What are Runtime Guardrails and how does Tumeryk use them?

Runtime Guardrails are controls designed to apply security and governance policies while an AI system or autonomous agent is operating.

AI assessment before deployment is important, but AI risk does not remain static. Models, prompts, retrieval sources, permissions, tools, application configurations, and agent behavior can change over time. Tumeryk therefore combines assessment with runtime enforcement and continuous governance.

Moving from assessment to enforcement

Tumeryk’s approach goes beyond identifying AI vulnerabilities.

Findings from AI testing, behavioral signals, risk assessments, and governance requirements can inform policies and controls that help organizations manage AI behavior during operation.

Runtime Guardrails can help address risks including:

• Unauthorized actions
• Excessive permissions or excessive agency
• Unsafe AI behavior
• Sensitive-data misuse
• Policy violations
• Agent actions outside intended governance boundaries

Runtime controls for Agentic AI

Runtime governance becomes particularly important for autonomous AI agents because agents may access enterprise data, invoke tools and APIs, communicate with other agents, and execute actions across enterprise systems.

Tumeryk’s Agentic AI Governance combines Runtime Guardrails with capabilities including:

• Agent Access Control
• Agent Observability
• Human Permission Enforcement
• Model Risk Audits
• Continuous governance

Together, these capabilities help organizations maintain visibility and control over what agents are permitted to do and what they actually do during execution.

Human authorization remains the boundary

Tumeryk’s Human Permission Enforcement adds an identity and authorization layer to agentic governance.

When an AI agent acts on behalf of a person, Tumeryk can help validate the permissions being exercised against those granted to the authorized human actor. This helps prevent agents from exercising authority beyond the person they represent.

Continuous AI governance

Runtime Guardrails form part of a broader continuous governance cycle:

Assess → Measure → Enforce → Monitor → Reassess

This allows organizations to combine pre-deployment testing with operational controls and ongoing monitoring rather than treating AI approval as a permanent, one-time decision.

Within Tumeryk’s broader Discover → Assess → Secure → Govern lifecycle, Runtime Guardrails help organizations move from understanding AI risk toward actively controlling it during operation.