AI-Assisted Review Workstation
I defined human-AI interaction patterns for a review workflow that surfaced evidence, kept final judgment with people, and made decisions traceable.


- 10×faster reviews
- Humanfinal judgment
- Auditabledecision trail
These case studies document work from my time at Pearson VUE across enterprise SaaS, human-AI decision systems, remote proctoring, certification platforms, and specialized admissions tools. Each case explains the context, problem, research, design response, validation, and outcome. Start with AI-Assisted Review Workstation, or read them in any order.
I defined human-AI interaction patterns for a review workflow that surfaced evidence, kept final judgment with people, and made decisions traceable.


I defined human-AI interaction patterns for a validated proof of concept that helped candidates capture their environment, understand system feedback, and recover before an exam.


As founding designer, I led OnVUE from 0 to 1 and stewarded its experience across web, desktop, and mobile as the platform grew to serve 2.3 million exams annually.


As sole designer, I co-led a three-year North Star across learner, educator, professional, and administrator journeys, tested the multi-persona Figma prototype, and shaped a phased roadmap.


I redesigned a role-tiered asset marketplace and management platform for Microsoft, Amazon, and Apple programs, reducing administrator task time and clarifying a phased three-year product direction.


I designed the technical experience for an offline-capable, certificate-pinned tablet workflow spanning biometric capture, ID validation, local operation, cloud fallback, and recovery paths.

