Why I Built Kygo-health app: Connecting What You Eat to How You Feel

I started Kygo for one main reason: to help identify cause-and-effect relationships between the food you eat and the

biometrics you're tracking through your wearables.

Right now, the health tracking industry is incredibly fragmented. Oura owns your sleep data. Whoop owns recovery. Apple owns activity. MyFitnessPal owns calories. All this data sits in silos, leaving you with an incomplete picture of your overall health and what actually affects it.

Food Logging Is Broken (And We're Fixing It)

Let's be honest—food logging sucks. Every app on the market requires a massive amount of manual effort, and that's exactly why people quit. I wanted to change that.

I believe food logging should be built around a system that's simple, easy to use, and adapts with you. That's why we built a template system that automatically learns your eating habits. Once you've logged a meal a few times, the app creates a template that lets you add it again in one to two seconds.

People are creatures of habit, and this works with human psychology instead of against it. Most people are motivated and consistent when they first start logging food. That's when the templates are created. Then, as people naturally drop off (because life happens), the system adapts with you. Your frequently eaten meals are right there—just one tap away. This dramatically reduces the friction that causes people to quit.

Down the line, I'm hoping to implement better image recognition for even quicker meal logging. The technology is close, but it's not quite accurate enough yet to do this reliably.

Making Sense of Wearable Data in Health Apps

Health Apps and wearables are just as fragmented as nutrition apps. There are several major players in the market offering different devices, which is great—it gives people flexibility to choose what works best for them. The problem? Not all wearables track the same things, and many have significant blind spots.

Take Oura, for example. It provides excellent sleep metrics, but it doesn't have GPS-based tracking, so metrics like distance and steps are called "Equivalent Distance". That's misleading.

The plan is to make Kygo fully wearable-agnostic. As technology evolves, so will the app. I'm currently working on a standardization setup that lets you connect one or multiple wearables to supplement your data. For example, you could connect your Apple Health from your phone with your Oura Ring to get more accurate step and distance tracking while still benefiting from Oura's sleep analytics.

As we grow, there will be a huge emphasis on data quality and utilizing the key advantages of each wearable. This unified data backbone gives us the foundation to build powerful features and gives you complete control.

Why Nobody Else Is Doing Correlations (And Why We Are)?

Correlations are meant to provide a closed-loop system that shows you cause-and-effect relationships between the food you eat and how your body responds. Right now, we're seeing some incredibly promising results with the correlations we've built into the app.

Here's a simple example: consuming caffeine later in the evening. There's tons of research showing that caffeine increases your sleep latency (the time it takes you to fall asleep). What Kygo does is look for statistically significant data, factor in outliers, and time lags to determine if your body is actually affected by this. If it is, we link the caffeine you logged to that night's sleep data and tell you: "Your sleep latency increases by 8 minutes when you consume caffeine after 3 PM."

Although this is a basic example, the results we're seeing are really exciting, and the ability to do this at scale for users is what makes Kygo different.

What's Next?

We're continuing to work on finishing the beta app. The back end is fairly strong right now and virtually ready for users, but we need to make the front end user-friendly, simple, and incentivizing for users to keep logging food.

We're only as capable as the data we receive. There's

no intent to provide incomplete or speculative data just to keep users engaged. Instead, we're trying to provide clear goals so you can see how continued logging helps identify hidden correlations that actually matter to your health.

It's a really exciting time, and development keeps getting better every day. I hope you'll join this journey with us.

Ryan Founder, KYGO Health

October 2, 2025

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P.S. This is our first blog post and was written with talk-to-type. This is not AI Generated content.