Projects.
Systems that shipped, got adopted, and kept running: fraud detection and forecasting for a global pharma finance function, risk intelligence for a central bank, and GenAI work of my own. Each one below opens into the problem, what I built, and what it changed.
157
automation projects delivered
12,000+
hours saved annually
8
markets in production
4×
Microsoft certified
Retrieval, generation, explainability.
Where the model output has to justify itself before anyone will act on it. The pattern is the same in a consumer prototype and an enterprise decision-support system: retrieve, generate, then show your reasoning.
One view where there were fifty-two.
Both of these were built inside Malaysia's central bank, on the same problem from two directions: risk that lives in scattered internal spreadsheets, and risk that builds in public conversation before anyone files a report.
Risk register consolidation and intelligence dashboards
52 manual departmental risk profiles digitised into one centralised SharePoint register with live Power BI dashboards, replacing a slow, paper-heavy reporting cycle.
5,000 hrs/year of analyst effort eliminated across 52 departments
Reputational risk monitoring platform
A multi-source social media analytics platform integrating LinkedIn, Facebook, Instagram, and Twitter APIs with NLP sentiment analysis and automated controversy flagging for reputational risk.
4 platforms unified into one real-time sentiment and controversy-tracking pipeline
Built once, run everywhere.
Finance systems that had to survive eight markets, each with its own currency, calendar, and reporting habits. Standardising the inputs was most of the work; the forecast was the easy part.
Robotics, before any of this paid the bills.
Coursework, not shipped work — kept separate from the case studies above on purpose. The engineering problems were still real: arm kinematics, and getting subsystems designed by seven different people to work as one machine.
157
automation projects delivered at AstraZeneca
The pages above are the ones worth reading end to end. They sit inside a much larger programme: Malaysia's first nationwide digital transformation, where my team upskilled 492 people and took 12,000+ hours of manual work out of the business every year.
The full history →