Laminar
Automatically trace, evaluate, and debug AI agents with real-time failure detection and clustering. Built for reliability and scalability.
Laminar is an open-source alternative to:
Open-source AI agent observability platform
Laminar is an open-source platform designed to help developers trace, evaluate, and debug AI agents in production. It automatically captures agent interactions, costs, and failures, providing actionable insights to improve reliability.
Key Features
- Automated Tracing: Capture LLM calls, tool invocations, sub-agents, costs, and tokens in a readable transcript view.
- Failure Detection: AI-powered Signals analyze every agent run to surface unexpected failure modes without manual configuration.
- Signal Clustering: Group similar failures into patterns for high-level insights and trend analysis.
- Real-time Alerts: Receive notifications in Slack about new failures and clusters.
- Debugging Tools: Use the CLI and MCP to query traces, replay checkpoints, and verify fixes.
- Cost & Performance Monitoring: Visualize agent costs and performance with heatmaps and detailed metrics.
- Integration-Friendly: Works with popular AI frameworks and tools for seamless adoption.
Tech / Self-Hosting
Laminar is open-source (Apache 2.0) and can be self-hosted. The platform supports Docker-based deployments and integrates with existing infrastructure. Documentation and setup guides are available on the official website.