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Enterprise Layer Intelligence
Categories/APM & Observability/Laminar
Laminar

Laminar

Founded by Robert Kim

Open-source platform to trace, evaluate, and improve AI agents. Debug LLM calls, track tool use, and run evaluations on your AI applications.

Pricing model

Free trial, Paid

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Laminar to monitor and debug AI agents by tracing their execution, evaluating their performance, and analyzing failures. It provides full observability into agent behavior, captures browser recordings for web agents, extracts insights from traces using AI, and runs evaluations to catch regressions. You can query all platform data with SQL, create custom dashboards, and identify patterns in agent failures to improve performance.

What Laminar does

Trace AI agent execution step-by-stepDebug failed LLM calls with full contextEvaluate agent accuracy with custom metricsRecord browser interactions automaticallyCluster traces by failure patternsQuery trace data with SQL commandsBuild custom performance dashboardsRun evaluations on agent datasetsTwo-line integration with AI frameworksBrowser screen recording for web agentsAI-powered trace analysis and debuggingFull context trace visualizationAutomatic trace clustering by behaviorSQL queries across all platform dataCustom dashboard builderOpen-source with Apache 2.0 license

Pricing breakdown

Pricing model: Free tier, Paid

PlanList price
FreeFree
Hobby$25 / mo
Pro$50 / mo

Frequently asked

VercelVercelAnthropicAnthropicPostHogPostHogOpenAIOpenAILangChainLangChainKernelApps Private LimitedKernelApps Private LimitedSentrySentryRowsRowsGeminiGemini

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Laminar, AI agent observability, agent tracing, LLM debugging, AI evaluation, agent monitoring, trace analysis, AI agent performance, observability platform, agent development, AI debugging, trace visualization, AI metrics, agent failures, evaluation framework, AI testing, agent analytics