Monitoring
Add monitoring and observability so AI agents can be trusted in production.
Without visibility, teams end up guessing why quality falls, cost rises, or workflows break. Herb Trevathan helps businesses add the operational signals they need to manage AI systems with confidence.
Logging
Capture prompts, tool actions, and workflow outcomes cleanly.
Diagnostics
Inspect failure patterns, retries, and drift before they spread.
Alerts
Set thresholds for degraded quality, broken tools, or rising latency.
Reporting
Track health, efficiency, and reliability over time.
What gets measured
- Response quality and task completion success
- Tool failure rates and retry behavior
- Latency, token usage, and cost by workflow
- Escalation volume and operator interventions
Why it matters
Monitoring is not extra overhead. It is what makes AI systems manageable. Better observability creates faster troubleshooting, better optimization, and less business disruption.
Evaluating self-hosted model options before you deploy?
Use the Choosing a Model page to compare models by privacy, coding strength, speed, hardware footprint, and business fit.