Laminar provides full-stack observability for AI agent workflows, combining distributed tracing, evaluation, and analytics in a single platform. With a single line of code, it instruments popular frameworks including Vercel AI SDK, LangChain, Browser Use, and direct OpenAI and Anthropic API calls. The OpenTelemetry-native architecture ensures compatibility with existing observability tools while providing specialized views for understanding LLM agent behavior, reasoning chains, and tool usage patterns.
The evaluation framework supports running evals both locally during development and in CI/CD pipelines for automated quality gates. Teams define events using natural language descriptions to track issues like hallucinations, logical errors, and custom behavioral patterns. The built-in SQL editor provides direct access to all trace and metric data, enabling custom queries and dashboard creation for monitoring agent performance trends and identifying degradation before it impacts production users.
Founded through Y Combinator S24, Laminar offers both a self-hosted deployment option for organizations requiring data sovereignty and a managed cloud platform at laminar.sh for simplified operations. The visual debugging timeline shows exactly what an agent did, what it was thinking at each step, and where things went wrong, dramatically reducing the time needed to diagnose and fix agent failures in complex multi-step workflows.
