Build the First Health-Data Giant: Why an All-In-One Would Win

Hey there! Welcome back to Founder Mode!

You shouldn’t need five wearables, three lab portals, and a spreadsheet to know if you’re healthy. Yet most of us who are trying to optimize health juggle exactly that. The real unicorn fixes this mess by pulling every signal into one clear view—and acts on it for you. This is a company someone should build!

Why Fragmented Data Holds Us Back

Numbers live in silos. Sleep sits in Oura, workouts in Whoop, glucose in Stelo, blood tests in Function Health, full-body MRI/CT scans in Ezra.
Insight dies in translation. Each tool explains its slice but never the full picture—so early warnings slip through.
Users burn out fast. Manual exports, duplicate alerts, and competing advice create friction. Simpler wins.

What “All the Data” Actually Means

A winner ingests ALL streams automatically. No CSV uploads, no lost APIs. Even better if they also deliver ALL the wearables I need.

The "Blueprint" for a Billion-Dollar Health Platform

1. Unified Pipe

Secure read/write connections to every major tracker, lab, scanner, and EHR. HIPAA baked-in from day one.

2. Long-Term Memory

A single vector store that keeps lifetime health events, not just 30-day summaries. Makes it easy to connect any LLM.

3. LLM-Driven Reasoning

The model asks: “Given Kevin’s glucose spike, sleep debt, and travel schedule, what change prevents weight gain?” Then it writes the plan. Give me a plan to peak recover for big event Tue. Give me a plan to lose 3% body fat in next 90 days.

4. Closed-Loop Coaching

Advice isn’t passive. The app schedules workouts, adjusts calorie targets, and orders refill labs—automatically.

5. Outcome Score

One nightly grade tied to risk reduction (heart, metabolic, mental). If the score dips, the user sees exactly which metric triggered it and WHAT to do NOW to adjust. It's all about the "next best action".

What’s Happening Already

Oura × Dexcom (Stelo): Dexcom’s strategic investment green lit the CGM path for mainstream wearables.
Function Health + Ezra: Blood, urine, and MRI+CT under one roof—an early taste of true full-stack testing. Will be great to have insights across both.
Guava & Heads Up: Both aggregate multiple devices and labs, but still stop short of real-time reasoning.
Whoop MG: Adds daily blood-pressure trend to strain and recovery data.

The pieces exist; nobody has snapped them together end-to-end.

My Personal Stack (Today)

Night: Eight sleep. Whoop and Oura on,
Morning: Withings scale first thing, Stelo CGM report, Whoop recovery score, Eight sleep score if I'm home.
Quarterly: Function Health blood draw + DexaFit (body fat)
Annual: Ezra MRI+CT.

Key Takeaways

1. Data Alone Isn’t Enough.

Value lives in translation across sources, not bigger charts.

2. Early Signals Beat Late Treatments.

Continuous, cross-checked inputs catch trouble while it’s cheap to fix.

3. The First True Aggregator Wins Big.

Own the pipe, store, and coach, and you become the operating system for personal health.

4. Distribution Favors Consumer Trust.

Start as a subscription app, nail outcomes, then partner with insurers and employers. Company's will pay to have fitter and healthier employees.

Final Thoughts:

I’m betting the next health unicorn is the one that makes “How am I doing?” a single-tap answer. If you’re building in this space—or want to—I’d love to hear from you. In the meantime, keep your own data flowing and your feedback loops short. Your future self will thank you. Stay healthy!

Pro tip: It’s a smart habit to save all your health data and ask your assistants to compile it as PDFs. You’ll thank yourself when you need to reference trends, share with a provider, or train your own health agent. If you want an amazing assistant for this kind of task, I highly recommend Athena EAs.

See you next week,

-kevin

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Kevin Henrikson

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Kevin Henrikson

@kevindegods

I run multiple companies, sleep 8 hours a night, and still have time to see my kids grow up.
My secret? I built a 3-layer system around my brain:
→ Delegation
→ Outsourcing
→ AI agents
Here’s how I operate at scale (so you can too):