Laminar
Open-source all-in-one platform for engineering AI products
Laminar launched on October 31, 2024 with 350 votes, #111 of 5,185 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
Laminar is an open-source platform designed for engineers building AI products with large language models. It enables users to trace LLM applications, run evaluations, label production data, and use those insights to improve prompts. Built in Rust with a modern tech stack, the platform emphasizes speed, reliability, and developer experience.
written from the facts on this page · September 2026
From the sources
Laminar is an open-source platform where you can trace your LLM app, run evaluations, label production data and use it to improve your prompts. Laminar is fast, reliable and offers best-in-class DX. It’s written in Rust and built on top of a modern tech stack.
Open-source platform to trace, evaluate, and debug AI agents. Laminar surfaces agent failures, and helps you fix them.
Laminar is an open-source agent observability platform. It automatically catches agent failures and helps you fix them. Laminar automatically captures LLM calls , tool calls , sub-agents, costs, and tokens, and shows it in a readable transcript view. Laminar Signals analyze every agent run to surface failure modes you didn't anticipate. Similar failures are clustered into distinct patterns to give you a high level overview. Signal clusters show the full distribution of your agent's failures and behaviors. Understand whether a newly reported issue has occurred before. The agent ran web_search three times for the same question, carried on past a 404 from fetch_page without retrying, then…from laminar.sh
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Laminar – Open-Source DataDog + PostHog for LLM Apps, Built in Rust2024 · github.com · ▲203Hey HN, we’re Robert, Din and Temirlan from Laminar (https://www.lmnr.ai), an open-source observability and analytics platform for complex LLM apps. It’s designed to be fast, reliable, and scalable. The stack is RabbitMQ for message queues, Postgres for storage, Clickhouse for analytics, Qdrant for semantic search - all powered by Rust. How is Laminar different from the swarm of other “LLM observability” platforms? On the observability part, we’re focused on handling full execution traces, not just LLM calls. We built a Rust ingestor for OpenTelemetry (Otel) spans with GenAI…
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