Multi-omic longevity engine
Genome, bloodwork, and wearables, synchronized into one live Biological Twin that reverses cellular aging on autopilot.
The problem
Your genome maps inherited risk but stays frozen. It can't track the rate your cells are actually aging today.
Blood, urine, DEXA scans and MRI capture what's happening inside, but episodic panels surface damage months after the early markers have already started to drift.
Your ring and watch see strain and poor recovery, but stay blind to the particle load and inflammation driving it.
The integration layer
Every modality compiles into one computational core that estimates your biological age in real time, then routes a daily protocol, with the rigor of mission-critical software.
The living biological twin
Most wellness advice guesses at your macros, your sleep, your supplements, then hopes. We don't guess. We treat the body as an engineering system and synthesize every signal, biomarkers, DNA, wearables, lifestyle and scans, into one live biological twin. A closed-loop view of your biology that our engine reads to systematically reverse biological aging and unlock peak physical and mental performance.
WHAT WE MEASURE
WHAT CHANGES
Closed loop
Genome and 87 markers set your immutable baseline.
Wearables feed the twin continuously, not annually.
The engine flags drift across every layer at once.
A precise protocol patch lands on your dashboard at 07:00.
Grounded in the science
Every estimate traces to published methods and an explicit tier of evidence. Validated biological-age clocks, the hallmarks of aging, and models trained on large population cohorts, with clinical guardrails on every recommendation.
Two validated biological-age clocks, Levine 2018 and KDM-BA, computed as transparent benchmarks and tracked continuously.
Non-linear marker interactions learned from UK Biobank and NHANES, hundreds of thousands of records, not a single hand-tuned formula.
Renal and metabolic limits follow KDIGO and the 2021 CKD-EPI equation, with a physician authorizing every protocol.
Research network
Our research members are working scientists and clinicians who contribute domain expertise, review methodology, and keep our protocols grounded in what the evidence actually supports.
Clinical Geneticist
Medical Genetics Institute
Physician and molecular geneticist with over 18 years across clinical medicine and research genetics. Directed the Molecular Genetics and Cytogenetics Lab at King Fahd Medical Research Center, King Abdulaziz University, one of the Arabian Peninsula's leading biomedical research institutions, overseeing day-to-day operations, clinical genetics workflows, and genetic counseling. His research interests sit at the intersection of cytogenomics, inherited disease risk, and population-level genetic variation. His work is directly relevant to calibrating longevity protocols for non-European ancestries.
Clinical Reviewer · Internal Medicine
Guru Gobind Singh Medical College & Hospital, Faridkot
Physician (MBBS, MD General Medicine) and a Gold Medalist in her MD, currently Senior Resident in the Department of General Medicine at Guru Gobind Singh Medical College & Hospital, Faridkot. Her practice spans internal medicine, critical care and emergency medicine, diabetes, hypertension, acute coronary syndrome, thyroid and inflammatory disease, with hands-on ICU, cardiology and bedside-procedure experience (ACLS, echocardiography, ECG and ABG interpretation). Her MD research studied the neutrophil-lymphocyte and platelet-lymphocyte ratios as markers of diabetic nephropathy in type-2 diabetes, the same inflammatory ratios our engine computes. At Antiaging Labs she is the physician in the loop: every protocol passes her clinical safety review, and she reads each member's cardiometabolic panel the way a treating doctor would.
Field notes
New studies and biohacking claims, read the week they land and written in plain English: what it means, what's hype, and what to do.
Research decoded, biomarker explainers, and honest reads on longevity claims. No hype, no selling.
Fifteen operators, founders, and investors to stress-test the engine before commercial deployment.
Zero-knowledge architecture
Your genome, scans, and biometrics are decoupled from your identity at the database edge, so your most sensitive data is never exposed, sold, or used to train anything but your own protocol.