Aeri

Diabetes treatments today are reactive

Health tools provide constant data, but diabetes management still depends heavily on the individual. Users must interpret readings, track patterns, and repeatedly check devices throughout the day.

With sensors that require routine replacement, care becomes a cycle of monitoring, maintenance, and reaction. This revealed an opportunity for a more preventative and supportive experience.

More than 1 in 10 adults worldwide are living with diabetes (International Diabetes Federation). Its scale reflects a growing need for tools that better support the ongoing decisions, adjustments, and mental effort of daily care. Managing diabetes is not limited to isolated moments of checking a number. It is shaped by repeated choices around food, activity, sleep, stress, and routine, all of which can influence glucose levels throughout the day.

As a result, care often becomes a continuous process of monitoring, interpreting, and responding. This creates an opportunity to design tools that do more than report data by offering guidance that feels more supportive, timely, and easier to live with.

Shifting toward proactive care

We set out to design a system that helps people act before issues intensify. We focused on the management of Type 2 diabetes approaching the problem through earlier awareness, clearer guidance, and more confident decision-making.

Our solution, Aeri, is an AI-powered preventative care concept that utilizes an AR-integrated contact lens to help users anticipate changes earlier throughout the day.

Aeri's core experience is built around four connected parts: live interventions, daily overviews, metric breakdowns, and user controls. Together, they make health insights more useful, timely, and actionable.

User controls also give people more choice over what is surfaced, how prominently it appears, and when they are notified.

Structured across 3 integrated layers

Each layer plays a distinct role. A continuous glucose biosensor reads metabolic signals beneath the skin, an AR smart lens delivers guidance directly in the user's field of view, and an AI-integrated interface turns that data into clear, timely recommendations. Together they form a closed loop that moves from sensing, to insight, to action.

Revealing the gap

Conversations and user interviews point to a system that interrupts daily life rather than supporting it: frequent sensor failures, constant replacements, and the need to repeatedly check numbers create frustration and fatigue. Instead of feeling supported, many feel tethered to their devices, managing alerts, troubleshooting issues, and trying to make sense of inconsistent readings.

Across the category, products have improved in sensing accuracy, connectivity, and real-time display. However, reliability issues, short sensor lifecycles, and fragmented device ecosystems continue to introduce friction.

As conditions become more complex, the operational overhead increases highlighting an opportunity to reduce system friction and create a more seamless experience that requires less active management from the user.

Next Steps

Further evaluate the biomedical feasibility of the sensing approach and underlying hardware.

Refine predictive modeling with clinical datasets to improve accuracy and reliability.

Test AR guidance interactions in real-world contexts to validate usability and behavior.

Expand user research with individuals managing Type 2 diabetes to ground the system in lived experience.

Our takeaways

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