LangSmith

LangSmith

LangSmith is a comprehensive platform for developing, testing, deploying, and monitoring AI agents. It provides observability and evaluation tools for debugging and improving agent performance, a managed deployment service for scaling agents, and Fleet for building no-code agents. Key capabilities include tracing, online/offline evaluations, dataset management, prompt engineering, and an LLM Gateway for cost and access control. It integrates tightly with the LangChain ecosystem (LangChain, LangGraph, Deep Agents) but is framework-agnostic, supporting any model provider. Targeted at AI developers, engineers, and teams building production-grade agentic applications, LangSmith offers a free tier for solo users with pay-as-you-go pricing for additional usage. It includes specialized services like Engine for automated issue diagnosis and Sandboxes for ephemeral code execution, catering to the complex needs of the modern AI development lifecycle.

Automation
Visit website
Added on
Sep 16, 2026
Monthly Visits
103.4K
Agent ObservabilityLLM GatewayNo-Code FleetAutomated DiagnosisManaged DeploymentSandboxed ExecutionPay-as-you-go
Product information

Everything worth knowing about LangSmith

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Agent Observability & Evaluation
Full-stack tracing, monitoring, and online/offline evals for debugging and improving AI agents in production.
Managed Agent Deployment
One-click deploy and manage long-running agents with horizontally-scalable serverless or dedicated infrastructure.
No-Code Agent Builder (Fleet)
Create agents for daily tasks using natural language and prebuilt templates without writing code.
Automated Agent Diagnosis (Engine)
Autonomously monitor traces, cluster failures, diagnose root causes, and generate code/prompt fixes.
Sandboxed Code Execution
Ephemeral, isolated environments for running agent-generated code with configurable TTLs and snapshotting.
Technical capabilities
Pay-As-You-Go LCU/LSU Metering
Usage-based billing via normalized LangChain Compute Units (LCU) and Storage Units (LSU) across services.
LLM Gateway with Cost Controls
Centralized proxy for managing LLM API keys, rate limiting, cost controls, and PII redaction across providers.
Must watch videos
Ultimate LangChain Crash Course for Developers 🔥
7:28:49
Tutorial7:28:49
Ultimate LangChain Crash Course for Developers 🔥
🚀 Welcome to the Ultimate LangChain Crash Course for Developers! In this comprehensive hands-on tutorial, you'll learn how to leverage LangChain, the powerful framework for building applications powered by large language models (LLMs) like OpenAI GPT, Llama, Mistral, and more. Whether you're new to LangChain or want to deepen your skills, this course covers everything from basics to advanced integrations. 👉🏻Code: https://github.com/entbappy/Latest-LangChain-LLMOps Topics of the video: 00:00:00 - Overview of LangChain, Evolution, and Learning Path 00:42:16 - Connecting with Leading LLMs (OpenAI’s GPT-4, GPT-4o Mini, and Open Source Models like Llama3 and Mistral) 01:24:58 - Prompt Templates for Integrating Logic into LLM Interactions 01:48:02 - Chains for Sequencing Instructions 01:57:49 - Output Parsers for Response Formatting 02:06:43 - Working with Custom Data (Data Loaders) & RAG Basic Concepts 02:50:15 - Different RAG Components like (Splitters, Embeddings, Vector Stores, Retrievers, Top k) 03:24:21 - Basic RAG Implementation with LCEL 03:45:14 - Memory Management in LangChain: Temporary and Permanent Memory 04:11:30 - Introduction to Langchain Expression Language (LCEL) | Chains and Runnables 04:36:41 - Built-in Runnables in LCEL 05:04:01 - Built-in Functions in runnables 05:09:40 - Combining LCEL Chains 05:15:34 - RAG demo with LCEL 05:20:45 - Comprehensive Overview of the LangChain Ecosystem 05:30:36 - LangServe Demo 05:49:40 - LangGraph Demo 06:17:55 - LangSmith Demo 06:34:32 - End-to-end Projects #LangChain #GenerativeAI #LLM #AI #Python #MachineLearning #LLMApps #LangChainTutorial #OpenAI #Chatbots #AIApplications #LangChainAgents #DeveloperCourse Check out my other playlists: ► MLOps Production Ready Machine Learning Project: https://youtube.com/playlist?list=PLkz_y24mlSJZvJOj1UXiJPVRQrNFdNEXX&si=yxL3EpwDcOslx3du ► End To End Data Science Projects Implementation: https://youtube.com/playlist?list=PLkz_y24mlSJaGcOXgJSuMM62sFha4fank&si=L0O96gFeduHCEVdi ► MLflow For Data Science | MLOps: https://youtube.com/playlist?list=PLkz_y24mlSJZrqiZ4_cLUiP0CBN5wFmTb&si=mOOoyy6gcNmG3IqS ► The Complete Self Driving Car Course: https://youtube.com/playlist?list=PLkz_y24mlSJawbZz-fJrrxZi0QNmJ5aP6&si=iC2PZhLG5Q5J3tF6 ► Object Detection Using YOLO v6: https://youtube.com/playlist?list=PLkz_y24mlSJY3H0WZGY2XKvuFdvkJS9oM ► Object Detection Using YOLO v7: https://youtube.com/playlist?list=PLkz_y24mlSJagh6O2MIrgI-Ki-t1rhjLI ► Sign Language Detection Using YOLO v5: https://youtube.com/playlist?list=PLkz_y24mlSJYWpwFbU8fyaBSwihoVHiJz ►ONNX (Open Neural Network Exchange): https://youtube.com/playlist?list=PLkz_y24mlSJZJx9sQJCyFZt50S4ji1PeR 😀Please donate if you want to support the channel through Buy me a coffee: https://www.buymeacoffee.com/dswithbappy This channel focuses on providing content on Data Science, Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, etc. in English. My mission is to provide inspiration, motivation & good quality education to students for learning and human development, and to become an expert in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural language processing, Generative AI, MLOPs, Python programming, and so on. #dswithbappy aims to provide unique & high-quality free education. I believe that high-quality education is not just for the privileged few. It is the right of everyone who seeks it. My aim is to bring quality education to every single student. All I need from you is intent, and a ray of passion to learn. Thanks! #dswithbappy Connect with me here: Telegram Group: https://t.me/+D-VqcrzSv5Q5Nzc1 Twitter: https://twitter.com/bappy913873 Facebook: https://www.facebook.com/groups/dswithbappy instagram: https://www.instagram.com/entbappy/ linkedin : https://www.linkedin.com/in/boktiarahmed73/ Github: https://github.com/entbappy 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 THINGS to support my channel LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL
Agentic AI Crash Course using LangChain | LangChain Crash Course
2:23:52
Tutorial2:23:52
Agentic AI Crash Course using LangChain | LangChain Crash Course
A complete crash course on agentic ai using langchain. This is also a course on generative AI. In this video, we will discuss theoratical foundations of generative AI and agentic AI. Langchain will be used for hands on programming. We will then build two projects (1) shopping agent (2) telecom RAG chatbot using langchain, chromadb, llama vision model, Qwen, gemini LLMs, streamlit, sqlite, huggingface and sentence transformers. Download the resources here: https://codebasics.io/resources/agentic-ai-crash-course No code agents: https://codebasics.io/ - Check "Our Live Cohorts" section Langgraph tutorial: https://youtu.be/CnXdddeZ4tQ Customer care support: https://youtu.be/Jekzc6BM5_w Workflow automation: https://youtu.be/QBI5bmbgL38 Check out OpenRouter: https://openrouter.plug.dev/6QpCcgh Codebasics AI Pro keeps you ahead of it: weekly tool tests, live build sessions, and AI you can actually apply at work: https://codebasics.io/ai-learning-for-professionals ⭐️ Timestamps ⭐️ 0:00:00 Intro 0:01:53 What is Gen AI 0:03:10 Traditional AI 0:05:41 Transformer Architecture 0:11:13 LLM Parameters 0:13:28 LLM Analogy Based Explanation 0:18:41 API Key Setup 0:21:01 Simple LLM call using LangChain 0:41:50 RAG Theory 0:47:52 Vector DB - Hands On 0:53:50 Rag - Hands On 1:02:54 AI Agent Intro 1:03:31 What is an AI Agent 1:10:18 ReAct Loop 1:10:49 AI Agent Hands on 1:21:28 Multi-Agent system 1:21:48 Multi-Model Agent theory 1:23:31 Multi-modal agent – hands on 1:29:28 Evaluation 1:34:07 Guardrails 1:36:41 Project 1 – Shopping Agent 2:06:57 Project 2 – Telecom RAG 2:22:46 No Code Agents Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses. Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website. 🎥 Codebasics Hindi channel: https://www.youtube.com/channel/UCTmFBhuhMibVoSfYom1uXEg #️⃣ Social Media #️⃣ 🧑‍🤝‍🧑 Discord for Community Support: https://discord.gg/r42Kbuk 📸 Codebasics' Instagram: https://www.instagram.com/codebasicshub/ 📝 Codebasics' Linkedin : https://www.linkedin.com/company/codebasics/ 📱 Dhaval's X handle : https://x.com/dpcodebasics ------ 📝 Dhaval's Linkedin : https://www.linkedin.com/in/dhavalsays/ 📝 Hem's Linkedin: https://www.linkedin.com/in/hemvad/ 📽️ Hem's Instagram for daily tips: https://www.instagram.com/hemvadivel/ 📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalcodebasics 🔗 Patreon: https://www.patreon.com/codebasics?fan_landing=true
Complete Agentic AI Course In 10 Hours- Langchain, Langgraph, RAG,Vectorless RAG, Guardrails,Evals
11:13:25
Tutorial11:13:25
Complete Agentic AI Course In 10 Hours- Langchain, Langgraph, RAG,Vectorless RAG, Guardrails,Evals
This is a complete course on learning Generative ai and agentic with Langchain and Langgraph. We have included all the topics from RAG, vectorless rag, Deep agents, Guardrails, LLM Evaluation and LLM Gateways Techniques Github Links Langchain : https://github.com/krishnaik06/Langchain-V1-Crash-Course Langgraph: https://github.com/krishnaik06/Agentic-LanggraphCrash-course RAG: https://github.com/krishnaik06/RAG-Tutorials Vectorless RAG: https://github.com/krishnaik06/RAG-Tutorials/blob/main/PageIndex_Vectorless_RAG_CrashCourse%20(1).ipynb Deep Agents: https://drive.google.com/file/d/1SVjvgqvKfF-FPAIqpEZdKMQLhe13NLFD/view Guardrails : https://github.com/krishnaik06/Langchain-V1-Crash-Course/blob/main/updatedlangchain/langchain_guardrails_crash_course.ipynb LLM Evals : https://github.com/krishnaik06/RAG-Tutorials/blob/main/1-rag_evaluation.ipynb LLM Gateways: https://github.com/krishnaik06/Langchain-V1-Crash-Course/blob/main/llm_gateway_tutorial.ipynb Timestamp 00:00:00 Introduction 00:02:31 Langchain Course 02:35:12 Langraph Course 05:02:29 RAG Course 07:10:43 Vectorless RAG 08:02:11 Deep Agents 08:45:43 Guardrails 09:22:55 LLM Evaluation 10:30:25 LLM Gateways ------------------------------------------------------------------- Learn from us visit https://krishnaik.in/liveclasses

Who uses it

Real use cases, no hype
AI Agent Development & Deployment
Build, test, and deploy complex, long-running autonomous agents using low-level control (LangGraph) or high-level templates.
Production Monitoring & Debugging
Trace, debug, and observe agent behavior in real-time to catch failures and understand execution flows.
Automated Evaluation & Improvement
Run online and offline evaluations, collect human feedback, and use Engine to automatically diagnose and fix recurring agent issues.
No-Code Agent Creation
Quickly prototype and deploy agents for daily tasks using natural language without writing code via Fleet.
LLM Traffic Management
Centralize and control LLM API calls with cost controls, fallbacks, PII redaction, and usage tracking via the LLM Gateway.
Secure Sandboxed Execution
Run and test agent-generated code in isolated, ephemeral sandbox environments with configurable lifetimes.
What's great
  • End-to-end agent lifecycle platform (build, test, deploy, monitor).
  • Deep integration with LangChain, LangGraph, and Deep Agents frameworks.
  • Comprehensive observability, tracing, and evaluation tools.
  • Managed deployment infrastructure for long-running agents.
  • Extensive ecosystem of open-source frameworks and community support.
Technical strengths
  • Framework-agnostic, works with any LLM provider.
  • Offers both cloud and self-hosted/hybrid deployment options for enterprises.
  • Includes specialized tools like Sandboxes (ephemeral compute) and Engine (auto-issue detection).
Where it falls short
  • Pricing can be complex with multiple metered components (LCU, LSU, traces).
  • Free tier limits are relatively low for serious projects.
  • Some advanced features (e.g., self-hosting, custom SSO) are locked to Enterprise.
  • Dependency on the LangChain ecosystem, though it's framework-agnostic.
  • Cost can escalate with heavy usage of compute-intensive services like Engine or Fleet.
Technical limitations
  • Rate limits and trace ingestion caps apply even on paid plans.
  • Self-hosted deployment requires significant operational overhead.
For technical folks

The deep-dive specs

Core Unit
LangChain Compute Unit (LCU)
Storage Unit
LangChain Storage Unit (LSU)
Fleet Models
Fast, Pro, Max performance tiers
Deployment Options
Cloud, Hybrid, Self-Hosted
Data Retention
Base (14d), Extended (400d)

FAQ

Includes technical Q&A
LangChain is the open-source framework for building agents. LangSmith is the paid platform for testing, deploying, monitoring, and improving those agents across their lifecycle.

Traffic Insights

Monthly Visits

103.4K

October 2026

Growth Rate

-0,2%

vs last month

Dominance

0%

in Automation

Top Country

—

Top Countries Breakdown

—

Growth Trend

Declining

Traffic has decreased compared to last month.

Honest pricing

No sneaky tiers, no “contact sales”

Here's who each plan is actually for — and where the hidden charges might hit.

Developer
Free

Individuals

  • Up to 5k base traces / mo
  • then pay-as-you-go. Community support. 1 seat.
Plus
Most picked
$39/mo

Teams

  • Up to 10k base traces / mo
  • then pay-as-you-go. Access to Deployment
  • Engine
  • and more. Add unlimited seats.
Enterprise
Custom

Enterprise

  • Self-hosted and hybrid deployment options. Custom SSO
  • ABAC
  • and RBAC. Support SLA. Custom seats and workspaces.
View Full Plans & Pricing on LangSmith

Official pricing, checkout, and plan upgrades are handled directly on langchain.com.

Reviews

What the internet actually thinks

Data refreshed weekly. No paid placements.

Trustpilot
Not reviewed yet
G2
G2
Not reviewed yet
C
Capterra
Not reviewed yet
Product Hunt
Not reviewed yet
COMMUNITY COMMENTS

Leave a Comment

Help others make informed decisions. Your honest feedback shapes the community's understanding of this tool.

Tips for commenting

  • •Be specific about features you used
  • •Share real use cases and results
  • •Mention both pros and cons
  • •Keep it honest and constructive
to leave a comment

Your comment is published immediately.

Filter:
Sort:

No comments yet

Be the first to share your experience with this tool.

Alternatives

Not quite the right fit?

Here's what else is out there.

Detail tags
Found via these searches
#AI#Agents#LLM#Observability#Evaluation#Deployment#AIDevelopment