Snowday AI

It’s harder than ever to get into college. Students and their families spend countless hours navigating complex application requirements. Forums, webinars, and activity fairs are overwhelming and often inaccessible without a private counselor.

Snowday is an AI copilot that matches students to enrichment opportunities based on their unique interests, learning styles, goals, and eligibility. Unlike static search platforms, Snowday provides ongoing, context-aware guidance in a conversational format.

It learns quietly in the background and improves over time. Students and counselors can focus on meaningful decisions, not sifting through endless options.

I designed the behavioral framework to build user trust in the AI system. I also created UX flows and wireframes for features like:

• “Reveal Why”: transparent explanations of AI recommendations
• “Fit Analysis”: at-a-glance matching scores based on student criteria
• “Edit Memory”: long-term personalization over years of use
• “Conversation History”: recalling prior guidance to support family discussion

To address trust and adoption barriers in AI for education, I implemented key design principles:

• Show Value Early & Often: in-context nudges highlight benefits
• Make It Transparent: clear rationale behind AI suggestions
• Learn Quietly: passive refinement without extra input load

Snowday has launched to over 200,000 users. I contributed directly to the design system and implementation of front-end CSS. The AI guidance system is currently in active development, shaped by continuous feedback from students, families, and counselors.