Oura's app shows you scores. AI shows you why — across months of your own data.
The Oura Ring captures sleep stages, HRV, body temperature, and activity in a clean export. The data is excellent. The interpretation is generic.
The Oura app gives you a daily score and a generic tip. It can't say: 'your deep sleep collapses on weeks where you train more than 4 days' — but your data can.
Use AI to read the literature on the specific Oura signals you care about (e.g. nocturnal body temperature trends, sleep latency, HR dip).
Export your last 180 days from Oura's web dashboard. Have AI build a personal ledger that maps Oura signals against your training, meals, alcohol, and travel.
Use Oura's existing data as your baseline. Run a 14- or 21-day single-variable experiment. AI handles the design, the check-in, and the read-out.
Paste any of these into the AI chat tool you already use. No setup.
I have 90 nights of Oura data. For each night I have: total sleep, deep %, REM %, latency, restlessness, average HRV, lowest HR, body temperature deviation. Identify the 3 inputs most predictive of my best sleep score nights.
Oura's readiness score is a black box. Using my last 60 days of HRV, resting HR, body temperature, and previous-day activity, build me a transparent personal readiness model I actually understand.
I've pasted 3 months of nightly body temperature deviation. Find the cyclical pattern, label likely phases, and tell me where my temperature trend differs from the textbook description.
Yes. Both export the same core signals. The method is device-agnostic.
You keep historical exports. AI lets you keep getting value from that data even if you stop paying for the app.
Oura's web dashboard exports CSV. The course walks through the exact steps and the prompts to feed it to AI.
Everything we’ve published that touches this topic — refreshed automatically as new entries ship.
What ChatGPT is good and bad at for mental health support — an honest framework.
An honest framework for using ChatGPT for mental health support: what it is genuinely good at, where it is dangerous, and a four-line script to keep a thread safe. Not therapy. Not nothing.
Three free chat tools, three different jobs
Perplexity for research, Gemini for ledger, ChatGPT for protocol. Why we picked these three, what each is uniquely good at, and what to swap if any of them changes.
One scheduled prompt replaced three apps I was paying for — and I feel weird about it.
Scheduled prompts inside free AI chat tools quietly replace habit, meal-planning, and weekly-review apps. Why that matters, and what's actually worth paying for.
The research was never proportionally about women. The apps inherited the gap.
Women's health was historically under-researched, and the apps inherited the gap. Here is the four-line daily note, the four-cycle read-back, and the one paragraph that finally moves a GP visit past “cycles vary.”
The 60-year-old mum who got healthy without any of the apps.
For mums fifty and over, the bottleneck is not data — it is the cost of producing it. Four honest lines a week, read by a practitioner, beat any app stack you cannot sustain.
We are our own case study
Wellness & AI built its own recommendation engine using the 3-Layer Stack it teaches. Browse signals, affinity scoring, dismiss-to-learn. Here is why eating your own cooking is the only credible proof.
Computer Vision Unlocks Deeper Nutrient Insights
A practitioner refines dietary recommendations by leveraging image analysis to quantify food intake with greater precision.
Automated Health Data Flow for a Busy Executive
A streamlined system for health data collection and analysis improved decision-making for a demanding schedule.
Bridging the Gap Between Movement and Pain Thresholds
A physiotherapist integrated visual analysis to refine client recovery protocols.
Enhanced Nutritional Insight for Individual Wellness
An individual leverages automated data flows to refine dietary choices and improve well-being.
Mapping the terrain of practitioner burnout
A practitioner used a reasoning chat tool to navigate the complexities of burnout research, identifying key areas for deeper focus.
Activity Trend Recognition for Personalized Energy Management
An individual leverages automated data synthesis and pattern identification to inform daily routine adjustments for sustained energy.
AI for Whoop
Whoop charges a monthly fee for an opaque score. AI lets you read your own strain and recovery data and decide what's actually working.
AI for Apple Health
Apple Health silently collects years of your data. Use AI to export it, read it, and turn it into one clear page about your body.
AI for Garmin
Garmin Connect collects years of training, HR, sleep, and stress data. Use AI to find patterns the app's badges don't surface.
AI for Fitbit
Fitbit's most useful insights live behind Premium. AI lets you read your own export and skip the upsell — even after Google's changes.
The free 10-day email challenge teaches the same method on whatever data you already collect. No credit card.