The daily operations of longevity clinics are dictated by data. From full-body scans to exhaustive biomarker workups and hour-by-hour information generated by wearables, clinics are tasked with assembling and then interpreting medical dossiers deeper than anything doctors could have imagined 20 years ago. Clinics could easily be overwhelmed by the mass of evidence and could easily miss patterns that might be crucial for expanding healthspan. Effie Arditi is out to change that. The co-founder of Longevitix says his AI-supported records system channels the flood of data into a system that allows multiple specialists working with the same patient to see how the pieces fit together. Records that are comprehensive are now comprehensible, he says, creating a model for better outcomes and possibly more access to longevity care. We talked to him about the support clinics need and how it could support the needs of patients.
Do you think longevity clinics are delivering the kind of comprehensive care that delivers true longevity and healthspan?
Many of them are closer than people assume. The clinics we work with have assembled strong teams: cardiology, endocrinology, nutrition, sleep, movement, and mental health. The clinical talent is already in the building. Care gets thin in the space between those specialists. Each specialist does careful work in their own domain, and the whole picture only comes together when the managing physician writes the patient’s report, often weeks later, from notes spread across email, PDFs, and WhatsApp threads. Healthspan depends on seeing how systems interact over time, like a glycemic pattern that aligns with a cardiology finding from three months earlier. Right now that connection usually happens because someone on the team is diligent. Diligent teams do this well. The trouble is that diligence is hard to scale, and it leaves when a staff member does.
What services and treatments should be more common in the clinics?
I’d start with follow-through. Most clinics are very good at the intensive baseline assessment. Fewer have a structured cadence for re-testing and reviewing what changed, and longevity medicine relies on that trajectory. A single panel tells you where a patient is. A series of panels tells you where they’re heading.
Beyond that, a few areas deserve more attention. Midlife women’s health is one, especially perimenopause, where symptoms are frequently misread. Body composition monitoring for patients on GLP-1 therapy is another, since muscle and bone loss can go unnoticed when the scale is the only number anyone watches. And wearable data should be interpreted by a physician. Patients are already collecting it, and much of it never enters a clinical conversation.
Finally, structured case review between specialists. Big multidisciplinary clinics have it, and so can a solo physician who works with outside labs and consultants. In both cases, it works best when it’s a defined part of the workflow with a clear owner.
What’s holding them back?
Mostly infrastructure. The software available to clinics was built for episodic, reactive care and billing. It handles a visit, a diagnosis, and a claim well. It handles a five-year relationship with a patient whose data comes from a dozen sources poorly.
So clinics fill the gap with people. When we interviewed 50 preventive medicine clinics, the same problems came up repeatedly: data arriving in incompatible formats, physicians spending hours assembling information before they could start thinking, and team communication running through messaging apps that sit outside the patient record.
There’s also an ownership question that rarely gets written down. Giving every specialist access to the chart is easy. Deciding who is responsible for pulling it all together, and what a specialist should flag versus handle independently, is harder, and most clinics leave that to habit. Access without clear ownership just gives gaps more places to hide.
How could Longevitix change that?
We built Longevitix as the intelligence operational layer that longevity care is missing. Every patient has one shared record. Each specialist sees the part of it that matters for their domain, so a sleep specialist and an endocrinologist work in the same chart without wading through each other’s noise. Case discussion happens right next to the data it refers to, so nobody has to reconstruct afterward who said what and whether it made it into the plan. The managing physician owns the final synthesis, and the system makes that ownership explicit.
The AI decision support works inside that structure. It pulls labs, wearables, imaging, and specialist notes into a single patient dossier, surfaces patterns across domains (that glycemic signal and the earlier cardiology finding, for example), and flags them for physician review. The physician reviews and decides. Each clinic also configures its own intake, its own clinical protocol, and its own dossier format, so the output reflects how that clinic actually practices medicine.
AI is increasing its capabilities fast. What role do you see it playing in longevity five years from now?
I expect the biggest change to be continuity. Today most longevity care is still organized around events: the annual assessment, the follow-up visit, the report. In five years I think AI will make it practical to treat a patient’s health as a continuous record that gets read and re-read as new data comes in, with meaningful changes flagged to the care team between visits.
Measurement will improve too. Biological age models are already moving from single clocks toward foundation models that read many data types together, and those tools will mature. But the clinics that benefit most will be the ones that have already organized their data and their teams so AI has something coherent to work with.
The physician’s role will also shift. With synthesis and data assembly handled by the system, the hours go into judgment and into the patient relationship, which is the part of medicine that should stay with people. Every serious use of AI in this field keeps a physician in the loop, and I expect that to become a baseline expectation from patients and regulators alike.
Can technology make longevity care more accessible to people who might not be able to afford it now?
Yes, though technology alone won’t get there. Longevity memberships today run from a few thousand dollars a year to well over $20,000 at the top end, and a large share of that cost is physician and specialist time. A lot of that time goes into assembling and reconciling data before anyone starts the clinical thinking.
When software takes on that assembly work, the hours per patient go down. A clinic can then serve more patients with the same team, or offer a lower-cost tier that still includes real specialist input. It also makes it realistic for smaller practices and primary care physicians to offer structured prevention without hiring a large staff to coordinate it.
Diagnostics will need to get cheaper and reimbursement will need to catch up before this care is truly broad-based. Those pieces are moving. Removing the operational overhead is the part technology can solve today, and it’s the part we’re focused on.
Editor’s note: After this interview, we learned that Longevitix is in conversations with a director at the Buck Institute for Research on Aging.