YOU(th) raised $4.5m in February. The number is unremarkable. The thinking behind the product is worth a closer look. In late February 2026, the German startup closed a $4.5m round led by Callisto Health, with caesar., adesso Ventures, Antler, Moonstone and 1024 Ventures alongside, plus angel cheques from Jean-Charles Samuelian (Alan, Mistral AI) and Patrick Andrae (HomeToGo). The product is a smartphone-based screening platform that turns face videos, voice recordings, eye and skin images, typing patterns and step data into a panel of more than fifty biomarkers across ten-plus organ systems — blood pressure, oxygen saturation, respiratory symptom index, cognitive age, skin condition, hydration, plus proxies for glucose, haemoglobin and cholesterol. The check-up takes under two minutes.

So far, so unremarkable. The smartphone-screening category is densely populated. What’s unusual is the company’s read of where the value goes.

Most health-tech founders raising in 2026 are pitching defensibility through proprietary technology. They have a face-screening algorithm. They have a voice-pattern algorithm. They have a step-pattern algorithm. The pitch is that the algorithm is the moat. YOU(th) co-founder Johannes Kraus thinks the pitch is wrong.

The aggregation thesis in smartphone health screening

“What we’re not doing, and what I think we shouldn’t do, is compete on basic proprietary technologies like developing another face-screening algorithm for blood pressure. There are already many companies doing that. Instead, we integrate the best providers. I think those underlying technologies will become commoditised, so aggregation is the better strategy.”

This is a meaningful inversion of the standard health-tech defensibility playbook. The default founder bet is that proprietary IP, a better algorithm, a better sensor pipeline, a better validation study, will sustain a premium long enough to capture the category. Kraus is betting the opposite: that the algorithms themselves will compete to zero, the way image-recognition models did, the way speech-to-text did, the way most narrow ML capabilities do once enough teams chase them.

If he is right, the founders building defensibility on a single algorithm are building castles on sand. If he is wrong, YOU(th) is choosing to be a thin layer on top of someone else’s infrastructure.

The company has thought about where the true moat lives. Kraus names two areas. “One is the UI and UX and owning the end user relationship. The second is the dataset created through what we’re doing. Because when we measure many biomarkers regularly, it creates a very interesting dataset that can power big-data analytics and personalisation.”

This is the platform strategy recast for healthcare. Aggregate the underlying capabilities, hold the user, accumulate the data, build the experience layer that the underlying providers can’t. It is an approach that is well-developed outside of health; it is approximately the bet Spotify made against the record labels, the bet Uber made against the cab companies.

Whether it works for YOU(th) depends on a question Kraus does not pretend to have settled. “I think distribution in health tech is not easy. You always need to align the user, the payer and the payment flows. Getting that right is challenging.”

What gets lost when health tech competes on UX in healthcare

Kraus repeats one line in slightly different forms across the conversation: that healthcare apps should look like Instagram and Uber, and currently don’t. “When you own a user, that comes with a lot of responsibility because people are used to very good apps. You open Instagram and it loads instantly. You take an Uber and the interface is very well designed. We don’t see that very often in healthcare.”

That’s a competitive observation, most healthcare apps are bad, so a well-designed one wins by default. And it is a thesis about how users will choose between increasingly similar offerings as the underlying algorithms commoditise. The interface becomes the thing the user actually experiences; the algorithm becomes invisible plumbing.

This is also where YOU(th)’s technical ambitions and its strategic ambitions converge. Kraus’s longer-term view is that screening will become entirely passive. “In my vision people won’t actively do that much. Everything will move in a more passive direction. People will live their normal lives — driving, doing meetings, calling friends — and their health will be monitored passively. When something goes out of range, the system will notify them.”

His co-founder Filippo Nigro described the same destination in his own conversation with us at the same conference: “You unlock your phone, take selfies, send voice messages, type messages, use your laptop for meetings. You are constantly generating facial, voice and typing data. From that, you could perform preventative screening continuously just through normal device use.”

If passive monitoring is the destination, the product that wins won’t be the one with the best blood-pressure algorithm. It will be the one that holds the user across years of normal smartphone use without ever feeling like a healthcare product.

Defensibility through dataset accumulation in preventative health

The dataset claim is the more contested part of Kraus’s defensibility thesis. Aggregating algorithms is a known strategy. Owning UX is a known strategy. But the assertion that biomarker data accumulated across many users at high frequency will become a defensible asset depends on two things working that haven’t worked yet for most consumer health-tech datasets.

The first is that the data has to be useful at scale beyond the individual user. Most wearable-derived datasets have struggled to produce population-level insights that are commercially useful. The second is that the data has to be retainable. Consumer-health users churn, and a dataset of one-month users with a single panel of biomarkers is a different proposition from a dataset of five-year users.

According to Kraus, YOU(th) has around 8,000 users on the platform and roughly 23 contracts with insurers and clinics. Whether the dataset becomes a moat depends on what happens at 100x and 1,000x — which is what the $4.5m is paying to find out.

Asked what the next steps are, Kraus names two. “Closing the loop between screening and outcomes and strengthening distribution. Those are the two key priorities.”

The first matters more than the funding round narrative usually acknowledges. “Measuring the results of treatments or lifestyle actions and feeding that information back into the system to close the loop is still unsolved by most health tech companies”, says Kraus. Apps measure. Apps recommend. Apps notify. Apps don’t reliably show the user that the action they took moved the biomarker, because the biomarker measurement is usually too infrequent to detect the change before motivation collapses.

If smartphone screening can compress that measurement cadence to weekly or daily, the loop becomes considerably easier to close. That, more than the algorithmic edge, is what would make the product genuinely different from what the user already has on their wrist.

Longevity as preventative health by another name

Kraus places YOU(th) in the prevention rather than the longevity category. “For me, longevity is a new buzzword that has helped prevention become fashionable again,” he says. “In reality, longevity is just the extreme extension of prevention. It’s about measuring biomarkers and optimising them.

“Personally, I think it’s important to get the first 80% right before trying to optimise the last 2%. For me, sleep hygiene is one of the most important topics.”

This is not a position the more hyped end of the longevity industry wants to shout too loudly. It is, however, the position consistent with a company whose belief is that the basics, such as measurement, friction reduction, adherence and the closed loop, offer the key to success.