This piece explains how Quantified Self technology has evolved and what new stage it has now entered. It highlights how wearable companies like Oura Ring and Whoop are commanding enormous valuations and reshaping the market, and how advances in AI alongside a more favorable regulatory environment are accelerating that shift. Going forward, wearables are expected to become the center of personal health management — acting as a "Biological System of Record" (BSoR) that integrates a wide range of healthcare services — with innovation emerging in new sensing technologies, ambient monitoring, and software aggregation.

1. The History of Quantified Self and Its New Phase 📈

The concept of Quantified Self — measuring and analyzing personal biometric data to improve health and performance — has been discussed since the late 2000s, but hardware development challenges and technical limitations meant it took a long time to reach mainstream adoption. Recently, however, companies like Oura Ring and Whoop have commanded valuations of $11 billion and $10 billion respectively, bringing sweeping change to the market.

Several important factors underlie this shift:

• Widespread health monitoring: As of 2026, nearly 70% of Americans track their activity digitally, and close to half own at least one wearable device — a massive increase compared to 2020.
• Favorable regulatory environment: In January 2026, the FDA relaxed regulations for "general wellness" products that measure biometrics such as blood pressure and blood glucose, dramatically lowering the barrier to innovation as long as devices are not used for medical diagnosis. This opened the door to a far broader consumer base beyond just biohackers.
• AI-enabled preventive care: The long-held goal of wearables — preventive health management — is finally becoming realistic thanks to the latest AI technology. Wearables can now go beyond showing historical data to predicting and preventing future health problems.

Against this backdrop, Quantified Self has evolved through three distinct phases.

1.1. Phase 1: Simple Digital Logging 📝

The first phase was the era of digital ledgers. It was dominated by apps like MyFitnessPal where users manually recorded basic activity and nutrition. On the hardware side, MEMS (Micro-Electro-Mechanical Systems) technology enabled activity trackers from Jawbone, Misfit, and Fitbit, which combined MEMS sensors with algorithms to recognize movement patterns — distinguishing walking from brushing teeth, for instance.

Devices of this era suffered from low sensor accuracy, and users had to invest significant effort to interpret their data. Marketing slogans like "10,000 steps a day" lacked strong scientific backing. Many companies of this period could not answer the "so what?" question and disappeared; only a handful survived, including Fitbit, which was acquired by Google. Nevertheless, this phase played a crucial role in popularizing the idea of health monitoring and attracting early adopters.

1.2. Phase 2: Physiological Response Analysis and Personalized Insights ✨

The second phase focused on understanding body state — analyzing how the body responds to a user's activities. This was made possible by advances in sensing capability, battery life, and signal processing. Companies like Whoop and Oura leveraged these technologies to analyze longitudinal data, provide biological context through sleep scores and readiness scores, and offer users concrete behavioral guidance.

The biggest innovation of this phase was the "score" and the software powering it. Oura and Whoop used high-quality optical sensors (PPG) to measure heart rate variability (HRV), then processed that data with sophisticated signal processing to deliver meaningful insights. Battery life lasting two weeks or more also greatly improved user convenience, enabling more continuous data collection. This made personalized coaching possible — for example, "if your sleep score is low, try eating earlier or meditating." By the end of this phase, nearly half of Americans owned a wearable device.

1.3. Phase 3: AI-Powered Prediction and Closed-Loop Systems 🔮

The third phase we are now entering is that of closed-loop systems — where multiple devices continuously monitor and predict a user's health. Artificial intelligence is the core driver of this phase. AI enables complex data smoothing techniques that make previously noisy biosignals — like EEG and EMG — analyzable.

The biggest opportunity is emerging in personalized health coaching. AI-powered agents like Oura Advisor and WHOOP Coach (built on GPT-4) interpret users' biometric data and deliver conversational health insights. Rather than simply displaying daily numbers, they analyze long-term trends and invest in models that can predict illness or fatigue before symptoms appear.

"Device companies armed with long-term datasets, deep consumer trust, and artificial intelligence are in a unique position to own the entire health stack."

2. Why Hardware Companies Are Commanding Higher Valuations 💰

Within the next decade, a handful of companies will own the "source of truth" about an individual's health — what the article calls the Biological System of Record (BSoR). This is analogous to how Oracle or Salesforce owns the source of truth about a company's customers and financials. Bret Taylor (co-founder of Sierra, chairman of OpenAI) explained why Systems of Record create such enormous value:

"The reason systems of record have always been the most valuable is that they are the anchor tenant of your technology deployment... You accumulate a lot of value in that system, which means switching costs are very high. Similarly, you accumulate a lot of value by charging rent within the ecosystem or by developing premium add-ons."

This "anchor tenant" concept applies directly to Quantified Self Phase 3. In Phases 1 and 2, wearable companies were one component of the healthcare ecosystem. In Phase 3, the device itself becomes the anchor tenant of the health stack. Leading companies like Oura and Whoop can now layer in a wide range of additional services:

• Blood testing via Labcorp
• MRI via Prenuvo
• Continuous glucose monitoring via Levels
• Fertility tracking via Natural Cycles or Flo
• Personalized supplements via Thorne
• And ultimately, telehealth and primary care

This is precisely why Oura and Whoop command valuations above $10 billion. They have built high-trust, high-frequency relationships with consumers and are uniquely positioned to integrate these services vertically. Users check their Oura or Whoop app every morning and rely on it to tell them how their body is doing. That relationship not only creates opportunities to recommend additional services, but also makes consumers more trusting of the solutions these companies offer. Oura has already announced a lab testing partnership with Quest Diagnostics, and Whoop with LabCorp.

Critically, these hardware companies can offer new features as premium services at near-zero marginal cost. This mirrors the Apple Health model, where third-party apps must pay "rent" — in the form of integration fees — to the company that owns the customer relationship (here, the wearable company).

As the market develops this way, switching costs become enormous for users. Just as Salesforce, integrated with every other tool in a company's stack, becomes nearly impossible to replace — if you manage blood tests, fertility tracking, and glucose monitoring all through Oura, switching to another device becomes far more difficult.

Just as Oracle became the "sun" of the enterprise software ecosystem, the winning wearable company will become the "sun" of the consumer health ecosystem — serving as the hub for additional features and sustaining growth through net revenue retention. This is why hardware remains an attractive investment opportunity in the age of AI and commoditized software.

3. Areas Where Innovation Is Happening 🔭

Will Ventures is actively investing in the Quantified Self market and focusing on three areas of innovation.

3.1. Breakthrough Sensing Capabilities 💡

Over the past several decades, the sensors used to track health have not changed dramatically in themselves — but advances in sophisticated software, data smoothing, and signal processing have enabled new aspects of physiology to be tracked. Wearables are tools, like X-rays or MRI machines, that become more powerful over time as new data models and software are layered on top. Advances in AI will accelerate and expand the use cases for wearable technology, driving the emergence of new sensing capabilities and specialized companies. Two areas stand out in particular:

• Women's health: Most wearable algorithms have been calibrated primarily for male physiology, treating the body as a linear system. But the female body changes cyclically according to complex hormonal rhythms, affecting everything from resting heart rate to body temperature to recovery capacity. A standard wearable might flag a rise in body temperature or a drop in HRV as a sign of illness or overtraining, when in reality it may simply signal entry into a different phase of the menstrual cycle. Companies like Clair Health and Lume Health are developing multi-sensor devices that detect hormone levels without blood draws to address exactly this problem. 🩸
• Neuro-cognitive monitoring: There is also a major opportunity in brain health. Atlas recently raised $14 million to commercialize a brain wearable, and Deepinder Goyal — former CEO of Zomato — raised $54 million through his new company Temple to enter the brain monitoring space. These companies aim to monitor cognitive state by detecting when the brain is optimized for deep work versus when it needs rest. 🧠

3.2. Ambient Monitoring 🏡

When evaluating remote monitoring startups, the most important criterion is ease of use. The value of remote monitoring lies in longitudinal data, and the only way to obtain it is to create an experience users don't find burdensome. From this perspective, ambient sensing is a highly compelling area. It refers to monitoring human activity, behavior, and environmental conditions using contactless, passive sensors embedded in the environment — such as the home — without any wearable or camera. In other words, tracking users without them having to wear anything at all.

• Eight Sleep is a prime example. By using the mattress itself as a sensor, the company achieves nearly 100% compliance. It recently raised $50 million and is expanding into AI-powered predictive health management. 🛌
• Throne is launching a device that attaches to a toilet and analyzes waste — dubbed the "Whoop for your poop" — aimed at helping people with conditions like Crohn's disease, IBS, and cancer. 🚽
• Soma is pioneering ambient neuro-cognitive tracking. Rather than a headset, it uses environmental sensors and "voice biomarkers" to detect burnout or "clinical drift" before users themselves realize it is happening. 🗣️

3.3. Software Aggregators 💻

The strongest counterargument to the hardware-centric thesis is the software aggregator. These are software companies that integrate with all wearables to deliver comprehensive medical services. Companies like Lotus AI and Prana are good examples. They aim to become the Biological System of Record for consumers — storing medical records, wearable data, and more to support prescription fulfillment, lab testing, and AI-driven treatment plans.

If these companies successfully capture market share, they could displace hardware companies as the "first touchpoint" in healthcare. If users get their information from an app like Lotus rather than a device like Oura, hardware becomes a commoditized, interchangeable input and loses its pricing power.

However, software aggregators face platform risk. They are ultimately secondary consumers of data, so if Oura or Apple decides to restrict data access or levy a "tax" on API calls, the aggregator's business model could collapse. Even so, this space continues to be worth watching closely.

Closing Thoughts ✨

Quantified Self is now entering a genuinely exciting new phase. Over the past twenty years, consumers have increasingly taken ownership of their health by using wearables and tracking software to better understand their own physiology. With the arrival of AI, that relationship will deepen further — and for the companies that are able to capture this generational opportunity, it will translate into a far larger and more durable business. If Phase 1 of Quantified Self was about tracking and Phase 2 was about retrospective analysis, Phase 3 will be built on closed-loop systems. As AI commoditizes coaching, datasets and consumer relationships will be the only true moats. 🏞️