OligoScan
Minerals and trace elements
Clinical AI
A platform where physicians enter a patient’s studies and get recommendations based on clinical protocols.
DEXA
Bone and body composition
InBody
Body composition
Lab tests
Blood and biomarkers
- Albumin
- 4.5 g/dL
- Creatinine
- 1.04 mg/dL
- Fasting glucose
- 110 mg/dL
- hs-CRP
- 3.59 mg/L
A patient on one screen
Biological ages, 10-year risks and the plan the physician approved. Values are shown against their reference ranges.
Screens are from the production build, in a demo clinic. Patients and names are fictional.
- Client
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- For
- Physicians and clinics in regenerative and longevity medicine
- Platforms
- Web and mobile app
- Plans
- From a single practitioner to clinic networks, 14-day free trial
Upload the studiesPhysician reviewRecommendationPhysician decision
Lab reports and InBody, DEXA or OligoScan results go in as PDFs, scans, photos, Word, Excel or CSV. Every value is extracted with its unit and range.
The physician checks the values against the original report. Nothing enters an analysis until it is approved.
The platform suggests which studies to order and, once results are back, a protocol with its source.
The physician adjusts the suggested plan and approves it. Only then does the patient see it.
Clinical protocols
Recommendations draw on protocols from faculty presentations and conference transcripts. Each one shows its source.
Regenerative medicine
- Exosomes
- Stem cells
- NK cells
- MUSE cell treatment
- Peptides
Adjuvant therapies
- Hyperbaric oxygen
- Red light therapy
- Oxygenation
Longevity and biohacking
- Daily step targets
- Protein intake
- Lifestyle measures
Studies to consider
From symptoms, goals, history and previous treatments, the platform recommends which studies to order first.
When a treatment did not work
The platform recommends the workup that could explain it before suggesting a new protocol.
Published formulas
Risks and biological ages come from versioned equations you can cite. The language model writes the words and never the numbers.
| Model | Estimates | Source |
|---|---|---|
| PhenoAge | Phenotypic (biological) age | Levine et al., Aging 2018 |
| Heart age | Vascular age | D’Agostino et al., Circulation 2008 |
| CANRISK | Type 2 diabetes, 10 years | Public Health Agency of Canada |
| ADA Risk Test | Undiagnosed type 2 diabetes | Bang et al., Ann Intern Med 2009 |
| Pooled Cohort Equations | Heart attack and stroke, 10 years | ACC/AHA 2013 |
| CAIDE | Dementia, 20 years | Kivipelto et al., Lancet Neurol 2006 |
| CKD-EPI 2021 · KDIGO · KFRE | Kidney function and kidney failure | NEJM 2021 · KDIGO 2012 · JAMA 2016 |
Results for a demo patient, age 61.
Built-in assistant
It answers questions about the patient whose record is open, in the clinic’s preferred style.
- Reads approved labs, risks, the plan and visit notes
- Never sees names or contact details
- Drafts SOAP notes and plans for the physician to edit
An app for patients
Patients see the approved plan and its notes in the app. The app connects to Apple Health and Apple Fitness.
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Apple Health -
Apple Fitness
Book About You
The clinic gives the patient a PDF report in its own brand, from one page to a full breakdown. Patients don’t need to register.
Clinic workspace
The home screen shows patients’ average pace of aging, new patients and the results waiting for review.
- Starter
- A single practitioner
- Growth
- Up to 6 clinicians, the clinic’s logo and colors
- Enterprise
- Networks and health systems, 25 seats included
Protecting medical data
Separate clinics
Each clinic’s data is separated by row-level security in the database.
Encryption
Names, contacts and birth dates are encrypted and stored apart from clinical data.
Audit log
Every view and change of medical data is written to an audit log.
AI without identities
The assistant sees de-identified clinical context. Clinic data never trains models.
Something similar?
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