Laminar

Freemium

Open-source LLM observability built specifically for debugging long-running agents in production. Apache 2.0 licensed, OpenTelemetry-native. Where Langfuse is prompt-iteration-first and Braintrust is eval-first, Laminar is debugger-first — transcript view of agent runs, SQL over traces, agent rollout debugger, browser-agent session replay. The category leader for teams whose primary pain is 'why did this agent fail in production' rather than 'did this prompt change regress quality'.

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Pricing

Freemium

Type

Automation

Languages

Python, TypeScript

// VERDICT

Reach for Laminar when you want a lightweight, open-source trace + eval platform for LLM apps you can self-host. Skip it when you want a fully managed vendor, the largest ecosystem (LangSmith), or just prompt comparison.

Best for

An open-source platform for tracing, evaluating and analysing LLM apps - capturing runs and running evals to debug and improve quality, self-hostable.

Avoid when

You want a fully managed vendor, a mature large-ecosystem platform, or simple config-only prompt tests.

CI/CD fit

SDK tracing · self-host or cloud · eval pipelines

Languages

Python · TypeScript

Team fit

LLM app teams · OSS-leaning teams · Dev/QA debugging + evaluating

Setup

Medium

Maintenance

Low

Learning

Intermediate

Licence

Freemium

// BEST FOR

Open-source tracing of LLM app runs
Evaluation pipelines over captured data
Self-hostable, with a cloud option
Debugging chains/agents from traces
Analysing quality and behaviour over time
Lightweight setup for LLM observability

// AVOID WHEN

You want a fully managed vendor platform
You need the largest, most mature ecosystem
Simple config-only prompt tests suffice
You can't run/host the tool
You're not building LLM apps
Turnkey enterprise support is essential

// QUICK START

# self-host Laminar or use the cloud
pip install lmnr   # or npm i @lmnr-ai/lmnr
# instrument the app -> traces + eval pipelines

// ALTERNATIVES TO CONSIDER

Tool	Choose it when
Langfuse	You want a more established open-source platform.
Arize Phoenix	You want OpenTelemetry-based OSS observability.
LangSmith	You want a managed platform with a large ecosystem.

// FEATURES

Transcript view — read 2,000-span agent runs as a conversation, not a tree
Signals — natural-language extraction of patterns across trace history
SQL editor over the trace database for ad-hoc analysis
Browser-agent session replay alongside trace data
OpenTelemetry-native ingestion via OpenLLMetry or OpenInference

// PROS

Best-in-class agent debugging UX — finds failures faster than tree-based viewers
Apache 2.0 with one-command Helm self-host — every feature on the OSS image
Data-volume pricing tracks actual payload size, fairer for agent traces with many small spans

// CONS

Prompt-management workflow is lighter than Langfuse — treat that separately if it's a primary need
Newer than the alternatives; smaller community and fewer SDK integrations
No native LangGraph IDE — LangSmith remains stronger for LangChain-committed teams