A Common Ground case study
Where your data
meets your DNA.
Origene is a highly personalized health vault — bloodwork, body composition, glucose, recovery, and genome — built around your code, not the average person’s.
What’s inside
Nine layers of you.
Each layer is its own dashboard, fully cross-linked. Change a supplement in March, watch the marker move in June.
Bloodwork
Every blood panel, every marker, flagged and trended across years — not just the most recent printout.
Body Composition
DEXA scan history with regional breakdowns, lean-mass tracking, visceral-fat monitoring, and bone density.
Glucose
CGM data with daily overlays, time-in-range, and meal-tagged context. Built for protocol changes you can actually see.
Genome
23andMe-grade SNP analysis with deep predisposition reads, trait insights, and a methylation lens you can act on.
Recovery
Oura readiness, HRV, RHR, and sleep architecture tied back to the day’s training and stressors.
PRs & Training
Rolling PR board across every lift, full workout log, and training-volume monitoring — the long arc, not just last week.
Family
A separate dashboard per family member, including child growth tracking and side-by-side partner comparisons.
Supplements & Nutrition
Genetics-informed stacks, macro tracking, carb cycling, and a feedback loop into your bloodwork over time.
Insights
AI-assisted correlations across every layer of your data — the kind of pattern only your own data can teach you.
Screens
The shape of a life’s data.
Every screen below is the real product, populated with fictional sample data.
Walkthrough · Click to unmute
Why we built it
Most health software flattens you to the average. We refused.
Origene started as an internal Common Ground project — a place to hold a decade of bloodwork, half a million CGM readings, full-genome SNP data, DEXA history, and every PR alongside the family that surrounds them.
It’s the kind of tool we’d build for any operator who wants to see their own life clearly. We’re showing the work because the work is worth seeing — and because the way most teams handle personal health data isn’t the way we would.