Before AI
Governs Your
Operations,
Define Who
Governs AI.
AI is already making decisions in enterprise systems — recommending, routing, flagging, executing.
Without a governance layer, there are no defined boundaries, no cost controls, no audit trail.
Ariva AI designs the governance model. Arbiter enforces it.
You'll complete a short intake form. If aligned, you'll receive a private scheduling link.
The question is not whether your AI works.
The question is whether it stays governed as it scales.
The Governance Gap
Three problems every organization
ignores — until they can't.
No Decision Boundaries
AI is making operational decisions without defined approval rules. Who decides what AI can act on autonomously? Most organizations have no answer.
No Cost Controls
Every AI call has a cost. Spend drifts without attribution. Teams experiment independently. By the time someone notices, it's already a budget problem.
No Audit Trail
Compliance will ask which model made this decision, who approved it, and what it cost. Most organizations have no way to answer any of those questions.
Approach
Two Layers.
One Governance Model.
Ariva AI
The Governance Architecture
We work with your leadership to define how AI is allowed to operate: decision boundaries, approval chains, system access rules, cost controls, audit requirements.
The output is a governance architecture — not a vendor recommendation. It defines the rules Arbiter enforces.
Arbiter
The Enforcement Layer
Arbiter sits between your applications and your AI providers. Every request passes through it. Budgets enforce automatically. Models can be blocked or rerouted.
Dangerous outputs are intercepted before delivery. Every governance action is audited.
Ariva AI defines the governance model.
Arbiter implements the governance infrastructure.
This is the complete answer —
not half of one.
Start
AI Governance Review
For organizations where AI is already operating across systems. We examine your current AI footprint, map where governance is missing, and produce the governance architecture that Arbiter deploys.
What We Examine
- Which AI systems are operating and where
- What decisions they are making without defined boundaries
- Where costs are drifting without accountability
- What governance controls are missing
- Where risk is accumulating without visibility
What You Receive
- Decision boundary map for your AI use cases
- Governance gap assessment with priority ranking
- Arbiter governance blueprint — enforcement rules, budget controls, and guardrail configuration
- 90-day Arbiter deployment roadmap with onboarding milestones
We review a limited number of engagements at a time.
Request a Governance ReviewScale
Scale with Structure
For teams already deploying or expanding AI across systems.
AI Governance Audit
For teams already running AI across workflows. We map your AI footprint to Arbiter's governance modules — identifying which controls to activate, at what thresholds, and in what order.
- Active AI systems mapped to Arbiter's enforcement scope
- Decision authority and approval gaps
- Cost visibility and budget control thresholds
- Enforcement rules and override behavior
- Prioritised Arbiter module activation sequence
Governance Architecture Design
For teams scaling AI across operational systems. We design the governance model Arbiter enforces — and deliver the complete deployment architecture for full organisational rollout.
- Unified decision authority model
- System access and boundary rules
- Enforcement and change control framework
- Cost controls and accountability model
- Full Arbiter deployment and rollout plan
Every engagement leads to Arbiter. Consulting designs the governance model. Arbiter is how it gets enforced.
Fit
Who We Work With
Organizations that want to deploy AI with discipline — not just speed.
Strong Fit
- Adopting or expanding AI across operational or engineering systems
- Deploying AI coding tools (Claude Code, Cursor) at team or organization scale
- Concerned about decision accountability, cost control, and audit readiness
- Operating in regulated environments where AI governance is a requirement
- Want AI to remain controlled and accountable as adoption grows
Likely Not a Fit
- Looking for AI experimentation without operational governance
- Wanting a vendor to build and deploy AI tools for you
- Not ready to define approval, ownership, and accountability for AI decisions
If AI will influence operational decisions in your organization, governance is not optional — it is infrastructure.
Ready to Define the Rules?
Start with a private governance review.
If aligned, we'll recommend the right engagement path — consulting, Arbiter deployment, or both.
We review a limited number of engagements at a time.