01
Risk Register
Catalog AI-specific risks. Prompt injection. PII leakage. Hallucination. Cost overrun. Model drift.
Risk Register
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← Governance
ZENTINELLE
Catch the failure before it becomes the headline.
Identify, detect, respond, mitigate. Zentinelle brings control theory to AI risk — observability, controllability, and feedback loops that treat your AI systems like the dynamic systems they are, so problems get caught before they cascade.
AI systems fail in ways you haven’t imagined yet.
Prompt injection. Data exfiltration. Hallucination cascades. Model drift. Cost explosions. Credential leaks.
Traditional risk frameworks weren’t built for AI. They don’t account for autonomous systems that learn, adapt, and sometimes do things nobody expected.
Zentinelle treats AI as a system to be observed and controlled — not a checkbox to be filed.
AI-specific risks you need to manage:
- These aren't hypotheticals. They're happening now.
- Prompt injection — Malicious inputs that override system prompts
- Data exfiltration — Sensitive data extracted through carefully crafted queries
- PII leakage — Personal data in prompts or responses
- Hallucination — Confidently wrong outputs that look correct
- Cost explosion — Runaway token usage or compute costs
- Model drift — Behavior changes as models update
- Credential exposure — API keys and secrets in logs or outputs
Risk Capabilities
02
Anomaly Detection
Baseline normal behavior. Detect deviations. Alert on: Usage spikes (token consumption, API calls) Cost anomalies (unexpected spend patterns) Latency changes (model performance shifts) Error rate increases (failure patterns) Behavioral drift (output characteristic changes)
Anomaly Detection
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03
Incident Management
When policies are violated, Zentinelle creates incidents. Track: What happened (full context) Root cause analysis Remediation actions SLA tracking Post-incident review
Incident Management
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