Monitor, score, alert and root-cause analysis of AI misbehavior in real time.
Runtime guardrails tell you how it behaves with real users, real data and real attackers and let you control it.
Hexashield AI monitors live AI applications, scores their risk in real time, alerts security teams as they happen and traces misbehavior back to its root cause. What it learns at runtime feeds straight back into continuous red teaming, closing the loop between testing and production.
Once AI is live, every conversation is a potential attack and every response is a potential exposure. Most security teams have no view of what their AI is actually receiving and returning.
Live traffic includes adversarial inputs that were never seen in testing.
AI can leak sensitive data or produce misleading output in production.
Security teams lack visibility into AI inputs and outputs.
Without root-cause analysis, the same AI incident keeps happening.
Define and tune the policies that govern what your AI may accept and return, aligned to your business and compliance needs.
Continuous visibility into the inputs and outputs of production AI applications.
A live risk score for each AI application, so teams can see which ones are trending riskier.
Security teams receive alerts about risky behavior and threats as they happen.
Understand why the AI misbehaved, identify the underlying cause, and feed the findings into the next red-team cycle.
Set the rules for acceptable inputs and outputs for each AI application.
Hexashield watches production AI interactions continuously.
Each application carries a live risk score that updates as behavior changes.
Risky behavior triggers alerts and security teams are alerted to threats in real time.
Trace misbehavior back to why it happened.
Update guardrails and validate them through continuous red teaming.
A healthcare organization uses an AI assistant to help clinicians draft clinical documentation. It is live and used daily.
Runtime monitoring spots responses containing inaccurate clinical information, and separately an attempt to extract patient details. The application's risk score rises, an alert fires and the extraction attempt is alerted in real time.
Root-cause analysis shows the guardrail policy did not cover a particular retrieval pattern. The team updates the policy, Hexashield red teaming retests it, and the risk score returns to normal.
Risky AI behavior is caught and alerted in production, not discovered after the fact.
Every AI application carries a current, comparable risk score.
Root-cause analysis fixes the cause, not just the symptom.
Runtime findings strengthen every red-team cycle.
Real-time alerts for AI-specific threats.
Visibility into how their applications behave in production.
A live view of AI risk across the estate.
Evidence that production AI is monitored and controlled.
Monitor, score, get risk alerts and analyse risky AI behavior in real time.
AI Trust Infrastructure for secure, governed and accountable enterprise AI
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