Monitor Production LLM → Alert on Anomalies → Generate Incident Report
Automatically detect when deployed AI models start behaving unexpectedly and create detailed incident reports for engineering teams to investigate.
Workflow Steps
Goodfire Silico
Set up continuous model monitoring
Configure Silico to continuously analyze your production LLM's internal parameters and outputs. Set threshold alerts for when key neurons or attention patterns deviate significantly from baseline behavior.
PagerDuty
Create automated incident alerts
Integrate Silico's monitoring with PagerDuty to automatically create high-priority incidents when anomalies are detected. Include the specific parameter changes and affected model components in the alert details.
ChatGPT API
Generate incident analysis report
Use GPT-4 to automatically analyze the anomaly data from Silico and create a structured incident report including potential causes, impact assessment, and recommended investigation steps for the on-call engineer.
Workflow Flow
Step 1
Goodfire Silico
Set up continuous model monitoring
Step 2
PagerDuty
Create automated incident alerts
Step 3
ChatGPT API
Generate incident analysis report
Why This Works
Proactive monitoring catches issues before users notice them, while automated report generation gives engineers the context they need to quickly diagnose and fix problems.
Best For
MLOps teams managing production AI models that need immediate notification of behavioral changes
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