Agentic AI onboarding with enforceable controls.
A structured onboarding lifecycle helps teams move autonomous agents from design to deployment with clear controls, traceability, and runtime accountability.
Design, implement, enforce, monitor.
The workflow maps agent threats to approved controls and carries those controls from architecture review into implementation and runtime enforcement.
Illustrative sample — not a live product screenshot.
Agent risk categories, scored and tracked.
Findings are classified by risk category, impact scope, and lifecycle phase so teams can prioritize remediation with confidence.
From approved threat model to runtime control.
Approved agent policies are generated, implemented, and continuously checked post-deployment to keep runtime behavior aligned with design intent.
Deployment gate
CI/CD agent deployment gates can block unsafe agents before they reach production.
Behavior monitor
Continuous verification closes the design-to-monitor loop against the approved policy.
SecureShift AI threat-models agents before deployment, generates runtime enforcement policies, and continuously verifies post-deployment behavior against approved controls.