Agents fail differently
They don't only crash. They hallucinate, lose context, call the wrong tool, and confidently return the wrong answer. You need more than logs to catch that.
Search through thousands of traces
Find the exact step where your agent went wrong. Filter by error type, model, user, time range.
Automatic failure clustering
Latitude groups similar failures into issues without you configuring anything. No rules, no regex.
Evals generated from real failures
Every discovered issue becomes a running eval. New traffic is tested against known failure modes automatically.
Monitor recurring failure modes effectively with issues
Project issues
4
1
Pending review
Monitoring
Regressing
User frustration
Escalating
Golden datasets
Human signal
Get started in minutes
Set up Latitude in your project and discover first issues in as little as
$
npx -y @latitude-data/claude-code-telemetry install
What's the difference between LLM observability and regular logging?
Do I need observability if my LLM app is already working fine?
How is Latitude different from Langfuse or other observability tools?
How quickly can I see my first production traces?
What issues will observability actually help me catch?
We're already using OpenAI's dashboard. Why do I need more?
Once I can see issues, then what?
