Founders of Ultrahuman: Vatsal Singhal, Mohit Kumar

We started Ultrahuman around two and a half years ago. Vatsal and I have known each other for almost 16 years because we did our engineering together. Back then, we were nowhere near the health or fitness domain. We were in engineering college, dreaming about computers and how computing could change the world. Over the years, health became an interesting topic for us, and we founded a business in the logistics space.

It was similar to Uber for logistics, solving the last mile problem with intelligent supply-demand matching. In 2015, our business, Roadrunner, was acquired by Zomato, and we ran their food delivery business. After seven years, we decided to take a break. I went to Tiger Muay Thai, a martial arts camp, and stayed in touch with Vatsal to explore something new in fitness and health. We wanted to bring data to health, leveraging biosensors to help people understand more about their health.

That's awesome. You built a fantastic success before starting Ultrahuman.

Yes, it was a success in a different domain. Vatsal can add more to it. We wanted to build something unique, a last mile delivery service that was crowdsourced. We believed in the power of crowdsourcing because it benefits workers. We employed over half a million people, impacting their families. It was a large problem statement, both as a business and technology challenge. We were doing more than 2 million transactions a day. But health is the base of everything. We realized that being healthy makes us more productive, and we wanted to support everyone in having a healthy lifestyle.

When we started, the biggest problem was supply, specifically delivery drivers who had a high churn rate. We realized that improving efficiency for full-time delivery workers would attract better talent. We also made it a part-time gig for students to pay tuition fees. It started with a supply problem, but network effects were massive. We sold to restaurants because they understood the urgency of delivery within 30 minutes.

Network effects required density, meaning hiring ahead of time, which meant losing money initially. We used to joke about it being a mountain of cash to cross before making a business out of it.

Did you concentrate on specific areas or go broader?

We concentrated on high-density areas initially. In India, entering a locality, even if not dense, meant owning it due to first-comer advantage. We balanced between dense, competitive areas and new, non-competitive areas. The latter made us lose money initially, but we owned the locality.

Culture is hard. What worked for us was creating a culture around social impact. We wanted people to live the life of a delivery driver to understand their challenges. We also maintained a lean team structure. Initially, we had a bloated organization, but we learned to hire based on the need for work, not just structure. People care about the quality of work, and that understanding helped us a lot.

It's interesting how startups transition from generalists to specialists as they scale.

Exactly. Early on, generalists drive the business, and as you scale, you transition to specialists. Everyone can touch something to create content or do social media. When there's a need, you hire people for that work.

It started as a sales conversation. I met with Zomato's founder, and we discussed our journey. Zomato was launching a food delivery business, and there was natural synergy. What started as an integration partnership emerged into a merger. We had similar journeys and challenges, making it easy to work together. It was a good synergy, A plus B, creating a superior product. As founders, we initially didn't want to sell, but the opportunity to scale from a million to 70 million transactions a month was compelling.

You went from 1 million transactions a month to 70 million?

Yes, at our peak, we were doing over 2 million transactions a day. It was a huge technology and data problem, but it was exciting to solve it with Zomato.

After Zomato, I took a break at Tiger Muay Thai, a martial arts camp in Thailand. Vatsal and I discussed what to do next. We were both into fitness; I was into Brazilian Jiu Jitsu, and Vatsal was into CrossFit. We explored various business ideas, but our interest in health and performance led us to focus on that. At the camp, I saw athletes using biomarkers to improve health. We decided to build something close to how we wanted to live our lives, leading to the birth of Ultrahuman.

When you do what you like, it's not work anymore. What was your first step?

We tried different biomarkers ourselves, fascinated by HRV, sleep zones, and glucose. The glucose biomarker hooked us instantly. We realized it could make health interesting for people, providing feedback on food. Everyone eats, so a wearable giving feedback on eating habits could have a large impact. We started building deeper into the glucose wearable ecosystem.

Real-time data and consistent sampling change everything. Glucose monitoring gives constant access to glucose levels, allowing deductions about insulin. It's individualized; your glucose response to high-carb foods like pineapple can differ from mine. This sensor can change nutrition for good.

It's fascinating how individual nutrition is. What myths have you seen broken?

Many myths get broken. People think home food is healthy, but high-carb home food can spike glucose. Jaggery is marketed as healthy compared to sugar, but it has a similar glucose response. Misleading labels also confuse people. Real-time glucose monitoring reveals the truth.

Healthy food from 20 years ago might not be healthy today due to lifestyle changes. It's about balance. Athletes can eat more for energy, but sedentary people can't. It's not a simple answer; it's individualistic.

Today, we provide glucose response to food, exercise, stress, and sleep. Thanks to you, we're integrating with other platforms for a holistic view. Combining data streams offers more insights than a single metric. We're also launching our own hardware to measure more biomarkers, different from existing ones. This will allow us to provide more actionable insights.

That's incredible. You're offering tailored recommendations based on glucose responses and integrating more data. It's exactly what we need.

Yes, data without actionability is useless. Insights drive value. Glucose data is just data until you build algorithms on top of it. Our goal is to provide actionable insights, helping people find the lowest hanging fruit for their health. Whether it's walking after meals or getting enough zone two exercise, we want to guide people towards better health.

It's fascinating how real-time data is changing our understanding of health. I recently had a late meal, and my sleep tracker showed my heart rate was 11% higher than usual. This kind of data correlation is something we wouldn't have known before. How do you see this impacting healthcare?

It's exciting. We can now see our glucose levels, sleep cycles, and other biomarkers in real-time. This data allows us to use machine learning to gain better insights. It's a revolution in lifestyle medicine.

Exactly. Real-time data keeps you close to the problem. If you see the impact of a late meal on your body, you'll consciously avoid it next time. Preventive healthcare is changing because of this data.

We're moving from reactive to predictive healthcare. You can foresee potential health issues years in advance and make lifestyle changes accordingly.

You've raised a significant amount of funding. How did you approach fundraising, and what can others learn from your experience?

We've raised $25 million in total. Our approach was to show early traction and user interest. We focused on building a waitlist and learning from user feedback.

We made health tracking cool and accessible. By sharing user experiences, we created acceptance around tracking biomarkers. This story resonated with our investors.

In our Series A, we showed demand through our waitlist. Even if you can't show revenue, demonstrating user interest can be compelling.

Keeping investors involved in our journey helped build conviction. They saw our challenges and progress firsthand.

It seems like as long as you're building something people want, you just need to convey that to investors. How do you see the future of your space?

We're working on new biomarkers, like a nuanced recovery algorithm based on HRV and temperature. We're also exploring light exposure's impact on sleep.

Measuring blue light exposure could help understand its correlation with sleep quality. It's a new approach that could validate how light affects stress and sleep.

What's next for you in the coming year?

We're focusing on our hardware and providing more real-time information to our community of cyborgs. We aim to have a close-knit group of 100,000 users who believe in the science and work with us to improve.

Our goal is to be 30 to 50% done with this focus in a year. Once we have a strong community, we can expand to millions.

Fantastic. Thank you so much for this, and we speak soon.