In complex industrial environments, alarm systems are meant to guide operators toward timely decisions. In reality, they were doing the opposite — creating cognitive overload, delayed responses, and heavy reliance on support teams. I redesigned not just the screens, but how alarms function as a decision-support system.
Enterprise users weren't failing because of bad UI. They were failing because the system gave them answers, not guidance. I shifted the design paradigm from "AI as an answer engine" to "AI as a guided problem-solving partner" — reducing resolution time and support dependency.
Every customer request in a XaaS ecosystem triggers a chain of dependent actions across multiple stakeholders. The problem wasn't bad UI — it was a fragmented service supply chain with cascading delays. I reframed the challenge and introduced AI at the highest-friction points.
Contextual inquiry, diary studies, stakeholder interviews. I find the real problem, not the stated one.
Translating messy ambiguity into clear problem frames. Aligning design direction with business outcomes.
IA, mental models, user flows. Designing the skeleton before the skin — because structure is UX.
Low-fidelity concepts to high-fidelity interactive prototypes. I test assumptions before they become debt.
Building scalable, documented component libraries that give teams velocity without sacrificing quality.
Running design sprints, critiques, and stakeholder reviews. The best design decisions are collaborative ones.
I've spent 11 years learning that the best UX work is invisible. My practice lives at the intersection of user behaviour, business strategy, and system thinking — where a well-placed decision in a flow chart is worth more than a hundred polished pixels.