Laminar

Free trial, PaidObservability and Application Monitoring

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

Founded by:

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.

Use Cases

Debug LLM calls in production AI applications

Track tool usage patterns in AI agents

Evaluate agent performance with custom metrics

Identify why web automation agents fail

Monitor token usage and latency across models

Analyze conversation flows in chatbots

Run regression tests on AI features

Extract failure patterns from agent traces

Replay browser sessions for debugging

Query historical agent performance data

Integrations

KernelApps Private Limited

Sentry

Rows

Gemini

Standout Features

Two-line integration with AI frameworks

Browser screen recording for web agents

AI-powered trace analysis and debugging

Full context trace visualization

Automatic trace clustering by behavior

SQL queries across all platform data

Custom dashboard builder

Open-source with Apache 2.0 license

Who is it for?

AI Engineer, Machine Learning Engineer, Software Engineer, AI Research Scientist, Data Scientist, Full-Stack Developer, DevOps Engineer, Product Manager