
LangWatch
8.2#4 in ai agent observability toolsFrom €29 a monthFree planWebAPILinuxmacOS
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| Fact | LangWatch | PetalTrace |
|---|---|---|
| Deployment | LangWatch offers managed cloud, self-hosted, and hybrid deployment; its pricing page says self-hosting uses Docker Compose and the customer's ClickHouse. | The repository README documents building PetalTrace from source or downloading a release binary and running its daemon locally. |
| Integrations | Official integrations cover OpenAI, Anthropic, Google Gemini, Bedrock, Azure OpenAI, Vertex AI, Groq, Ollama and LiteLLM. | The MCP server lets AI agents query trace history, inspect prompts, analyze costs, compare runs, and trigger replays; the docs include Claude Code configuration. |
| Intended users | The company says the platform is for AI teams shipping agents and describes evaluation workflows for developers, product owners, QA, and domain experts. | The documentation describes PetalTrace as an observability platform for developers working with AI agent workflows. |
| What it does | LangWatch is an AI-agent engineering platform for testing, evaluating, observing, governing and improving agents across development and production. | PetalTrace captures AI workflow execution data, including LLM prompts and completions, tool calls, token use, costs, and timelines. |
LangWatch suits AI teams shipping agents, including developers, product owners, QA, and domain experts working on evaluation workflows. Teams can choose managed cloud, self-hosted, or hybrid deployment.
PetalTrace suits developers who need to inspect, compare, or replay AI agent workflow runs. It is especially relevant to teams using OpenTelemetry or PetalFlow, while its local deployment and disabled-by-default authentication matter when considering access needs.