ELI
Learn

Laminar - Observability and Application Monitoring Tool

Observability and Application Monitoring · Founded by Robert Kim

Laminar

Laminar

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

Cost

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

PlanPrice10 seats / yr
Free$0
Hobby$25.00 / mo$3,000
Pro$50.00 / mo$6,000

Annual estimates assume continuous billing at the listed list price. Volume discounts typical above 50 seats.

Frequently asked

— Want a tailored answer?

See whether Laminar fits your stack — for real.

Techbible weighs Laminar against what you already pay for, your team shape, and the work that's actually happening. Free to start.

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