AI PRODUCT DESIGN
Eye Care Dashboard (AI)
Helping chronic dry eye sufferers prepare for local conditions with AI-written daily guidance.
AI
Powered
API
Integration
Evidence
Base Logic
Summary
Industry: Healthcare
Product: AI-Powered web app
Timeframe: September to October 2026
Role: AI Product Designer
Team: Solo project
Tools: Figma, Wix Velo, OpenAI API, Claude Code
Deliverables: Interactive dashboard, AI-generated daily guidance, backend proxy
Background
I have chronic dry eye, and wind or temperature that feels like nothing to most people can leave me in real discomfort. Managing it has meant years of trial and error, especially when traveling or moving through allergy season without knowing what’s coming. I built this dashboard to read the day’s conditions ahead of time, so I can pack the right drops,
Dry eye affects an estimated 16 million adults in the US alone, and many more go undiagnosed. When I was first diagnosed, I had no idea how much daily conditions like wind, humidity, or heat would
Problem
Dry eye is hard to manage because it depends on constant, moving variables:
• Routines that shift depending on the day
• Protection like glasses and drops, used consistently
• Prescriptions, when required
• Environmental control, the hardest and least intuitive factor
That last one isn’t straightforward. Heat often helps, not hurts, by letting tear oils flow more freely, but push it too far without enough water and it turns against you. It’s a shifting balance, not a fixed rule.
This app turns that balance into a formula, with AI restructuring the guidance to fit the moment.
Solution
Years of researching the condition with an optometrist in Vancouver, and testing everything through online communities and my own recurring flare-ups, led me to a formula rather than a rule of thumb.
The dashboard scores five conditions daily: dew point (the true dryness signal, more accurate than relative humidity), wind (banded by speed, with an escalation when gusts spike or the air runs dry), temperature (a shallow U-curve, since both cold and heat carry real but limited risk), air quality, and pollen.
Each is weighted by how strongly it drives dry eye in the research, then combined so the single worst factor can’t hide behind several mild ones, the same principle behind the EPA’s Air Quality Index. AI then takes that math and turns it into encouraging guidance for the day.
