Kelvin Ung

Kelvin Ung builds live AI systems. He does not advise on AI. That distinction matters. The enterprise AI landscape is crowded with consultants who have studied the technology, evaluated the vendors, and published their frameworks. Kelvin has deployed the systems — production-grade, operating under real institutional load, in environments where failure carries real institutional consequences.

He has also done it as a founder. Kelvin globalised Liquidnet — the world's most successful institutional dark pool — understanding from the inside what it takes to take a market-defining business from traction to global scale. Globalising Liquidnet required the full stack: institutional relationships, security and compliance architecture that satisfied the world's leading financial institutions, and an operational model that could scale without compromising the standards that counterparties and regulators demanded.

That experience is the foundation of SQRT AI. Kelvin knows what accelerates a business in finance, fintech, and enterprise — and in the age of agentic AI, that knowledge translates directly into the platforms he builds and the transformations he leads.

Kelvin Ung's background is in institutional finance and fintech — building and operating technology to the security, compliance, and cyber risk standards that the world's leading financial institutions demand. That institutional-grade rigour is the foundation every SQRT AI deployment is built on.

The credibility signal most relevant to CISOs and regulated-industry buyers is Kelvin's background in institutional finance and fintech — and specifically, the security, compliance, and cyber risk standards he has operated to at the world's leading financial institutions. Those standards are not aspirational checklists. They are operational requirements enforced by independent audit, regulatory examination, and institutional counterparty due diligence that tests whether a technology partner's controls are real or cosmetic.

The current generation of vibe-coded AI solutions — built rapidly for speed-to-market without institutional security architecture — creates multi-vector attack risks for organisations operating in precisely the environments where those risks are most consequential: financial services, legal, compliance, and regulated data. An AI deployment that handles client data without proper isolation, audit trails, and access controls is not a productivity tool — it is a liability in waiting.

SQRT AI builds to institutional standards because those are the only standards that hold when they are tested. Every deployment Kelvin architects includes: data isolation by design, full audit trail capability, access control at the appropriate granularity, and security architecture evaluated against the threat models that sophisticated financial and legal institutions face daily.

Autonomous Prime is live: a unified AI-native deal management platform for private markets — agentic CRM, integrated data rooms, unified communications, and deal workflow automation in one system, operating under real institutional load with real clients. These are not proofs of concept. These are not demos. These are systems that operate autonomously within enterprise workflows today.

Governance credentials spanning SOC2, ITIL, ESG, and SDG frameworks — the same standards that regulated enterprises and institutional investors use to evaluate the organisations they work with. SOC2 is the security and availability standard enterprise buyers use to evaluate whether a technology partner can be trusted with their data. ITIL is the service management framework enterprise buyers use to evaluate whether a technology partner can deliver against SLAs.

The most durable competitive advantage from AI deployment is not headcount reduction — it is the intelligent redeployment of human capital alongside AI. The organisations that will outcompete across the next decade are the ones that use AI automation to elevate their people: eliminate the cognitive grunt work and redeploy that human capacity toward higher-value work that AI cannot yet perform.

SQRT AI works with COOs and executive teams to design and lead this transformation. The technology architecture and the people architecture are designed together, not in sequence. The output is an organisation that is genuinely more capable — not one that has automated its previous operating model and called it transformation.

Most organisations navigating AI transformation face the same structural problem: the decisions that determine whether the transformation succeeds — technology architecture, security posture, commercial strategy, AI implementation sequencing — require a calibre of experience that is rarely available in-house at the moment it is needed.

SQRT AI functions as your external CEO, CSO, CTO, and Chief AI Officer — a concentrated source of institutional finance, fintech, and enterprise AI expertise, deployed directly into your business. Not advisory frameworks. Not vendor recommendations. Practical implementation: the specific steps, sequencing, and solutions that will transform how your business operates, the revenues it can generate, and the margins it can sustain.