GlycoSync

Inspiration:

Growing up, we watched our grandparents wear early continuous glucose patches. They had these amazing sensors attached to their arms, giving them a constant stream of numbers. But to them, it was just a confusing line on a screen. Already technologically illiterate, they didn't know how to actually use that information. Because they couldn't use the data, we would watch them suffer sudden, scary insulin crashes right in front of us. They had the data, but they were still completely powerless.

That was our lightbulb moment. Millions of people have health trackers, but they suffer from "data fatigue." They see a number drop, but they don't know what to do until they already feel it. We wanted to build a tool that finally translates those confusing numbers into simple, real-time actions, protecting people from dangerous energy crashes before they happen.

What it does:

GlycoSync acts as your personal health translator and predictive copilot. It takes confusing biometric data and turns it into simple, preventative action.

Sensor Fusion: It integrates your continuous glucose data with your Apple Watch (heart rate, activity) and food-tracking data. From this, it learns the difference between a blood sugar spike from eating a big lunch versus from feeling stressed out.

Predictive Trajectory Engine: Instead of buzzing after you crash, it looks at your patterns. It predicts a sudden energy dip or "brain fog" up to an hour before you actually feel it.

Real-Time AI Copilot: When it sees a crash or a spike coming, our AI talks to and then notifies you like a coach. Instead of saying "eat healthier," it gives exact instructions: "Your sugar is rising too fast. Take a 15-minute walk to bring your levels back to normal."

How we built it:

We utilized Figma to build our mobile app. Essentially, we approached this project by prioritizing simplicity and functionality by using warm colors, sufficient white space, and interactive graphs that visualize data in patternized habits. Challenges we ran into One of the biggest challenges was figuring out how to visually translate massive walls of complex medical data into an interface that feels friendly and empowering. Since we were building a high-fidelity prototype in Figma, our primary hurdle was the UI—we went through multiple iterations to ensure it didn't look like a boring hospital dashboard, but rather a sleek, high-performance telemetry screen. Another major challenge was designing the user experience for the AI Copilot. Even though we were simulating the chat interactions for the pitch, we had to deeply conceptualize how the AI logic would actually work. We had to script a completely new interaction model, mapping simulated glucose curves to short, immediate kinetic instructions (like doing 40 air squats) to show the judges exactly how we would bypass the long paragraphs of generic diet advice that standard health bots usually default to.

Accomplishments that we're proud of:

We are incredibly proud of the human-centered design. We took a highly technical concept—metabolic trajectory physics—and turned it into an app that anyone's grandparents could actually use to feel better. We are also extremely proud of breaking the mold of "reactive" health tech. Moving from an app that says "you just crashed" to an app that says "you are going to crash, here is how to stop it" is a massive leap forward.

What we learned:

Through our research to build out the app's logic, we learned a massive amount about human metabolic pathways—specifically discovering how physical movement can be used as an immediate lever to quickly alter blood chemistry. From a UI/UX and systems-architecture perspective, we learned the deep design intricacies of "sensor fusion." Simply mapping out the user journey in Figma taught us how difficult it is to take three distinct data streams (food, heart rate, and blood sugar) and visually synthesize them. We learned how to design a cohesive dashboard that makes complex telemetry look simple, clear, and actionable without overwhelming the user.

What's next for GlycoSync:

Our next big step is true automation through smart home integration. If the app predicts an unavoidable afternoon energy crash, we want it to automatically communicate with your environment—dimming your computer monitors to reduce eye strain, lowering the room temperature to keep you alert, and switching your phone to "Do Not Disturb" so you can safely recover your energy.

Built With

• figma