ZENTINELLE

AI Risk

Identify. Detect. Respond. Mitigate. Before incidents become headlines.

AI systems fail in ways you haven’t imagined yet.

RISK MANAGEMENT

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.

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

Risk Register

Catalog AI-specific risks. Prompt injection. PII leakage. Hallucination. Cost overrun. Model drift.

Risk Register
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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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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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