CLIENTS

Some companies I worked for

CASE STUDIES

Where my expertise creates value

Selected engagements across product, organisation and strategy—each focused on turning complexity into meaningful outcomes. They show how evidence, structure and clear decision-making can create lasting value.

RANGE

Eight industries. One consistent finding.

Working across multiple industries has taught me that every domain comes with its own regulations, constraints, stakeholders and ways of working. Understanding these differences allows me to contribute quickly, ask better questions and make decisions that fit the context - not just the technology.

Core banking systems, treasury workflows and transactional logic across international markets. That includes cross-jurisdictional tax reporting platforms, cash and risk management systems, third-generation treasury software for financial institutions across Asia, and crypto savings and portfolio products. KYC processes, FIFO reconciliation, deal capture flows and capital markets logic are core working territory, not adjacent topics. In financial systems, usability has to coexist with transactional certainty, auditability, error prevention and regulatory constraints.

Human Factors, usability engineering and regulated environments. I know the difference between designing a product and designing under certification constraints — including ISO 62366 and IEC 62304, formative and summative evaluations, and the documentation standards required for regulatory submission. Familiar with the Johner Institut framework and what it actually takes to get a medical device through the process. In MedTech, usability evidence, risk controls and traceable design decisions can become part of the safety case itself.

Digital products across the full vehicle lifecycle — riders, dealers and R&D teams as simultaneous user groups, each with fundamentally different needs. Model year planning cycles, hardware/software dependencies, HMI, OTA pipelines, CCU architectures and PIM logic across markets in the age of SDV — including direct experience working for a globally leading OEM. Mobility products have to work across long hardware cycles, regional variants and dependencies between vehicle, software, cloud and dealer operations.

HMI systems, ergonomics and safety-critical workflows across heavy machinery and construction equipment. That includes operator interface design for track tamping machines and workplace ergonomics in rail maintenance, as well as display systems for construction machinery. Industrial environments require fundamentally different design logic than consumer products — where operator error has physical consequences, clarity and ergonomics are not a UX concern but a safety requirement.

Content production systems, learning infrastructure and the operational complexity behind large-scale educational platforms in enterprise environments where dozens of teams depend on the same system. Experience spanning early video learning platforms through to enterprise-grade content pipelines serving millions of users globally, and the structural challenges that come with systems that have outgrown their original architecture. At that scale, the biggest UX constraints often sit behind the learner interface — in workflows, dependencies, content operations and legacy complexity.

Mission-centric thinking and emerging technologies across complex operational environments. That includes the regulatory and certification effort behind autonomous systems, familiarity with SORA as the risk assessment framework for drone operations, and hands-on exposure to the software stack that runs them — MAVLink, PX4 and QGroundControl. Organizational ambiguity is the norm in this space, not the exception. Product strategy has to separate technical possibility from mission value, regulatory feasibility and commercial viability before engineering capacity is committed.

Recruiting platforms and AI-assisted hiring workflows. Early exposure to applied machine learning in HR contexts — sentiment recognition, confidence-scored candidate evaluation using SHAP values, and the behavioral shifts that emerge when both sides of a hiring process know they are being assessed by an algorithm. Here, model quality alone is not enough: explainability, perceived fairness and changed human behaviour become part of the product experience.

I’m familiar with high information density, expert users and workflows spanning multiple systems. I’ve learned that enterprise UX is less about starting from a clean slate and more about improving speed, clarity and error prevention within legacy constraints — without disrupting large, established user bases.