From Blueprintto Kernel
One layer. Every model. Total control.
NINA defines the gaps. Nivara OS is deployable kernel software that routes model calls, enforces policy, and records audit evidence on‑premises, private cloud, or hybrid.
The Problem
AI Without Governance Fails
Without a kernel, AI governance becomes paperwork: inconsistent controls, unclear accountability, and audit gaps across every model and workflow.
Regulatory Risk
No runtime controls, no evidence trail, higher exposure to fines.
Inconsistent Risk
Each team implements policy differently; risk classification drifts.
Chief Purgatory
Security and compliance own outcomes, but lack enforcement authority.
Shadow AI
Staff bypass controls to ship work; unapproved tools proliferate.
The Solution
Three Pillars of Control
Nivara OS binds policy, routing, and evidence to every AI call—inside your environment.
Pillar 01
Runtime Enforcement
Evaluate policy before prompts, tool calls, and outputs cross boundaries.
Pillar 02
Model Routing
Select approved models by risk, cost, and latency; block everything else.
Pillar 03
Audit Evidence
Log who requested what, what policy applied, which model ran.
Architecture
Architecture in Three Layers
Three layers place control on the execution path: data boundaries, policy decisions, and evidence capture.
Foundation
Where data lives
Data stays in your estate; prompts and outputs are inspected before leaving on‑premises, private cloud, or hybrid.
Stack Placement
Components
Four Components. Full Control.
Four kernel modules configure behaviour, procedures, enforcement, and operator support, aligned to your NINA blueprint.
Meta-Guides
Versioned behavioural guides; every change diffable for review. Metric: 100% versioned.
SOP Library
Executable SOPs for regulated work. Metric: publish from template in <30 minutes.
Policy Engine
Runtime ruleset for prompts, tools, outputs. Metric: <10ms decision latency per call.
AI Copilot
Integration and test assistant. Metric: trace and remediation guidance in <2 seconds.
Compliance
Audit-Ready
from Day One
Controls are enforced at the kernel, not retrospectively. Every decision is logged with policy context, model choice, and data lineage, supporting AI Governance and assurance reporting.
AI Act
Data Act
Data Governance
GDPR
Validate Your Architecture
Map your current stack to an Enterprise AI Operating System. Identify routing gaps, policy gaps, and sovereignty risks. Leave with a kernel-first control plan.