Latitude

Latitude is an observability platform built specifically for AI agents. Standard logging catches crashes. It doesn't catch hallucinations, lost context, wrong tool calls, or confidently wrong answers. Latitude is designed to surface exactly those failure modes.

It sits in your production traffic, traces every step of your agent's execution, and automatically groups similar failures into issues without any manual rule configuration. No regex, no thresholds to tune. You review what it finds and validate.

Once you've confirmed an issue, Latitude turns it into a running eval that tests new traffic against that known failure mode continuously. Fix the bug, and you can verify the fix actually held.

Key capabilities:

• Automatic failure clustering groups similar trace failures into issues without configuration, surfacing patterns you'd miss in raw logs
• Eval generation from real failures means every confirmed issue becomes an automated check running against live traffic
• Golden datasets are built automatically from validated traces for each issue, giving you grounded test cases
• Human signal integration clusters user feedback into failure modes you can convert into evals
• Trace search and filtering lets you find the exact step where something went wrong, filtered by error type, model, user, or time range
• Custom alerts notify you when new issues appear or existing ones escalate across your preferred channel

Compared to general-purpose tools like Langfuse or Arize Phoenix, Latitude focuses on the full loop: detect, validate, eval, monitor. It's not just a trace viewer. The automatic issue discovery means you don't need to know what to look for before you can find it.

It's a practical fit for teams running AI agents in production who need more than dashboards, and want failures turned into repeatable tests rather than one-off investigations.