrument applications outside the LangChain ecosystem, and offers EU data residency for European customers.
The standalone paid guide is not available to purchase.
Use our existing overview and feature information to evaluate LangSmith.
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Pricing and features change often. If anything on this LangSmith page is wrong or missing, tell us and include a link to the source. We review every correction.
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