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DeepEval-powered LLM evaluation platform to test, benchmark, and safeguard apps
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Trace, evaluate, and scale AI applications with minimal code.
Laminar provides automatic OpenTelemetry tracing, cost and token metrics, parallel evaluation, and dataset export for LLM apps, all via a Rust backend and SDKs for Python and TypeScript.

Laminar is a unified platform that brings observability, evaluation, and data management to AI applications. By leveraging OpenTelemetry, it automatically instruments popular LLM frameworks such as LangChain, OpenAI, and Anthropic, capturing inputs, outputs, latency, cost, and token counts with just a few lines of code.
The platform offers a Rust‑based backend that streams traces over gRPC for low overhead, stores metadata in Postgres, performs analytics in ClickHouse, and orchestrates processing via RabbitMQ. Users can run evaluations in parallel, export production traces to datasets, and visualize everything through built‑in dashboards. Laminar can be self‑hosted using Docker Compose for quick starts or a full‑stack deployment for production, and a managed SaaS version is also available.
Developers and teams building production LLM services gain deep performance insights, cost visibility, and a feedback loop for continuous improvement, all while retaining the flexibility of an open‑source, self‑hosted solution.
When teams consider Laminar, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Real‑time latency monitoring for a chatbot
Detect and alert on response slowdowns, reducing user‑perceived latency.
Cost analysis of multi‑model LLM pipelines
Track token usage and API spend per model to optimize budgeting.
Parallel benchmark evaluation of new prompts
Run thousands of prompt tests simultaneously, aggregating results in the dashboard.
Export production traces to a training dataset
Create labeled datasets from live interactions for continuous model improvement.
Install the Laminar SDK for your language, initialize with your project API key, and the OpenTelemetry instrumentation automatically captures calls; you can also wrap functions with the observe decorator.
The default stack includes Postgres for metadata, ClickHouse for analytics, and RabbitMQ for message queuing; you can customize the deployment but the components are tightly integrated.
Yes, Laminar offers a managed platform at lmnr.ai for quick onboarding without self‑hosting.
Yes, you can export traces to datasets and run evals on hosted or self‑uploaded datasets via the SDK.
Laminar is released under the Apache‑2.0 license.
Project at a glance
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