Latitude

Latitude watches AI agents in production and closes the gap between noticing a failure and shipping the fix. Instead of leaving a wall of traces for somebody to read, it groups failing runs into tracked signals and hands them, with full context, to a coding agent.

Instrumentation is one line of telemetry. The TypeScript SDK wraps the LLM client an application already imports, Python and any OpenTelemetry-compatible runtime are supported, and traces arrive from OpenAI, Anthropic, Bedrock, the Vercel AI SDK, LangChain and other frameworks. A capture call at request, conversation or agent boundaries attaches user IDs, session IDs, tags and metadata.

The loop it runs has four stages.

• Observe: multi-turn sessions, tool calls and full execution paths captured as traces over OpenTelemetry ingest.
• Understand: failing traces grouped automatically into signals with status, size and trend, searchable semantically and open to annotation.
• Fix: Agent Dispatch sends Claude Code or Cursor the sample traces and a deep link, and the agent writes the smallest correct fix and opens a pull request.
• Verify: fixes are replayed against the real failing traces, with regression datasets, monitors and alerts to stop them coming back.

Everything available in the interface is also reachable from your coding agent through the MCP server and the CLI, and a separate package captures full Claude Code session transcripts as traces from the terminal, desktop app or IDE extensions. Self-hosting runs from published container images as a single-host Docker Compose instance, a Kubernetes cluster through a Helm chart, or a one-click Railway deploy.