SYNC · Metabolic health app

SYNC pairs a wearable glucose sensor with a mobile app to help people manage their weight and stay ahead of type 2 diabetes. The sensor produces a constant stream of readings; the product’s job is to turn that stream into one simple answer a day: how is my body responding, and what should I do next?

I was the product designer across the whole surface, from stakeholder interviews and wireframes through mobile UI, the clinician-facing web dashboard, prototyping and testing.

Stakeholder interviews set the frame early. The medical side cared about time in range and glucose variability; users mostly cared about their weight and not developing the disease their parent has. Those are the same goal wearing different clothes, and the design job was to translate between them without showing users a wall of clinical numbers.

Testing early wireframes made the risk concrete: raw glucose charts read as medical equipment. People asked “is this number bad?” on nearly every screen. That question became the design brief. Every screen should answer it before the user has to ask.

The answer is a single daily metabolic score, sitting above the glucose curve and fed by meals, movement, fasting and sleep. The curve is still there for people who want depth, but the score does the interpreting. You log a meal, you watch what it does to your line, and the score quietly teaches you which foods your body handles well.

It launched deliberately as a “tentative” score: in its first days the app is honest that it’s still learning you, which tested far better than false confidence.

Onboarding earns the sensor. Pairing a wearable and granting health permissions is the highest-drop moment in any device-linked product, so onboarding was designed as a conversation: goals first, health background, then the sensor, with every error and empty state given a real screen instead of a toast.

The web dashboard serves the other audience: the coach or clinician looking after many users. Where the app hides clinical numbers, the dashboard leads with them, average and fasting glucose, high and low events, time in range, zone distribution, variability, hourly trends, and each meal’s glucose cost, all for one patient on one screen.

Same data, two honest views of it. The user gets a score; the expert gets the evidence behind it.

Moderated testing on the prototype validated the core bet: people who froze at a glucose chart could read the score instantly, and the “is this number bad?” question faded from later sessions. The workout redesign and the tentative-score framing both came directly out of testing rounds, which is the way I like a product to argue: with evidence.