Laminar

Laminar is an open-source observability platform designed to trace, evaluate, and debug AI agents at scale.

Laminar provides observability for AI agents by capturing LLM calls, tool usage, sub-agents, costs, and token consumption. The platform includes a transcript view and a signal analysis system that clusters similar failure modes to help developers identify issues. Users can perform full-text searches, view traces, and utilize screen recordings for browser-based agents. The system supports integration with frameworks such as Vercel AI SDK, LangChain, and OpenAI SDK. Teams can host the software on AWS or GCP using Docker and Helm charts, with full SQL access provided for custom data queries.

Laminar at a glance

Best for: Software engineer
Runs on: Web, CLI, self-hosted
Pricing: Free plan $0/month; Starter $30/month; Pro $150/month; Enterprise custom pricing.
Released: August 2024
Category: AI coding tool
Website: laminar.sh

Key features

Automatic agent failure detection and clustering
Trace and transcript visualization for agent runs
Full SQL access to trace data via CLI and MCP
Screen recording capture for browser agents
Automated conversion of error clusters into evaluation datasets
PII redaction at scale before storage
Full-text search across span inputs and attributes

Use it for

Debugging agent failures in production
Creating evaluation datasets from trace history
Monitoring agent costs and token usage
Investigating agent behavior via SQL queries

Alternatives to Laminar

Tracely — Turns production failures into regression tests that block pull requests.
VoltAgent — Offers open-source flexibility with built-in supervisor agent orchestration and RAG.
OpenLIT — It enables comprehensive monitoring, evaluation, and management of AI agents via OpenTelemetry.
New Relic — Unified visibility across applications, infrastructure, and AI models.
OpenObserve — Full observability stack at a fraction of the usual storage cost
flightdeck — Monitor and control production and coding agents with real-time token budgets and kill switches.
Opik — It offers comprehensive tracing, automated evaluations, and open-source flexibility.
Limma — It answers queries with complete sets and proof instead of partial search fragments.
AgentOps — Track token usage, costs, and traces across 400 plus LLMs and agent frameworks.
MLflow — Complete observability and evaluation for production AI apps.
Raindrop Workshop — Provides real-time observability and self-healing evaluation loops for local AI agents.
Agent Beacon — Retains coding agent knowledge across tools so errors do not repeat.

All Laminar alternatives