No Wires, No Waitlists: Chris Fernandez of EnsoData on Making Sleep Diagnostics as Easy as Putting on a Watch
Modern medicine has made staggering strides, yet one of its most fundamental building blocks — restorative sleep — still eludes millions. Sleep apnea alone affects an estimated billion people worldwide, but traditional diagnostics require cumbersome overnight studies interpreted by already‑stretched specialists, leaving patients on waitlists that can stretch for months. Automating that bottleneck is more than a technical upgrade; it’s a chance to raise the standard of care of sleep and in the future across cardiology, neurology, mental health, and beyond.
Enter EnsoData, a University of Wisconsin‑Madison spinout that began as a graduate project and evolved into an FDA‑cleared AI platform capable of translating raw sleep data into clinically actionable insights which impacts over 100,000 patients per month. Under the leadership of co‑founder and Chief Research Officer Chris Fernandez, EnsoData received a pivotal FDA clearance in 2024 which enables any FDA approved wearable device with photoplethysmography (PPG) to be used to diagnose sleep apnea, opening the door for accurate sleep diagnostics through everyday wearables, anywhere.
Venture Investors Health Fund backed Chris early because partnerships with academic innovators are in our DNA. We look for university‑born technologies with the power to redefine care pathways, and we stay committed to supporting founders as they navigate regulatory, reimbursement, and real‑world adoption. In the conversation that follows, Chris unpacks EnsoData’s origin story, the significance of its latest clearance, and how timely investment and institutional collaboration can help an audacious idea become a new standard in patient care.
Enjoy the Q&A below.
Let’s start at the beginning. Was there a specific “lightbulb moment” that sparked EnsoData? Picture yourself in that moment — what was happening, and what made you decide, “I have to create a solution for this”?
CF: Starting from the beginning, my co‑founders and I met in the biomedical engineering program at UW-Madison, and we sort of fell in love with machine learning through the classes there. I think that’s what started the spark that resulted in the light‑bulb moment — we were observing that we were in the middle of an AI revolution. People were developing deep learning and neural networks that allowed computer programs to take on tasks of a complexity that was previously off‑limits. We found that fabulously exciting. This was way before GPT, DALL·E, and all the other cool stuff we have today.
We went out and interviewed 100 physicians from different medical specialties and told them, “We love big data, machine learning, and important problems in healthcare — do you have anything we could work on?” We were essentially panhandling for problems, looking for a killer application. The light bulb came on when we went into a sleep lab for the first time and gave that pitch. They said, “Oh my gosh, yes, we have a data problem you could work on. If you could solve it, it would be immediately applicable here in the US and globally. Come with me.” They took us to the basement and showed us what sleep data looked like.
The light bulb was a confluence of several things. One was realizing how much data was in play — the richness of brain waves, heart rhythms, airflow patterns, respiratory effort, movement, blood‑oxygen saturation, and even more. In neurology they have more EEG channels on the head, and in cardiology they can put more ECG leads on the chest, but the sleep study is unique: relative to all medical specialties, it’s a complete picture of the whole body and how it’s interacting. We realized that out of eight billion people in the world, everyone sleeps, and more than a billion have sleep apnea. Sleep at face value seems boring, but the more we dug in, it felt like a conspiracy — it’s so central to human health and wellness, right up there with diet and exercise. When you look at major chronic conditions — depression, heart disease, high blood pressure, stroke, diabetes — sleep problems are consistently at the scene of the crime. It seemed like such an untapped area; if we could apply AI there successfully, we could transform diagnosis and treatment for a huge population.
AI can seem mysterious or abstract. Can you share a favorite story of how a healthcare provider or patient benefited from EnsoData’s technology in a down-to-earth, relatable way?
CF: Those stories are probably the most rewarding part of the job; hearing that feedback makes all the time at the computer terminals worth it. One customer that comes to mind was among our first. We met them in 2015 after driving to every single sleep clinic in the state of California in two weeks. They were a large multi‑site clinic in the Bay Area near Walnut Creek. They’d been growing quickly and had already used some automation to help interpret sleep‑study data — what we do. At that time, only about one in ten sleep clinics in the US used any form of automation. Most found existing tools so inaccurate that they created more work than doing it manually.
This clinic already had a technology‑forward mindset, so we offered to let them use our software for free. They could compare it to what they already used and decide which was better. The lead technologist was managing a ballooning workload, with six‑ to nine‑month waitlists and skyrocketing home‑sleep‑test volume. If they got sick or took vacation, it felt like the world would end. They were hungry for a solution that could ease the cognitive burden of this complex data interpretation.
We were able to save about 75% of the time they previously spent on each patient study — interpreting 700 to 800 pages of data with the old software. It was amazing to hear that they were now seeing more patients and, at the same time, spending more moments with their family. That’s a good story.
Congratulations on your 2024 FDA clearance for Photoplethysmography (PPG)! For those of us who aren’t in healthcare every day, what makes this clearance such an important milestone — and how does it set the stage for EnsoData’s future growth?
CF: It’s a cool milestone — perhaps the most significant FDA clearance we’ve achieved. It’s really the culmination of our prior clearances. Our first clearance automated analysis for complex in‑clinic tests. The second, during COVID, expanded home‑sleep testing in the rapid shift to virtual care. The third leveraged more than three million patient studies — we’ve helped diagnose over two million people — to train an AI model that produces the same quantity and quality of sleep information as those complex tests, but now using wearables.
We’re FDA‑cleared to enable sleep diagnosis interoperably from any wearable device with a PPG sensor — the most ubiquitous sensor on smartwatches, smart rings, head patches, and even traditional home‑sleep‑testing devices. Wearables take what used to require 20 sensors and bring it down to one, offering simplicity and convenience that’s unparalleled. Interoperability lets clinicians choose among many form factors, balancing cost and patient preference, while the AI delivers deep, accurate clinical data — respiratory, neurologic, cardiac, and more — to personalize diagnosis and treatment.
Previously, the AI just automated tasks clinicians already performed, making them faster. Now AI can detect REM sleep or slow‑wave sleep from pulse‑ox data — things clinicians weren’t trained to do with that data — unlocking new use cases. In sum, this clearance creates the largest opportunity yet for greater access, awareness, and scale in sleep‑disorder diagnosis.
Building a tech startup in healthcare is no small feat. Can you describe a situation where your team faced a big roadblock, and how you overcame it?
CF: The biggest roadblock was COVID — not only for us but for our customers. When COVID peaked, hospitals shut down many non‑essential services, repurposing staff to acute COVID care. Sleep doctors — often pulmonologists and critical‑care specialists — were among the first pulled to the front lines, and many sleep labs shut down, disrupting care for patients with sleep problems. Paradoxically, the stress of COVID made many people sleep worse.
Sleep‑study volumes plummeted, and hospitals scrambled to maintain care. Around 2021 we received our second FDA clearance, expanding integrations for home‑sleep testing and introducing the most accurate way yet to measure sleep from non‑EEG data across all home tests. We turned the lemons of COVID into lemonade by helping health systems shift to telehealth, virtual care, and home diagnostics. That capability became a huge asset: many clinics now do even more virtual care than during COVID, in addition to their in‑person services. The pandemic was terrible, but the acceleration of home care it spurred is, I think, really positive.
When you imagine the future of healthcare, what role does EnsoData play in creating a more patient-centered, streamlined experience? Are there specific health areas beyond sleep medicine that you’re excited to explore?
CF: This is a great question. I think sleep is still under‑addressed. It will be recognized more as the third leg of the health stool, alongside diet and exercise. I hope EnsoData makes sleep measurement and diagnosis so affordable and ubiquitous that it becomes second nature. There’s no disease we know that isn’t worsened by poor sleep, so the interplay between sleep and other body systems fascinates us.
We’re already working in cardiology. Sleep apnea occurs in about half of people with atrial fibrillation and 75% of those with aortic stenosis. We’re interested in breaking down silos — making cardiac analysis pervasive in sleep data and bringing sleep metrics into cardiac data. We’re also interested in neurologic conditions with little objective measurement, like mental‑health disorders and neurodegenerative diseases such as Alzheimer’s.
What inspired you to partner with Venture Investors Health Fund, and how has their support or collaboration helped shape EnsoData’s journey so far?
CF: We’ve known Venture Investors since very early in our journey, starting with the gener8tor gBETA program in 2015. Even before that, they were among our first advisors and mentors. When you start a company at 20, you’re behind on advice, and they connected us with smart people to pressure‑test ideas, figure out where to double down, and iterate faster than we could have alone. We initially did our seed deal with HealthX, kept doubling and tripling revenues, and then partnered with VI in our Series A just before COVID. It was great to team up with a group we’d built such a strong relationship with — they had the skills, knowledge, network, and resources to help us do what we wanted to do, and here we are.
Reflecting on your journey from dream to reality, what piece of advice would you offer to other founders who want to make a real impact — especially in an industry as complex as healthcare?
CF: There are many lessons, but one stands out: dare to have a big vision. Many people hold more reservations about that than they should. Changing the world requires excitement, resilience, and perseverance. One of the most potent motivators is a compelling, audacious vision — something huge if true, radically different, not incremental. Startups are out‑gunned and out‑resourced; big companies own the world. If you want to create a new category or own an existing one, you need those 10X differences.
That means you’ll always feel far from where you want to go. Your product is only a reference implementation of the bigger idea behind it. You’ll never fully arrive, but that’s the place you want to be. Have a billion‑dollar mindset, not a million‑dollar mindset; you’ll go only as far as you dare to aim.
Learn more at ensodata.com.
