Glossary · AI & Agents
LangSmith
Overview
What LangSmith Is
LangSmith is a developer platform, built by the team behind LangChain, for debugging, testing, evaluating, and monitoring applications that use large language models. It gives you full visibility into what an AI app actually does at each step—essential because LLM behavior is probabilistic and hard to inspect with traditional logging. It works with LangChain apps and framework-agnostic ones alike.
Key Capabilities
Its core feature is tracing: LangSmith records every prompt, model response, tool call, and retrieval step in a run, so you can pinpoint where an answer went wrong or where latency piled up. It also supports evaluations—scoring outputs against datasets or LLM-based graders—plus prompt versioning and production dashboards for cost, latency, and error rates.
Why It Matters for Business
Shipping an AI feature without observability is guesswork; a chatbot or RAG assistant can look fine in a demo and fail on real questions. We use tools like LangSmith when delivering AI Agents, AI Chatbots, and RAG development so quality is measured, not assumed—catching regressions before users do and keeping ongoing costs transparent.
Where we use it
Related Zen in Tech services
How our team puts LangSmith to work in real projects.
FAQ
LangSmith — common questions
Is LangSmith free?
LangSmith has a free Developer tier for individuals with a monthly trace allowance, then paid plans priced per seat and per traced event, plus a self-hosted enterprise option. You do not need to use LangChain to use LangSmith.
LangSmith vs LangChain—what's the difference?
LangChain is an open-source framework for building LLM applications; LangSmith is a commercial platform for observing, testing, and monitoring them. They're complementary, and LangSmith can trace apps built without LangChain too.
Do I need LangSmith for a small AI project?
Not strictly, but even small projects benefit from tracing when answers are inconsistent. Many teams start on the free tier to debug prompts and only upgrade once the app reaches production and needs monitoring.
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