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What is LangSmith?
LangSmith is an AI agent and LLM observability platform built by LangChain, the company behind the popular LangChain framework. It solves the problem of understanding and debugging complex AI agent behaviors in production by providing complete visibility into agent execution traces. Core capabilities include tracing, monitoring, and insights. Tracing allows developers to see exactly what their agent is doing step by step, pinpointing issues related to latency, cost, and response quality. Monitoring provides real-time dashboards for tracking performance metrics like token usage, error rates, and cost, with online evaluations and alerts. Insights automatically analyze and cluster traces to detect usage patterns and failure modes. LangSmith is designed for teams building AI agents and LLM applications, from individual developers to large enterprises, and integrates with any LLM framework via SDKs for Python, TypeScript, Go, and Java, as well as OpenTelemetry.
AI Tool Review Summary
4.7/5
High, consistent, and on-brand
Clean and minimal
Observability and debugging for AI agents and LLM applications.
Works with any LLM framework via SDKs (Python, TypeScript, Go, Java) and OpenTelemetry.
Freemium with paid tiers
Features
Features with the highest value for users are highlighted here.
Agent tracing with step-by-step visibility
Real-time monitoring dashboards
Online LLM-as-judge and code evaluations
SmithDB purpose-built trace database
Unsupervised topic clustering and error analysis
Multi-framework support (OpenAI, Anthropic, LlamaIndex, etc.)
OpenTelemetry integration
Self-hosted and BYOC deployment options
Who Is It For?
AI Engineers
ML Teams
Product Managers
DevOps Engineers
Startups
Enterprise Teams
RAG Developers
Chatbot Builders
Research Labs
Freelance Developers
Pricing
Free
Up to 1,000 traces per month Basic monitoring Community support
Pro
Up to 100,000 traces per month Advanced monitoring Email support
Join the Command Staff.
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
Pros & Cons
Pros
Provides deep observability into complex agent behaviors with sub-second query performance. Flexible deployment options including self-hosted for data residency compliance.
Cons
Pricing can become expensive at high trace volumes for production use. Learning curve for teams new to observability concepts and the LangChain ecosystem.
FAQs
Just Launched
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