01 Vision
Right now most organisations are stuck between an AI ambition and a system anyone would trust with money, customers, or a regulator. I want to close that gap for good: technology that is governed, accountable, and actually live. Every engagement I take is a step toward that, turning a bold idea into a platform that ships, scales, and holds up under scrutiny.
02 Gratitude
I am grateful that the work in front of me is real. Not slideware: production systems, regulated environments, and people who have to live with the decisions. After 24 years across Australia, the UK, and Hong Kong, I still get to sit with founders and boards on the days the stakes are highest, and I do not take that access lightly.
03 Profile
I am Ronald Ng, founder and CTO of Profit Rise Consulting in Hong Kong. Day to day I design and deliver AI, cloud, and regulated fintech platforms, currently modernising a law firm's core workflows with governed, auditable AI. Before this I was an IBM program executive owning P&L and contract delivery, an enterprise architect for global OTT clients, and founder and CTO of an AI education platform. ISO 42001 Lead Implementer, CISSP, TOGAF, EMBA.
04 Service
I serve founders taking a platform from zero to one, boards and executive teams who need AI adoption to survive contact with governance, and regulated fintech and professional-services organisations in Hong Kong and across Asia answering to the HKMA, the SFC, and the PDPO. If that is you, and you want the idea live rather than debated, let's talk.
Start a conversationA record of platforms built, transformations delivered, and systems trusted with money, compliance, and scale.
Engaged to redesign core workflows for a professional law firm with AI, mapping high-effort manual processes to safe, auditable AI-assisted flows. Grounded in an ISO 42001 AI-management-system approach, so adoption comes with governance, risk controls, and clear accountability - not just tooling.
Founded and led the platform end to end: product vision, cloud-native AWS architecture, and full-stack delivery across iOS, Android, Spring Boot, Node.js, and PostgreSQL. Scaled to 100% weekly user growth while holding 99.9% availability with Terraform, CI/CD, and Grafana and Prometheus observability.
Acted as client CTO for signature Hong Kong organisations serving 100K members. Designed multi-year hybrid-cloud transformation across AWS and Azure, Zero-Trust security aligned to HKMA and SFC, and a 360-degree customer data platform.
Built the infrastructure and DevOps function from the ground up for an SFC-regulated digital asset platform. Architected resilient, secure AWS environments and custody systems on Zero-Trust principles, with 24/7 DR, BCP, and incident management for mission-critical trading and settlement.
As an IBM program executive in Hong Kong, owned P&L and contract delivery for financial-services clients. Led architecture teams delivering to global OTT clients, and across fifteen years architected US$60M transformation programs, managing HK$20M budgets and distributed teams of 80 with 20% cost reduction.
I publish the work, not just the claim. One artifact is the engineering, how an agent should reason and which model should do what. The other is the commercial case, a market, a build plan, and a costed model. Read them and judge for yourself.
A disciplined agent loop plus multi-model routing
Most agent failures are process failures, not model failures. model-mesh pairs a think / act / prove / grow loop, which makes a model define done, gather evidence, and verify by observation before reporting, with a routing system that assigns each agent role to a model family instead of using one model everywhere. It is deliberately model-agnostic: every provider name is a placeholder, and CI fails the build if a real vendor name is committed.
github.com/An agentic compliance platform for Hong Kong, argued in public
Hong Kong's company register passed 1.6 million companies in 2026, and every one of them owes an annual return, a business registration renewal, and a controllers register. This is the full case for automating that with agents: a product requirements definition, a 48-week phased build plan with quality gates, 72 task cards, and a finance model built from sourced vendor quotes with scenario and cash-runway analysis. Published as a planning package, not a shipped product, because the thinking is the deliverable.
github.com/More in the open, including a multi-agent communication protocol specified down to the schema with a formal Bell-LaPadula admission gate, and a fully self-hosted AI stack that runs with no SaaS dependency, at github.com/bughunt8.
From roadmap and emerging-tech evaluation to shipping production AI features, data pipelines, and full-stack applications. Some of what I have built and costed is published in the open.
Scalable, secure, cost-disciplined design across AWS, Azure, and hybrid, with infrastructure-as-code and reliability engineering.
Zero-Trust architecture and governance for regulated environments, aligned to HKMA, SFC, PDPO, ISO 27001, and PCI-DSS - and, as an ISO 42001 Lead Implementer, responsible AI-management systems.
Board advisory and executive training that turn AI ambition into adoption: operating-model change, governance, and workforce enablement, grounded in ISO 42001.
Translating business objectives into technology decisions for founders, CEOs, and boards, with hands-on delivery when it counts.
Perspectives on agentic AI, enterprise adoption, and what technology leaders should do now.
The chronology, for the record. Two decades across startups, enterprise, and global technology firms.
Independently verified
If you are a founder, a board, or a regulated team with an AI or platform ambition that has not shipped yet, that is the work I do. Bring me in as fractional CTO, advisor, or hands-on builder, and let's get it into production.
projects@ronald.ng
Connect an AI client to https://mcp.ronald.ng/mcp to query
my CV directly over the Model Context Protocol.