Laminar

What is Laminar?

Laminar is an observability platform for AI agents that catches failures at scale and helps fix them. It captures LLM calls, tool calls, sub-agents, costs and tokens in a readable transcript view. It is open source under Apache 2.0, hosted on GitHub, and can be self-hosted.

Key capabilities of Laminar

• Tracing: captures LLM calls, tool calls, sub-agents, costs and tokens.
• Signals: analyzes runs to surface failure modes you did not define in advance, grouped into clusters.
• Slack alerts: notifies you of new failures and lets you ask questions about traces.
• Evals: turns error clusters into eval datasets to catch regressions.
• CLI and MCP server: give coding agents SQL access to investigate traces and verify fixes.
• Dashboards and search: custom SQL dashboards, full-text search, annotation and PII redaction.
• Browser session recording: screen recordings of browser agent sessions.

How Laminar works

You instrument your agent with a Laminar integration, and runs stream into the platform. Laminar groups similar failures into clusters, alerts you, and lets you convert clusters into evals. Self-hosting is available with Docker or with Helm charts on AWS or GCP.

Who uses Laminar?

Laminar is for engineers building production AI agents who need to see what agents did and why they failed. The vendor claims HIPAA and SOC 2 Type II compliance.

Laminar pricing

Laminar offers a Get started free sign-up. The home page does not describe plan names or prices, so see laminar.sh/pricing for current details. Because it is open source, self-hosting is also an option.

Laminar alternatives

AgentOps is a monitoring tool for agents that records sessions and costs. Traceloop builds on OpenLLMetry for tracing LLM applications with OpenTelemetry. Openlayer focuses on evaluation and testing of AI systems. Laminar stands out for clustering unanticipated failure modes and its open-source license.