Biological age intelligence
The aging clock,
for every
population.
A global machine learning platform for biological age intelligence. Proprietary blood based aging clocks, calibrated for every major world population, delivered by API to the institutions that need them.
CHRONOLOGICAL
45.0 yrs
ALPHA AGE
39.2 yrs
01 // The premise
Chronological age is a broken instrument.
Two forty five year old executives walk into a clinic. One is biologically thirty nine. The other, fifty six. Chronologically identical. Physiologically separated by seventeen years of accumulated function and decline.
The answer is present, latent, in the blood already sitting in the laboratory refrigerator, waiting to be read correctly. Alpha exists to read it, and to deliver the answer, calibrated, to the systems that need it.
100k+
Blood samples in corpus
7
Population models
Gen 2 + 3
Unified architecture
02 // Population catalog
Seven models. One architecture. Every major population.
Global calibration map
Status
In production
Alpha SA
South Asian
India, Pakistan, Bangladesh, Sri Lanka. Reference cohorts: LASI Wave 1, ICMR, clinical partnerships.
Input
Blood biomarker panel
Outputs
Alpha Age + Alpha Pace
Architecture
Unified deep learning
Delivery
REST API + SDK
03 // The output
Two coupled measurements. One unified model.
Alpha Age reports mortality anchored biological age in years. Alpha Pace reports the biological velocity of decline. Both are produced by a single deep learning model, internally consistent by construction.
{
"population_model": "alpha_sa_v2.4",
"alpha_age_years": 39.2,
"alpha_pace": 0.87,
"chronological_age": 45.0,
"age_delta_years": -5.8,
"system_breakdown": {
"inflammation": { "z": -0.42 },
"metabolic": { "z": -0.61 },
"hepatic": { "z": 0.18 },
"renal": { "z": -0.09 },
"hematologic": { "z": -0.33 },
"endocrine": { "z": -0.51 },
"cardiovascular":{ "z": -0.44 },
"immune": { "z": -0.28 }
},
"mortality_hazard_ratio": 0.71,
"audit_id": "af8c...9d21"
}Latency p50
180 ms
Regions
Multi
SLA
99.95%
04 // Scientific lineage
Built on the peer reviewed foundations of the field.
All publications →Aging · 2018
Levine et al. An epigenetic biomarker of aging for lifespan and healthspan (PhenoAge).
doi.org/10.18632/aging.101414
Read paper
eLife · 2022
Belsky et al. DunedinPACE, a DNA methylation biomarker of the pace of aging.
doi.org/10.7554/eLife.73420
Read paper
Aging · 2019
Lu et al. DNA methylation GrimAge strongly predicts lifespan and healthspan.
doi.org/10.18632/aging.101684
Read paper
Genome Biology · 2013
Horvath. DNA methylation age of human tissues and cell types.
doi.org/10.1186/gb-2013-14-10-r115
Read paper
05 // Who Alpha serves
A B2B intelligence layer. Four institutional customers.
Insurance
Population calibrated biological age for underwriting, cohort analytics and new longevity linked policy products, across every jurisdiction you write in.
For insurersHospitals & health systems
Embed biological age assessment into preventive care pathways, executive health and cardiovascular clinics, integrated by API into existing clinical software.
For hospitalsLongevity clinics
An instrument you can stand behind. Published validation, population specific calibration, both state and pace measurements, delivered under your clinical brand.
For clinicsClinical research
Alpha Research: a validated biological age endpoint for multi site, multi population trials in geroprotection, longevity therapeutics and lifestyle intervention.
For research06 // The moat
Four asymmetric assets, compounding together.
01
Multi population data corpus
Over 100,000 blood samples aggregated across the world's major population strata. Years of licensing, partnership and data sharing agreements. A durable head start no challenger can shortcut.
02
Unified Gen 2 + Gen 3 architecture
A single deep learning model that produces mortality anchored biological age and pace of aging together, internally consistent by construction.
03
Jurisdictional neutrality
Registered in Hong Kong. Commercial reach into every major market without the political friction of a US or India domiciled competitor.
04
API first, B2B first business model
We do not compete for end consumers. We build the intelligence layer beneath the institutions that reach them. Durable economics, lean infrastructure, deliberate sales cycle.
Input layer
Standard blood panels from existing pathology infrastructure. No new hardware, no new sample logistics.
Headquarters
Lippo Centre, Admiralty, Hong Kong SAR. A jurisdictionally neutral base for global institutional deployment.
07 // FAQ
Common questions.
For technical, scientific or commercial detail, book a briefing with the Alpha team.
Book a briefingIs Alpha a consumer product?+
No. Alpha is a B2B intelligence platform. When an individual receives an Alpha derived biological age, they receive it through their insurance company, hospital, longevity clinic or research protocol, never from Alpha directly.
What input does the Alpha model need?+
A standard panel of blood biomarkers spanning eight physiological systems. Alpha consumes the outputs of existing pathology infrastructure. It does not compete with laboratory networks.
How is Alpha different from existing aging clocks?+
Every serious aging clock in production today is calibrated for one reference population. Alpha is architected multi population from day one, and unifies second and third generation outputs in a single model.
Why registered in Hong Kong?+
Jurisdictional neutrality. It gives Alpha commercial reach into every major global market without the political friction of a US or India domiciled competitor.
Is customer data used for retraining?+
No customer data is used for model retraining without explicit contractual opt in. All retraining data is aggregated and de identified before use. Alpha operates as a data processor, not a controller.
Contact
Book a briefing.
Deploy the intelligence layer.
For insurance underwriting, hospital integration, clinic deployment or research collaboration, talk to the Alpha commercial team.