Govern AI that can act.
Enforcement Gap Review
In a complimentary 30-minute session, we identify which of three assurance questions your organisation cannot currently answer: does your control set satisfy the frameworks that apply to you, is it technically reliable, and can you evidence it.
Within 48 hours, you receive a written diagnosis mapped to your applicable frameworks, ready to share with your CIO, CRO, or audit committee.
Book Your Enforcement Gap Review
AI systems are moving from generating content to making decisions and taking action. Aivance tests whether your controls can reliably approve, block, or escalate those actions, and whether you can prove it under scrutiny.
01Who Aivance is for
Governance work is rarely proactive. Something changes, and the question becomes urgent.
You are putting AI agents or decision systems into production.
A regulator, board, investor, or enterprise customer is asking for evidence your controls hold.
Your AI governance exists on paper but has not been tested at runtime.
An AI pilot is stalled because risk, compliance, or oversight is unresolved.
This shows up most often in financial services and insurance managing MAS AIRG, MGF v1.5, and PDPA at the same time, and in technology and SaaS companies whose enterprise customers ask about AI governance before they will sign. CROs, CISOs, and enterprise architects are usually the ones who bring us in.
02What we assess
What most organisations already have
What few have
Every assessment starts by locating your controls on this line, then testing whether the ones on the right actually hold under pressure.
Why this matters now
A system that only generates output can be reviewed before anyone acts on it. A system that executes does not wait.
Yesterday
AI generated content
Output went to a person. A human read it, judged it, and decided whether to act. The model suggested. The organisation still decided.
Today
Every AI governance programme has three layers: policy, process, and enforcement. The enforcement layer is the part of your governance that can actually stop, limit, or escalate an action while the system is running, not just document it afterwards. By now the real question is not whether you have a third layer, but whether the one you have actually holds, and whether you can prove it.
01
POLICY LAYER
Documentation, oversight committees, regulatory frameworks
02
PROCESS LAYER
Approval workflows, post-hoc audits, monitoring dashboards
WHERE MOST GOVERNANCE PROGRAMMES STOP
03
ENFORCEMENT LAYER
Technical controls, deterministic control points, runtime guardrails
RUNTIME OUTCOMES
APPROVED
Executes within authority
BLOCKED
Prevented by control
ESCALATED
Held for human approval
03How we help
Each addresses a different starting point: the audit, the stalled pilot, or the override question from a regulator or board. Each produces specific, auditable outputs.
Diagnoses enforcement gaps across IMDA, MAS AIRG, PDPA, ISO 42001, and the EU AI Act, separating controls that exist on paper from controls that are technically real.
Diagnoses why each AI pilot stalled and designs the governance scaffolding that gets it to production.
Designs who holds the kill switch and what happens when they use it, including the Suspended Handoff State that halts an agent until a human ratifies.
04What you receive
The deliverables are concrete and auditable. You know exactly what you are buying before the work begins.
AI system inventory with risk rating
Every AI system mapped, each with a traffic-light risk rating against its actual authority to act.
Regulatory gap analysis
Your controls mapped to MAS AIRG, the IMDA Framework, ISO 42001, PDPA, and the EU AI Act, with paper controls separated from technically enforced ones.
Enforcement architecture
The technical controls and execution boundaries that close the gaps, specified at the level your team can operate.
Override authority design
Who can halt the system, and what happens when they do, including the Suspended Handoff State for high-risk decisions.
Prioritised remediation roadmap
The actions that close your gaps, ranked by risk and effort, so the sequence is defensible.
Board-ready executive summary
A non-technical summary written to be read by your CIO, CRO, or audit committee.
05Why Aivance
Most governance consultants come from legal, risk, or policy. Arjen comes from enterprise infrastructure: more than 30 years building large-scale systems, including nine years as Director of Advanced Consulting Services for Asia-Pacific and Japan at Akamai Technologies. That background is why Aivance can specify a control that is technically real, rather than one that is only procedurally described.
Featured insights
Singapore's updated Model AI Governance Framework includes over ten case studies. One of them, Terminal 3's payroll agent, shows what enforcement-layer governance actually requires technically. Here's what separates it from the others.
Read article →Most AI governance failures are not systems that misbehave. They are systems that proceed. The model produces output, the pipeline accepts it, the system executes, and no one ever explicitly granted that authority. Here is what governance looks like when it is designed rather than assumed.
Read article →Start with the complimentary 30-Minute Enforcement Gap Review. We identify which of three assurance questions your organisation cannot currently answer: does your control set satisfy the frameworks that apply to you, is it technically reliable, and can you evidence it. Within 48 hours, you receive a written diagnosis mapped to your applicable frameworks.
Book Your Enforcement Gap Review