Case study · Consumer health AI
Control Health
Control Health connects a person's medical records, lab results, and wearable data in one place, adds an AI assistant that explains what any of it means in plain language, and turns that history into a lab panel built for them specifically. As primary product designer I owned onboarding, the health dashboard, the data hub, and the labs-ordering flow, the surfaces that decide whether scattered medical data becomes something a person can reason about.
The question underneath all of it: how do you make a decade of messy, incomplete, sometimes contradictory medical data feel like yours, clear enough to act on, without pretending to be a doctor?
Onboarding
Earn the connection before you ask for it.
Handing over a full medical history is the biggest ask, so onboarding shows the payoff before asking for a single connection. Records come first, since they're what make the answers about you, not the population.
Cold start
Design the empty state first, not last.
Records take time to arrive and the picture is never complete, so I designed the empty and partial states first. A baseline panel gives someone a place to start before anything syncs.
Dashboard & chat
Ask your own records a question, in plain language.
The assistant already holds your labs, records, and wearables, so the home screen opens with a plain question box. Informational, not diagnostic, with most of the care spent on what it won't answer.
Personalized panels
Every recommendation shows its reason.
Each suggested biomarker shows why it's there, pulled from your own data, so it reads as care, not an upsell. Rules, not a model, keep it reproducible and auditable.
Control
Add or remove anything, and the price updates live.
The full catalog is one tab away, everything is removable, and the total updates as you go. That control is what makes people comfortable keeping the markers that cost the most.
Closing the loop
From recommendation to booked draw, in one flow.
Checkout flows straight into scheduling, with nearby labs and real appointment times, so the loop closes inside the product instead of a handoff to a phone number.
Prep guide
Show up prepared, so the draw is right the first time.
A panel is only as good as the draw behind it. A prep guide walks each person through the night before and morning of, tuned to the tests they ordered, so nothing has to be redrawn.
Outcome
A working consumer-health product, live at controlhealth.ai, built to hold real clinical complexity and stay readable to someone with no medical training.
For a pre-launch product, the honest measure is what the design made possible: medical data a person can reason about, and a recommendation surface people trust because every line explains itself. The patterns underneath, for empty states, messy records, and traceable sources, will hold up as more data arrives.