Not because Singapore launched a framework.
Not because South Korea’s AI law went live.
Because METRIS arrived.
And honestly? The timing couldn’t be more poetic.
On the same day that governments finally admitted AI governance needs real infrastructure - not more PDFs - we shipped exactly that.
Let me explain.
What Happened on January 22
Singapore released the world’s first agentic AI governance framework. 27 pages of guidance on how enterprises should govern AI agents.
South Korea’s AI Basic Act became enforceable. Mandatory impact assessments. Documentation requirements. Fines for non-compliance.
Two major economies. Two different approaches. Same message:
The era of “we’ll figure out AI governance later” is over.
But here’s what caught my attention in Singapore’s framework:
“AI risk is no longer static, it is dynamic and behavioral.”
Finally. Someone said it out loud.
The Problem With Frameworks
Frameworks tell you what to do.
They don’t tell you how well you’re doing it.
“Implement human oversight” → But how do you measure if it’s meaningful?
“Assess and bound risks” → But what’s your actual risk score?
“Enable accountability” → But across which of the 9 regulatory frameworks that apply to you?
We’ve spent years collecting frameworks like Pokémon cards. EU AI Act. ISO 42001. NIST AI RMF. Singapore MGF. Korea AI Basic Act.
And yet - 94% of AI repositories still fail basic governance requirements.
We know this because we measured it. 2,000+ repositories. 1,429 checkpoints. 9 regulatory frameworks.
The market is drowning in frameworks.
What it’s starving for is measurement.
Enter METRIS
METRIS is what we’ve been building at Sanjeevani AI.
Not another framework. Not another checklist.
A quantitative risk score for AI governance.
Think of it like this:
Frameworks tell you to “be healthy”
METRIS is your blood pressure reading
Here’s what it does:
0-1000 Risk Score → Know exactly where you stand
1,429 Checkpoints → Mapped across 9 regulatory frameworks
Continuous Assessment → Not point-in-time audits
Bayesian Scoring + Monte Carlo Modeling → Because governance isn’t binary
The Singapore framework calls for “continuous monitoring” and “technical controls throughout the agent lifecycle.”
Great. METRIS is how you actually do that.
Why January 22
We could have launched any day.
But when we saw Singapore’s Davos announcement on the calendar, and Korea’s enforcement date landing the same day, we knew.
This was the moment.
Not to ride their coattails - but to draw a line:
January 22, 2026 is the day AI governance stopped being a conversation and started being infrastructure.
They wrote the frameworks.
We built the measurement layer.
What This Means For You
If you’re an enterprise deploying AI - especially agentic AI - here’s the reality:
Voluntary frameworks become market expectations. Singapore’s isn’t mandatory. It doesn’t matter. Your customers, partners, and investors will expect you to comply.
Mandatory requirements are cascading. Korea today. EU AI Act implementation ongoing. Others will follow.
“We’re working on governance” isn’t an answer anymore. The question is: What’s your score?
The enterprises that can answer that question - with data, not promises - will own the trust advantage.
One Ask
If you’re building AI and wrestling with governance, whether you’re trying to comply with frameworks, preparing for audits, or just trying to figure out where you actually stand, I want to hear from you.
Reply to this email. Tell me what’s broken. What’s working. What you wish existed.
I read everything.
January 22, 2026. Mark your calendars.
The day AI governance got a score.
Suneeta Modekurty
Founder, SANJEEVANI AI | Creator of METRIS
I resonate with what you wrote. The distinction between frameworks and real, measurable governance is so crucail. Finally, someone speaks about dynamic AI risk. Thank you for this insight.
Thank you, that distinction is exactly why we built METRIS. Frameworks tell you what to do, but not how well you're doing it. And static assessments miss the drift. Glad this resonated.