Canonical normalization
Bring multiple observation layers into a consistent state before evaluating policy.
AI GOVERNANCE · SECURITY OPERATIONS FIRST
Control what AI does, before it does it.
AI agents and other AI systems are moving beyond answers to real-world actions. CYMAZE provides the control layer to make those actions visible, governable, and accountable before execution. WARDEN has six years of development behind it. The deterministic Go governance core, Grafana NOC, Electron control layer, human-in-the-loop controls and test harness are built; controlled testing continues and pilots are in preparation.
Policy-first execution Human oversight Evidence-linked decisions
CYMAZE / RUNTIME CONTROLILLUSTRATIVE
POLICY GATE / ACTIVEControl before execution
Observe the proposed action, normalize context, evaluate policy, then authorize or escalate.
01OBSERVEAI-proposed action
→02NORMALIZECanonical state
→03GOVERNDecision evidence
HUMAN OVERSIGHT AVAILABLEALLOW · DENY · DEFER
THE CONTROL POINT BETWEEN INTENT AND EXECUTIONSCROLL TO EXPLORE ↓
01 / THE CHALLENGE
Autonomy changes
the risk equation.
Traditional monitoring shows you what happened. Autonomous systems require decisions about what is allowed to happen next.
CYMAZE focuses on preventive governance: checking proposed actions against defined policies and keeping consequential decisions under accountable oversight.
01 / VISIBILITY
Perceive the situation.
Capture the proposed action and its operational context, rather than evaluating an AI system’s output in isolation.
02 / GOVERNANCE
Apply the policy.
Normalize observations into consistent state, then evaluate rules before execution is authorized.
03 / CONTROL
Act with accountability.
Allow, deny, defer or escalate actions to authorized humans, with decision evidence attached.
02 / HOW IT WORKS
From AI intent
to governed action.
One decision boundary separates what an AI system proposes from what it is permitted to execute.
Explore architecture ↗INPUT / 01
⌘
AI proposes
Action + environmental context
→
CONTROL POINT / 02
◈
Policy evaluates
Canonical state + governance rules
→
OUTCOME / 03
✓
Decision recorded
Allow · Deny · Escalate · Defer
Control flow overview. Deployment and validation details are available for technical review.
03 / CORE CAPABILITIES
Governance for systems
that take action.
Built around independent decision authority, human intervention when necessary, and traceable evidence.
Deterministic control
Enforce governance rules without relying on the AI model as the final authority.
Human-in-the-loop
Route sensitive or consequential decisions to authorized reviewers.
Evidence & traceability
Associate decisions with the context, policy, and outcomes that shaped them.
04 / INITIAL FOCUS
AI security operations first.
Broader AI governance.
Our first application is AI in security operations, where proposed actions intersect with critical systems, permissions and infrastructure. CYMAZE is an AI governance platform, not a cybersecurity product.
Our direction →01AI in security operationsINITIAL MARKET ↗
02Enterprise AI governanceSTRATEGIC SCOPE ↗
03Perception & situational awarenessSTRATEGIC SCOPE ↗
04Sovereign control environmentsDEPLOYMENT DIRECTION ↗
05 / INTERACTIVE DEMO
Explore the
demo.
Explore the interactive demonstration. Demo data is simulated; it does not establish production readiness or compliance certification.
CONTROL FRAME / ILLUSTRATIVE ● DEMO
01 / NORMALIZATIONContext assembled
02 / POLICY GATERule evaluated
03 / HUMAN OVERSIGHTEscalate if required
04 / EVIDENCEDecision trace
Illustration only · No live action execution06 / COMPANY BRIEFCYMAZE / WARDEN · ONE-PAGE OVERVIEWThe architecture.
The architecture.
At a glance.
A concise introduction to WARDEN’s perception, temporal-state and governance architecture, including its operating cycle and team contacts.
CYMAZE / WARDENGoverned Real-Time
AI Perception
AI Perception
01Perception
02Temporal State
03Governance
PERCEIVE → NORMALIZE → GOVERN
ARCHITECTURE & TEAMPDF ↗
BUILD WITH CONTROLMake autonomous AI
Make autonomous AI
accountable by design.
Talk to us about governing AI actions in your environment.
Discuss a pilot ↗