Kernel Interception
Intercept model calls, data access, and tool use at the kernel. Apply guards consistently across user-space services and third-party components.
Govern AI Before It Runs
Move from policy paralysis to controlled delivery. Responsible AI is the constitution layer for Nivara OS: Policy-as-Code, pre-event blocking, and audit trails for compliance and faster engineering.
Control stack section
Controls enforce Responsible AI policies pre-event.
Your audit trail shows what you prevented, not what you survived. Governance is engineering, not consulting.
Codify obligations
Encode EU AI Act Compliance, sector rules, and internal controls as Policy-as-Code with versioning, approvals, and clear applicability.
Solution
Define rules once, enforce everywhere. RAIN converts EU AI Act compliance and AI Governance requirements into Policy-as-Code with kernel enforcement, giving CISOs evidence and CTOs a clear path to deployment.
Benefits
Nina identifies obligations; Responsible AI enforces them inside the OS boundary through policies that block, allow, or route actions.
Intercept model calls, data access, and tool use at the kernel. Apply guards consistently across user-space services and third-party components.
Write policies as versioned rules with tests and approvals. Promote changes through environments, with traceable diffs and controlled rollbacks.
Block disallowed prompts, data egress, or actions before execution. Prevent violations; do not only report. Return deterministic outcomes: deny, redact, or escalate.
Align controls to EU AI Act, ISO/IEC 42001, NIST AI RMF, and internal standards. Produce mappings for auditors without vendor black-box assumptions.
Enforcement layers
Each layer applies a specific control function: guard, law, shield, record, judge, and standards. Together, they convert policy intent into deterministic enforcement.
Validate prompts, data sources, and tool requests against allowlists and sensitivity tags.
Compile Policy-as-Code and enforce decisions at kernel interception points, with scopes and ownership.
Filter outputs for data leakage, unsafe actions, and restricted content; apply redaction or truncation.
Write tamper-evident events for every decision, policy version, and override; support export for audits.
Evaluate drift, risk signals, and control performance; trigger escalation, throttling, or rollback.
Maintain control mappings to EU AI Act, NIST AI RMF, ISO/IEC 42001, and internal standards.