For many Levels members, a CGM is just one of the wearables they use every day. But as many have discovered, keeping tabs on multiple data sets from various wearables can be burdensome. Kyriakos Eleftheriou can relate. He is the CEO and co-founder of Terra, a B2B product that connects wearables in the fitness, wellness, sleep, and health space.
Eleftheriou talked to Levels about the start of Terra just 1.5 years ago, how Terra could someday change how you interact with Spotify and Netflix, what he sees as the future of wearables, and the biomarker that will change the way we interact with our health.
Levels: Can you tell us what Terra does and how you started the company?
Eleftheriou: We started the company about 1.5 years ago. Before that, I had gotten my first wearable to optimize my performance in the special forces—a heart rate monitor—and I could see my heart rate all the time and the calories I would expend. From that information, I knew what I needed to eat and how to train to perform, which got me into more data over the years.
However, I kept having the same problem with all my new wearables: I’d use a CGM sensor, and the data would remain in Apple. Or, I’d use a Garmin, and the data would remain in Garmin. We thought: Why don’t we build one solution that makes it super easy to connect my wearable data to any app?
At Terra, we build an API (a software connection) that makes it easy for apps to connect to any wearable through a single source.
Now we have millions of users and an established partnership with some of the best apps in the world, such as Eight Sleep, Carb Manager, and Ultrahuman.
How do you do that when each company has its own way of presenting its data, rules, and partnerships?
There is no data standard in this space. One company might name calories as calories, while another names it kilocalories. This problem becomes more prominent the more wearables you try to connect to—and hundreds of wearables exist.
What we’ve done is created a standard. We standardize all of the data that passes through Terra. That means you’ll always read HRV as HRV or deep sleep level as deep sleep level without caring about the source that this comes from. Ultimately, we are translating all the data into one language.
What is Terra aiming to do in the future? How do you want to be able to use this data?
The idea is to enable users to connect their wearable data to non-health-tech companies like Spotify, for example, to use your heart rate to create better song recommendations. Or have Netflix use your stress levels to make better movie recommendations – in real-time.
And this is happening with users first in mind: The user chooses if they want to connect their data. Terra has no access or storage to any of the data to preserve the user’s privacy.
When it comes to the wearables landscape, what are you seeing now as trends—and what can we look forward to?
One, so many biomarkers for real-time measurement are coming to the market. Two, companies are figuring out how to close the loop using the data.
One example I like in this space is the folks at Eight Sleep. They aggregate your heart rate variability, deep sleep, and REM levels, then regulate the mattress’s temperature to improve those metrics. That’s closing the loop between aggregation of the data and doing something with the data.
Levels is doing that. Having your glucose numbers, you can learn precisely how and when you should eat and how you could improve your lifestyle.
The more information we have about the human body, the more we can predict what will happen instead of reacting when something happens. There’s a big educational gap between having the information and doing something with that information.
Right now, we have individual sensors that measure one thing. Within the next few years, we will see more and more sensors measuring different biomarkers. What if we were able to access blood pressure in real-time? What if we can access sweat analytics as well? In the longer term, you will have a device that computes everything.
As somebody who has used these kinds of tools for yourself, what’s missing in this space that you would personally like to see?
Knowing how hormones work in each individual. For example, your testosterone is different in the morning and evening; it’s different after eating a steak with high saturated fat. Estrogen, insulin, and human growth hormone are all individual, too. If we get to the point where we can measure those hormones in a real-time way and get real-time feedback, this will enable us to understand the first principles of the human body. And it will radically change how we see our health.
You’ve used Levels. Did you learn anything surprising once you started looking at your glucose?
I had a good idea by using apps, like MyFitnessPal, of the types of carbohydrates that were high-glycemic. However, I ate whole oats or rice and saw a big glucose spike. I would have never expected it.
This helped because I’m structuring what I eat to synthesize my workouts. When I’m weight lifting and want to recover as fast as possible, I know I need more glucose after my workouts. I used the information from Levels to understand the foods I was eating and construct my post-workout nutrition.
I ended up changing my meals. I skip carbohydrates in the morning. I added an avocado to protein for my first meal. Then I have my first carbohydrate of the day after my workout to improve my performance and be able to focus at work. Whenever I spiked my glucose levels, I would crash, impacting my ability to work. When I come to the office, I want to work for 10 hours straight, so I make sure that my glucose levels are balanced and nothing interferes so I can focus and get right to it.