Kim Kardashian posted about it on Instagram and got 3.4 million likes. Bryan Johnson spends $2 million a year chasing it. And somewhere on London’s Harley Street, a year-long health optimization program will run you north of $70,000.
Welcome to the world of AI-powered health screenings, where the wealthy aren’t waiting for symptoms to show up. They’re paying premium prices to catch problems years before a traditional doctor’s visit ever would. And the technology powering these clinics is advancing so fast that what sounded like science fiction five years ago is now a Tuesday morning appointment for the ultra-rich.
But here’s the real question: is this just another luxury wellness trend, or are these clinics genuinely rewriting the rules of preventive medicine?
The Clinics Redefining What a “Check-Up” Looks Like
Forget the sterile fluorescent lighting and six-month wait times of your local GP. The new generation of private health clinics feels more like stepping into a boutique hotel designed by someone obsessed with minimalist Scandinavian architecture.
Take Neko Health, the Swedish startup co-founded by Spotify billionaire Daniel Ek. Their London clinic in Marylebone features duck-egg blue walls, soft lighting, and retro-futuristic furniture designed by a former lead architect at Foster & Partners. Patients swap their clothes for cream robes and custom Nike-designed slippers before stepping into a scanning pod that looks like it belongs on the set of a sci-fi film.
The scan itself takes roughly ten minutes. More than 70 sensors collect 50 million data points, mapping every mole on your body, checking cardiovascular markers, running an ECG, and pulling blood samples that get whisked to an on-site lab through a pneumatic tube system. Results? Ready before you’ve finished getting dressed. The whole appointment, including a 30-minute doctor consultation with your data displayed on a large screen, costs £299 (about $400). The demand has been staggering: the London waitlist hit 100,000 people within months of opening. Neko raised $260 million in Series B funding in early 2025, valuing the company at $1.8 billion.
Then there’s Prenuvo, the company that essentially turned full-body MRI into a celebrity status symbol. Their flagship scan uses custom FDA-approved MRI machines to screen for over 500 conditions across 33 organs in under an hour, all without radiation or contrast dye. A whole-body scan costs $2,500. Their newer Executive Membership, which bundles a full-body MRI with blood biomarker panels, brain health assessment, and body composition analysis, runs $4,499 per year (and $4,999 in New York). Prenuvo generated $100 million in revenue last year, has surpassed 170,000 scans, and now operates 26 clinics across North America, Australia, and Europe.
At the extreme end of the spectrum sits Reborne, a townhouse clinic on London’s Harley Street staffed with oncologists, cardiologists, psychologists, and orthopaedic surgeons. Their Foundation package costs up to $6,800 and unfolds over three months. The Bespoke programme lasts a full year and can exceed $70,000. Services include DEXA bone density scans, genetic testing panels, MRI imaging, and even therapeutic plasma exchange, the controversial treatment popularized by Bryan Johnson.
The AI Engine Behind the Scans
What separates these clinics from a traditional executive physical isn’t just the spa-like environment or the celebrity clientele. It’s the software.
The FDA has now authorized 1,451 AI-enabled medical devices through the end of 2025, with 295 cleared in that year alone. About 76% of those authorizations are for radiology and imaging tools. The global AI-in-healthcare market surpassed $36 billion in 2025 and is projected to exceed $500 billion by 2033, growing at nearly 39% annually. This isn’t a niche experiment; it’s a full-scale industrial shift.
At Neko, AI algorithms process the 50 million data points from each scan to create what the company describes as a “digital twin,” a volumetric model of your body. The real power emerges over time: when you return for your next annual scan, the AI compares your current results against your previous data pixel by pixel, detecting micro-changes like the slight growth of a nodule, arterial wall hardening, or subtle shifts in visceral fat distribution. These are changes invisible to the human eye and completely asymptomatic to the patient.
Prenuvo’s approach is similar in principle but different in execution. Their system captures 1.3 billion data points per whole-body MRI, and their team of over 200 healthcare professionals (including 100-plus board-certified radiologists) uses AI support to enhance accuracy and consistency across interpretations. Their recently FDA-cleared Body Composition report uses AI to assess muscle volume, symmetry, and abdominal fat distribution, metrics that predict metabolic disease risk far more accurately than a bathroom scale.
The companies building the diagnostic software for these clinics rely on increasingly sophisticated medical device app development processes that must satisfy strict FDA and CE regulatory frameworks. Every algorithm that touches patient data needs to meet rigorous standards for accuracy, security, and interoperability with existing healthcare systems. That’s a significant technical barrier, but it’s also what gives these AI tools their credibility. The first foundation-model-powered clinical AI (Aidoc’s CARE1) received FDA clearance in February 2025, marking a new chapter in how diagnostic software learns and adapts.
The practical results are hard to ignore. During Neko Health’s first year of operations in Stockholm, they scanned 2,707 people. Of those:
78.5% had no health issues detected
14.1% required medical treatment they didn’t know they needed
1% received potentially life-saving treatment for severe conditions like cardiac abnormalities
Prenuvo reports that approximately 5% of their scans detect a potentially life-saving condition. Nearly half of all patients find something worth monitoring, even if not immediately actionable.
Why the Ultra-Wealthy Are Obsessed With Preventive Scanning
Bryan Johnson might be the most extreme example. The tech entrepreneur, who sold his payments company Braintree Venmo for $800 million, has spent roughly $2 million annually for five years on his anti-aging regimen, Project Blueprint. His protocol involves more than 100 daily supplements, regular MRI scans, biomarker testing every few months, gene therapy injections, and continuous monitoring by a team of 30 doctors. In early 2026, he launched Immortals, a $1 million-per-year health optimization program. Within 30 hours of announcement, over 1,500 people applied, including entrepreneurs, politicians, athletes, and actors.
Johnson isn’t alone in putting serious capital behind longevity tech. Amazon founder Jeff Bezos has invested in Altos Labs, an anti-aging research company. Peter Thiel helped fund Unity Biotechnology, which focuses on the senescent cells linked to aging. OpenAI CEO Sam Altman has put $180 million into Retro Biosciences, which is exploring ways to rejuvenate cancer-fighting T cells.
The financial logic driving this obsession comes down to a simple calculation: chronic diseases account for roughly 70% of all healthcare costs, and most of them are either preventable or significantly manageable through early intervention. The ultra-wealthy aren’t just buying peace of mind. They’re making what they see as a rational investment in the asset that funds everything else: their health.
Three forces are converging to accelerate this trend:
Diagnostic AI is getting radically cheaper to deploy. Neko’s £299 price point is a fraction of what comparable testing cost five years ago, and the company has stated its goal is to make scans even more affordable over time. The underlying sensor and computing costs continue to drop.
Data accumulation creates compounding value. Each scan becomes more valuable than the last because AI can track longitudinal changes across years of baseline data. One snapshot tells you something; a decade of snapshots tells you everything.
Regulatory infrastructure is catching up. The FDA cleared more AI medical devices in 2025 than in any prior year, and 10% of those clearances now include Predetermined Change Control Plans, which allow algorithms to evolve and improve post-approval. The EU AI Act’s high-risk medical device obligations take effect in 2026–2027, adding another layer of oversight.
What These Scans Actually Catch (and What They Miss)
It’s worth being honest about the limitations, because the hype around full-body scanning can sometimes outpace the evidence.
The American College of Radiology does not currently recommend total-body screening MRI for average-risk, asymptomatic adults. Their concern is straightforward: these scans frequently surface “incidental findings,” abnormalities that look concerning on an image but turn out to be harmless. Those false alarms can trigger unnecessary follow-up tests, patient anxiety, and significant additional healthcare costs.
Dr. Heide Daldrup-Link, professor of paediatric oncology at Stanford, has compared whole-body scans to looking at a city from a distance. You can see the skyline, but you can’t read the street signs. Targeted, symptom-driven imaging remains more effective for diagnosing specific conditions.
That said, the technology is improving rapidly. Modern AI systems are getting better at distinguishing between benign incidental findings and genuinely concerning anomalies, which reduces the false-positive problem that critics rightly flag. And for people with elevated risk factors (strong family history of cancer, genetic predispositions, or prior serious illness), the calculus shifts. Early detection of conditions like aortic aneurysms, pre-diabetic metabolic patterns, or stage-one cancers can be genuinely life-altering.
The strongest case for these scans comes down to what they detect that traditional medicine routinely misses:
Cardiovascular abnormalities with no symptoms, including arterial stiffness and irregular heart rhythms
Early-stage skin cancers identified through AI-powered mole mapping that outperforms visual inspection alone
Metabolic syndrome markers, including pre-diabetic blood sugar patterns and dangerous visceral fat distribution
Soft tissue anomalies across major organs that wouldn’t trigger a standard blood panel
The Access Problem Nobody Wants to Talk About
Here’s the uncomfortable truth that hangs over this entire industry: none of these preventive health services are covered by insurance. Not Neko’s £299 scan. Not Prenuvo’s $2,500 MRI. And certainly not Reborne’s $70,000 annual program.
As Reborne’s CEO Faye Mythen has acknowledged, until the insurance market catches up with preventive health, these services remain accessible primarily to people who can afford them out of pocket. The clinics themselves are located in affluent neighbourhoods, marketed through celebrity endorsements, and designed with luxury aesthetics. The clientele skews wealthy by default.
This creates a paradox. The people who would benefit most from early detection (those with limited access to healthcare, higher rates of chronic disease, and fewer resources for treatment) are precisely the people who can’t afford these scans. Meanwhile, the worried wealthy are getting screened annually for conditions they may never develop.
Some companies are working to close the gap. Neko’s co-founder Hjalmar Nilsonne has publicly stated that the company’s long-term goal is accessibility, not exclusivity. Their pricing is already a fraction of competitors like Prenuvo and Ezra. And as sensor costs drop and AI processing becomes more efficient, there’s a plausible path toward genuinely affordable preventive scanning.
But we’re not there yet.
What Comes Next
The convergence of clinical-grade AI, wearable biosensors, and massive health datasets is pushing medicine from a reactive model (wait until something breaks, then fix it) toward a predictive one (spot the problem before it becomes a problem).
Mayo Clinic has used AI-powered remote monitoring to achieve a 40% reduction in hospital readmissions. Cleveland Clinic’s AI virtual triage system operates at 94% accuracy across its emergency departments. AI-based CT systems can now scan and analyze 200 to 400 images in 20 seconds. These aren’t pilot programs anymore; they’re operational infrastructure.
For the ultra-wealthy, the private clinic experience will only become more personalized, more data-rich, and more predictive. For everyone else, the real question is whether the technology that currently sits behind a £299 (or $2,500, or $70,000) paywall will eventually make its way into the healthcare systems that serve the rest of us.
The science says it should. The economics say it can. Whether it will depends on something technology alone can’t solve: political will, insurance reform, and a genuine commitment to making early detection a right rather than a luxury.
That’s the billion-dollar question the wellness industry hasn’t answered yet. And until it does, the future of medicine will continue to arrive first in the waiting rooms of Marylebone and Manhattan, long before it reaches the rest of the world.