LangSmith vs PetalTrace
LangSmith
langchain.comPetalTrace
docs.petallabs.ioSide by side
| Figure | LangSmith | PetalTrace |
|---|---|---|
| Price from | $39/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 1 |
| Spec score · AI Agent Observability Tools | 9.1 (#4) | 8.4 (#11) |
| Deployment | Deployment provides managed or self-hosted agent servers with streaming, cron scheduling, authentication, MCP support and more than 30 API endpoints. | The repository README documents building PetalTrace from source or downloading a release binary and running its daemon locally. |
| Integrations | Documented integrations cover OpenAI, Anthropic, Bedrock, Gemini, Mistral, LiteLLM, OpenTelemetry, CrewAI, Vercel AI SDK, PydanticAI, AutoGen and many other frameworks and providers. | The MCP server lets AI agents query trace history, inspect prompts, analyze costs, compare runs, and trigger replays; the docs include Claude Code configuration. |
| Purpose | LangSmith is a commercial agent engineering platform for building, testing, deploying, monitoring, and improving AI agents. | PetalTrace is an agent observability platform for inspecting AI agent workflows and their execution lifecycle. |
| What it does | LangSmith is LangChain's framework-agnostic platform for observing, evaluating and deploying AI agents. | PetalTrace captures AI workflow execution data, including LLM prompts and completions, tool calls, token use, costs, and timelines. |
Plans
In their own words
LangSmith
LangSmith is a commercial agent-engineering platform for building, evaluating, deploying, monitoring, and improving AI agents. It supports offline evaluations on curated datasets and real-time scoring of production interactions. Evaluation methods include human review, heuristic checks, LLM-as-judge evaluators, pairwise comparisons, and custom Python or TypeScript evaluators. Annotation queues route runs to subject-matter experts for feedback that can calibrate evaluations, improve prompts, or augment datasets. The Playground compares prompt versions or model providers, and LangSmith chat can auto-improve prompts. Observability includes agent and retrieval tracing, token and general cost tracking, trajectory monitoring, online evaluations, and webhook or PagerDuty alerts. Traces can arrive through SDKs or an API from LangGraph, custom Python, or other stacks; SDKs are listed for Python, TypeScript, Go, and Java. Hosting ranges from cloud to hybrid and self-hosted Enterprise options. The Developer plan costs nothing, Plus costs $39 a month, and Enterprise pricing is custom.
PetalTrace
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.