Build and deploy LLM apps with confidence

An all-in-one developer platform for every step of the application lifecycle.

An all-in-one developer platform for every step of the application lifecycle.



Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real-time with surgical precision.

Nested traces

Prompt-level visibility

Real-time insights

Playground mode

Website example
Website example
Website example

Test and evaluate

Software engineering relies on unit testing to build performant, production-ready applications. LangSmith  provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith.

Dataset curation

Evaluate chain performance

AI-assisted evaluation

Easy benchmarking


Given the stochastic nature of LLMs, it can be hard to answer the simple question: “what’s happening with my application?” LangSmith enables mission-critical observability with only a few lines code.

Application-level usage stats

Feedback collection

Filter traces

Cost measurement

Performance comparison

Manage Prompts

Prompts power your team's chains and agents, and LangSmith allows you to refine, test, and version them in one place. LangChain Prompt Hub makes it easier to discover and save successful prompts for any use case, so you don't have to start from scratch.

Prompt playground

Cross-team collaboration

Catalog of ranging models & tasks

Proven prompting strategies

Turn the magic of LLM applications into enterprise-ready products

Native collaboration

Bring your team together in LangSmith to craft prompts, debug, and capture feedback.

Works seamlessly with LangChain

Go from experimentation to production with one, unified toolkit.

Incorporate best practices

We’re not only building tools. We’re establishing best practices you can rely on.

Loved by Builders

“We give our learners access to LangSmith in our LangChain courses so they can visualize the inputs and outputs at each step in the chain. This observability helps them understand what the LLMs are doing, and builds intuition as they learn to create new and more sophisticated applications.”

Geoff Ladwig

Educator at DeepLearning.AI

“LangSmith has been great to build with, specifically adding observability and testing to complex LLM apps. It was easy to integrate and the agnostic open source SDK was very flexible so we could adapt it to our implementation.”

Richard Meng

Software Engineer at Snowflake

“As soon as we heard about LangSmith, we moved our entire development stack onto it. We could have built evaluation, testing and monitoring tools in house, but with LangSmith it took us 10x less time to get a 1000x better tool.”

Jose Peña

Manager at Fintual