#66th of 13 in Observability
Latitude
Agent observability that groups failures and dispatches coding agents to fix them
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- Stars
- 4.7k
- License
- MIT
- Last commit
- Oct 2026
- Last release
- Oct 2026
Overview
Captures traces, sessions and tool calls via a one-line SDK (TypeScript, Python) or OpenTelemetry, groups failing traces into tracked signals, then dispatches Claude Code or Cursor with those traces to open a fix PR and replays fixes against regression datasets. The UI is also reachable from an MCP server and CLI; self-hosts from Docker Hub images via Compose or Helm. For teams operating agents in production.
Who it is for: Teams operating AI agents in production
Strengths
- Signals auto-group failing traces with status, size and trend
- Agent Dispatch sends sample traces to Claude Code or Cursor via Linear or webhooks
- Regression datasets replay fixes against the real failing traces
- MIT license; Compose and Helm paths plus Railway one-click
Weaknesses
- README quickstart targets the cloud; self-host steps are in external docs
- Automatic fixing depends on third-party coding agents and their subscriptions
- Claude Code session capture is a separate telemetry package
- Storage and service requirements are not stated in the README
What it needs
- no GPU
- Docker + Compose
- Compose runs PostgreSQL, ClickHouse, Redis
- Models: OpenAI, Anthropic, Bedrock, Vercel AI SDK and LangChain apps, any OpenTelemetry source
Also in Observability
See all 13| Rank | Project | Score |
|---|---|---|
| 1 | LangfuseTracing, prompt management and evals for LLM apps on ClickHouse | 74 out of 100 |
| 2 | PhoenixLLM tracing, evals, datasets and prompt playground built on OpenTelemetry | 74 out of 100 |
| 3 | promptfooCLI for evaluating and red-teaming prompts, agents and RAG | 71 out of 100 |
| #4 | MLflowTracing, evals, prompt registry and AI gateway plus classic ML tracking | 70 out of 100 |
| #5 | OpikTrace, evaluate and monitor LLM apps and agents, Apache-2.0 end to end | 64 out of 100 |