Laminar vs Opik

Laminar is an open-source, OpenTelemetry-native observability and debugging platform for AI agents. It traces LLM calls, tools, custom functions, and sub-agents as readable transcripts. Signals turn plain-language outcomes or failures into structured events across traces. Its debugger replays runs from cache to a selected point, while evaluations run against datasets locally or in CI to catch regressions. Laminar provides realtime traces, full-text search, raw SQL through its UI, CLI, or MCP, and custom dashboards. Integrations include OpenAI, Anthropic, Gemini, Cohere, LangChain, Pydantic AI, Claude Code, and Playwright. Deployment is available through managed cloud or self-hosting, including AWS or GCP with Helm charts. The Free plan is free with 1 GB data and seven-day retention. Starter costs $30 a month; Pro costs $150 a month.

Opik helps teams building applications or agents that call an LLM log actions and evaluate behavior across development, testing, and production. It captures and visualizes traces, supports annotation, and provides audit logs. Its evaluation tools include more than 30 metrics for outcomes such as answer relevance, context precision, task completion, and hallucination. In production, Opik can evaluate traces in real time, alert when criteria fail, and track token use and model costs. Test Suites offer pass/fail assertions, an Agent Playground supports end-to-end tests, and a Prompt Optimizer provides six algorithms. Core observability and evaluation features are available as open-source code for local use. Opik includes a REST API and Python client, with Python and TypeScript SDKs listed, and integrations with more than 40 frameworks, model providers, and gateways. Free Cloud allows up to 10 team members, 25,000 spans per month, and 60-day retention. Pro Cloud costs $19 a month and lists up to 50 team members and 100,000 spans monthly.