AiRysk gives teams a clear path from app discovery to conversational evidence to alert triage — without forcing analysts to reconstruct context by hand.
Without context, an alert is just noise. Effective governance requires understanding what actually happened.
Once understood, take action immediately. Escalate to the incident response team, revoke access to a specific shadow application, or dynamically assign the user to coaching.
Before you investigate a specific conversational incident, you need to understand the attack surface. AiRysk creates a dynamic inventory of both sanctioned platforms (like Enterprise ChatGPT) and unsanctioned shadow tools.
When an interaction breaks a rule (like sharing source code or PII), AiRysk doesn't just log "Rule Broken." It captures what was shared, the prompt used, and the model's response.
An investigation surface must serve multiple stakeholders. The way a SOC analyst views an alert is different from how a Privacy lead evaluates it.
Rule triggered. Risk score: 68%. Categories: pii, internal. Findings: 12.
Rule triggered. Risk score: 68%. Categories: pii, internal. Findings: 12.
Rule triggered. Risk score: 79%. Categories: pii, internal. Findings: 12.
The event logs contain redacted personal data and IP addresses, confirming the alarm about PII exposure is valid. No credentials were detected, and the redactions are justified.
Bring alarm context, severity, reasoning, and operational recommendations together. Reduce swivel-chair work between logging tools, ticket queues, and screenshots. Give security, privacy, and compliance teams a common artifact to collaborate around.
Determine if an external party compromised an account to extract sensitive models or data via AI wrappers.
Verify what personal data was exposed, to which AI vendor, and generate audit-ready documentation.
Let us walk you through a simulated alarm—from initial detection to conversational review and remediation.