Sold by: LangChain
Deployed on AWS
LangSmith provides tools for developing, debugging, and deploying LLM applications. It helps you trace requests, evaluate outputs, test prompts, and manage deployments in one place.
LangSmith is framework agnostic, so you can use it with or without LangChain open-source libraries langchain and langgraph.
Prototype locally, then move to production with integrated monitoring and evaluation to build more reliable AI systems.
LangSmith provides:
- Observability to see exactly how your agent thinks and acts with detailed tracing and aggregate trend metrics.
- Evaluation to test and score agent behavior on production data and offline datasets for continuous improvement.
- Deployment to ship your agent in one click, using scalable infrastructure built for long-running tasks.
4.7
Overview
LangSmith Observability and Evals is a unified observability & evals platform where teams can debug, test, and monitor AI app performance - whether building with LangChain or not.
Find failures fast with agent observability. Quickly debug and understand non-deterministic LLM app behavior with tracing. See what your agent is doing step by step, then fix issues to improve latency and response quality.
Evaluate your agent's performance. Evaluate your app by saving production traces to datasets, then score performance with LLM-as-Judge evaluators. Gather human feedback from subject-matter experts to assess response relevance, correctness, harmfulness, and other criteria.
Experiment with models and prompts in the Playground, and compare outputs across different prompt versions. Any teammate can use the Prompt Canvas UI to directly recommend and improve prompts.
Track business-critical metrics like costs, latency, and response quality with live dashboards, then get alerted when problems arise and drill into root cause.
LangSmith Deployments is a purpose-built infrastructure and management layer for deploying and scaling long-running, stateful agents -- offering:
- 1-click deployment to go live in minutes,
- 30 API endpoints for designing custom user experiences that fit any interaction pattern
- Horizontal scaling to handle bursty, long-running traffic
- A persistence layer to support memory, conversational history, and async collaboration with human-in-the-loop or multi-agent workflows
- Native LangSmith Studio, the agent IDE, for easy debugging, visibility, and iteration
LangSmith Agent Builder: Give every team the ability to build, use, and improve AI agents with the security your org requires.
Highlights
- LangSmith Observability and Evals is a unified observability & evals platform where teams can debug, test, and monitor AI app performance - whether building with LangChain or not. Quickly debug and understand non-deterministic LLM app behavior with tracing. See what your agent is doing step by step, then fix issues to improve latency and response quality.
- LangSmith Deployments is a purpose-built infrastructure and management layer for deploying and scaling long-running, stateful agents offering 1/1-click deployment to go live in minutes, 2/Horizontal scaling to handle bursty, long-running traffic 3/A persistence layer to support memory, conversational history, and async collaboration with human-in-the-loop or multi-agent workflows.
- Please note: there is a $150k annual Platform License plus a minimum $150k annual usage commitment to access this package. To discuss enterprise pricing or to activate your commitment and obtain your license key after signup, please contact us at https://www.langchain.com/contact-sales - alternatively, our self-serve cloud-based products are available at https://www.langchain.com
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LangSmith Helm Chart
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Linux
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/unit |
|---|---|
Per Trace | $0.01 |
Per Agent Run | $0.01 |
Metered Usage Amount | $0.01 |
Minimum annual usage commitment, billed in advance | $150,000.00 |
Per Agent Builder Run | $0.10 |
Vendor refund policy
https://www.langchain.com/terms-of-service#:~:text=Customer%20will%20pay%20LangChain%20all ,Fees%20paid%20are%20non%2Drefundable.
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Delivery details
LangSmith Helm Chart
Supported services: Learn more
- Amazon EKS
Helm chart
Helm charts are Kubernetes YAML manifests combined into a single package that can be installed on Kubernetes clusters. The containerized application is deployed on a cluster by running a single Helm install command to install the seller-provided Helm chart.
Version release notes
LangSmith 0.13.14 release
Additional details
Usage instructions
See https://docs.smith.langchain.com/self_hosting for full installation and configuration instructions.
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AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
Information Technology and Services
Great Abstraction for Prompting, Tool Calls, and LangSmith Observability
Reviewed on May 25, 2026
Review provided by G2
What do you like best about the product?
abstraction over manual prompting, tool calls and also observability via langsmith
What do you dislike about the product?
debugging is painful at times and performance overhead
What problems is the product solving and how is that benefiting you?
it provides me with an enhanced abstracted layer over basic prompting and tool calls
Telecommunications
Awesome framework for building ai products
Reviewed on Mar 10, 2026
Review provided by G2
What do you like best about the product?
Out of the box features that it provides to manage and monitor llm based applications
What do you dislike about the product?
Nothing in general, folks with no experience can get lost in the myriads of features it offers
What problems is the product solving and how is that benefiting you?
Helps with easy integration of RAG, must have for applications with changing ground truth thereby reducing the inherent issues of LLMs hallucinations, improving groundedness and truthfulness
Ramagiri S.
Effortless AI App Building with Powerful Integrations
Reviewed on Jan 13, 2026
Review provided by G2
What do you like best about the product?
Its ability to simplify building complex AI apps by connecting LLMs with data/APIs through a standardized, model-agnostic interface, saving significant time with ready integrations (RAG, memory, chains) and composable components, while offering powerful agent creation via LangGraph for control and observability
What do you dislike about the product?
I dislike LangChain because its heavy abstractions make the codebase unnecessarily complex, opaque, and difficult to debug. This often results in a sense of 'lock-in' and complicates the process of moving to production. Many criticisms center on its bloated dependencies, outdated documentation, and the performance overhead introduced by its wrappers. Additionally, it tends to push users toward its proprietary observability tool, LangSmith, instead of allowing for straightforward, Pythonic solutions. However, I do appreciate that its integrations make it easy to get started quickly.
What problems is the product solving and how is that benefiting you?
LangChain solves the problem of turning LLMs into real applications. It connects models with data, memory, tools, and reasoning workflows. It helps me build intelligent systems like document Q&A bots, RAG pipelines, and agentic AI instead of just simple chat interfaces.
Financial Services
Essential Framework for Building Robust Generative AI Applications
Reviewed on Dec 16, 2025
Review provided by G2
What do you like best about the product?
This framework is useful for building generative AI applications, especially when you need to utilize large language models, vector databases, retrieval mechanisms, and track the entire execution process.
What do you dislike about the product?
Nothing, it has only evolved to enable developers like us to develop robust applications
What problems is the product solving and how is that benefiting you?
This tool assists in developing AI applications, enabling us to utilize LLMs to obtain technical solutions that address business challenges.
Mirian P.
Great for agentic ai programming
Reviewed on Sep 21, 2025
Review provided by G2
What do you like best about the product?
The platform is easy to use, even if you only have a basic understanding of AI concepts. I found that navigating the features didn't require advanced technical knowledge, which made the experience straightforward and accessible.
What do you dislike about the product?
Sometimes, other frameworks appear to be simpler.
What problems is the product solving and how is that benefiting you?
I found that some integrations with cloud services were more straightforward and agnostic when using langchain.