Skip to content
← All work

01 · Case study · Healthcare

My Glucose — Type 2 Diabetes

A day-to-day companion for living with Type 2 Diabetes — glucose, sleep, activity, meals and medication understood together.

My Glucose is a Type 2 Diabetes mobile experience. The design flow runs from onboarding and data permissions through a daily dashboard, logging for glucose, sleep, activity, meals and medication, insight and pattern cards, an AI assistant with visible evidence, medication reminders, daily routines, care-team and visit preparation, connected devices, and privacy and caregiver controls.

Role
To be added.
Duration
To be added.
Project type
Mobile app design
Users
People managing Type 2 Diabetes day to day, with caregiver access for the people who support them.
Status
Live
My Glucose — Type 2 Diabetes key interface

Outcome summary

To be added.

Open the live My Glucose site

02

Problem context

To be added.

03

Research insight

To be added.

04

History

To be added.

05

Geography

To be added.

06

Physics — how the product behaves

To be added.

07

Chemistry — the emotional layer

To be added.

08

Biology — repeated behaviour

To be added.

09

Mathematics — evidence

Task completion

Metric to be validated.

Time saved

Metric to be validated.

Research participants

Metric to be validated.

To be added.

10

Design engineering

  1. 01 · Discovery

    To be added.

  2. 02 · Problem framing

    To be added.

  3. 03 · Information architecture

    To be added.

  4. 04 · Wireframes

    To be added.

  5. 05 · Design system

    To be added.

  6. 06 · Prototyping & testing

    To be added.

  7. 07 · Handoff

    To be added.

11

STAR story

Situation

To be added.

Task

To be added.

Action

To be added.

Result

To be added.

12

Before & after

Before

To be added.

After

To be added.

13

My Glucose design flow

14

Final screens

DecisionOnboarding asks what kind of support the person wants, then connects data and permissions with an explicit explanation of how AI is used, so the dashboard opens on a home feed that already reflects their own data.
DecisionEvery insight names the data it considered and the evidence behind it, and states what is known and what is not, so an explanation can be trusted or questioned instead of taken on faith.
DecisionGlucose, sleep, activity and meals are logged in one place and read back as patterns with their history, and the person is asked whether a pattern feels useful — feedback that shapes what the product keeps surfacing.
DecisionThe assistant answers questions with AI controls the person can set, medication and routines are recorded and customised, and visit preparation, care-team access, data permissions, accessibility and account controls sit together.

15

Usability testing

To be added.

Numeric result: Metric to be validated.

16

Iteration

To be added.

17

Learnings

What I learned

To be added.

What I'd improve

To be added.

What I'd explore next

To be added.

Future opportunityTo be added.

18 · Final CTA

Want the deeper walkthrough?

Let’s TalkOther projects