Laminar vs PetalTrace

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.

PetalTrace is an open-source observability platform for developers examining AI agent workflows. It captures prompts and completions, tool calls, token use, costs, and execution timelines, with a React web interface plus CLI, HTTP API, and MCP server access. Full prompt capture can include system prompts, message history, tool definitions, and model responses. Users can search prompt and completion text, compare runs for structural, content, and cost differences, and replay runs with changed models or temperatures or in mocked mode. The platform accepts standard OpenTelemetry traces, including from applications that do not use PetalFlow. PetalFlow integration adds graph topology, node inputs and outputs, and replay-capable snapshots. Trace data is documented as stored in SQLite, and the software can be built from source or run from a release binary as a local daemon. Authentication is described as future functionality and disabled by default. The public repository identifies an MIT license; no commercial pricing or usage limits are stated.