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Knowledge & OpsFree plan + paid plans

LangSmith

Observability, evals, and deployment for LLM agents in production.

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What is LangSmith?

LangSmith is an LLM and agent observability, evaluation, and deployment platform from LangChain used by Klarna, Lyft, Gong, and Cloudflare. It provides step-by-step tracing of agent runs, real-time dashboards for tokens/latency/cost, online evaluations, Fleet management for production agents, and Sandboxes for safe code execution. SmithDB is a purpose-built store optimized for querying deeply nested traces.

Knowledge bases, internal search, operations, data, finance, HR, and back-office tools with AI workflows.

See the full Knowledge & Ops guide to compare more tools, buyer criteria, and related workflows.

Use cases to evaluate

Tracing a multi-step agent run to find which tool call blew up latency

Running online LLM-as-judge evaluators on production traffic to catch regressions

Deploying and managing a fleet of agents with versioned configs and rollouts

Spinning up sandboxes for agents to safely execute generated code

Fit to evaluate

Engineering teams already on LangChain or LangGraph

AI product teams running A/B tests on prompts and models

Regulated enterprises needing BYOC or self-hosted deployment

Platform teams managing many agents in production

Business fit

Right for you if you're shipping LLM-powered agents to production and need to debug long traces, score quality with online evaluators, and monitor cost and latency in dashboards. The framework-agnostic SDKs (Python, TS, Go, Java) mean you don't have to be on LangChain to use it. Skip if you only need tracing and prefer the OpenTelemetry-native, self-hostable economics of Langfuse, or if you're at very early prototype stage where free local logging is enough.

How to evaluate LangSmith

Use this category when operational data, policies, tasks, or internal requests are spread across disconnected systems.

Confirm the exact workflow

Map LangSmith to one concrete workflow first, such as tracing a multi-step agent run to find which tool call blew up latency. Avoid buying before the owner, trigger, output, and success metric are clear.

Check category fit

Compare internal search, permissions, workflow support, and reporting.

Compare practical alternatives

Shortlist LangSmith against Glean, Guru, Slite so the decision is based on fit, effort, and workflow ownership rather than brand recognition alone.

Validate cost and rollout effort

Developer $0/seat with pay-as-you-go (5,000 base traces/month free, then $2.50 per 1,000). Plus $39/seat/month (10,000 base traces included, $2.50 per 1,000 over; extended traces $5.00 per 1,000). Plus deployment runs $0.005 each, uptime $0.0036/min, Fleet runs 500 free then $0.05 each, Sandbox CPU $0.0576/vCPU-hour. Enterprise custom. Cloud, BYOC, and self-hosted options. Also confirm implementation time, support needs, and whether the medium setup matches your team.

Compare LangSmith with alternatives

Use this quick comparison before booking demos or moving data into a new system.

Primary workflowTracing a multi-step agent run to find which tool call blew up latency, Running online LLM-as-judge evaluators on production traffic to catch regressions
Best-fit teamEngineering teams already on LangChain or LangGraph, AI product teams running A/B tests on prompts and models
Implementation effortMedium setup and maintenance profile
Pricing checkFree plan + paid plans
Closest alternativesGleanGuruSliteSlab

LangSmith pricing

ModelFree plan + paid plans
SnapshotDeveloper $0/seat with pay-as-you-go (5,000 base traces/month free, then $2.50 per 1,000). Plus $39/seat/month (10,000 base traces included, $2.50 per 1,000 over; extended traces $5.00 per 1,000). Plus deployment runs $0.005 each, uptime $0.0036/min, Fleet runs 500 free then $0.05 each, Sandbox CPU $0.0576/vCPU-hour. Enterprise custom. Cloud, BYOC, and self-hosted options.
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Common questions about LangSmith

What is LangSmith?

LangSmith is an LLM and agent observability, evaluation, and deployment platform from LangChain used by Klarna, Lyft, Gong, and Cloudflare. It provides step-by-step tracing of agent runs, real-time dashboards for tokens/latency/cost, online evaluations, Fleet management for production agents, and Sandboxes for safe code execution. SmithDB is a purpose-built store optimized for querying deeply nested traces.

What is LangSmith used for?

Common use cases: Tracing a multi-step agent run to find which tool call blew up latency; Running online LLM-as-judge evaluators on production traffic to catch regressions; Deploying and managing a fleet of agents with versioned configs and rollouts; Spinning up sandboxes for agents to safely execute generated code.

How much does LangSmith cost?

Developer $0/seat with pay-as-you-go (5,000 base traces/month free, then $2.50 per 1,000). Plus $39/seat/month (10,000 base traces included, $2.50 per 1,000 over; extended traces $5.00 per 1,000). Plus deployment runs $0.005 each, uptime $0.0036/min, Fleet runs 500 free then $0.05 each, Sandbox CPU $0.0576/vCPU-hour. Enterprise custom. Cloud, BYOC, and self-hosted options.

Who is LangSmith best for?

LangSmith fits Engineering teams already on LangChain or LangGraph, AI product teams running A/B tests on prompts and models, Regulated enterprises needing BYOC or self-hosted deployment, Platform teams managing many agents in production. Right for you if you're shipping LLM-powered agents to production and need to debug long traces, score quality with online evaluators, and monitor cost and latency in dashboards. The framework-agnostic SDKs (Python, TS, Go, Java) mean you don't have to be on LangChain to use it. Skip if you only need tracing and prefer the OpenTelemetry-native, self-hostable economics of Langfuse, or if you're at very early prototype stage where free local logging is enough.

What are alternatives to LangSmith?

Common alternatives to LangSmith include Glean, Guru, Slite, Slab, Tettra, Sana.