Hey everyone. I've been lurking here for a while and finally want to share something I've been building. Fair warning: I'm the person behind this, so take this with whatever grain of salt you need. I'm not here to pitch. I genuinely want feedback from this community because you're the people who think about this stuff the way I do.

The backstory... I'm a dad of five boys, including newborn twins, engineer, and I wear a Garmin 24/7. My wife does too. We started as our own test subjects — not because we're fitness nuts (our step counts would disappoint you), but because we were drowning in health data from wearables, uploaded lab results, and medical records that never talked to each other.

I kept asking myself: why can't I just ask a question and get a real answer from my own data?

Not a dashboard. Not a chart I have to interpret. An actual answer, grounded in my personal data and peer-reviewed research.

What I actually built... I connected Garmin's Health API (sleep, stress, HRV, SpO2, respiration, blood pressure, body composition, skin temperature, activities — 13+ streams) to an AI system that can reason across all of them at once. You can also upload lab results, medical records, and imaging. The system remembers your past conversations, so context compounds over time.

The part I think this sub will care about. Here's the stuff I actually ask on a regular basis. These aren't hypothetical, they're from my real usage:

Simple but useful:

\- "How did I sleep this week?"

\- "What's my HRV trending over the last 30 days?"

\- "Show me my stress levels for the past 3 days"

\- "What activities did I do this week?"

Where it gets interesting:

\- "Does my HRV improve the day after good sleep?"

\- "How does my sleep quality correlate with my stress levels over the last 2 weeks?"

\- "Analyze my stress, body battery, and respiration trends this month"

The ones that blew my mind:

\- "Am I overtraining? Look at my HRV, stress, sleep, and activity data from the last month" — it pulled 4 data streams, correlated them temporally, and gave me an actual assessment

\- "Based on my sleep data, should I be concerned about sleep apnea? What does the research say?" — it looked at my actual SpO2 dips and sleep staging, then cross-referenced medical literature

\- "Given my stress and HRV patterns, what does the research say about my cardiovascular risk?" — personal data + medical research in one answer

\- "How was my cardiac performance in the last basketball workout compared to others over the last 3 months?"

Family sharing (this was a game-changer for us):

\- "Compare my sleep quality to my wife's this week"

\- "Who slept better this week, me or Tyrenne?"

\- My wife can ask about research I've been doing with the AI about our son's skin condition, and it remembers both of our conversation histories

Uploaded labs + wearable data together:

\- "Based on my Garmin data and my recent lab uploads, give me a health summary"

\- "Summarize my lab results and tell me what to watch"

\- "I have a family history of hypertension. Based on my blood pressure readings, what does the literature recommend?"

Visual stuff:

\- "Chart my stress levels over the last 2 weeks"

\- "Visualize my sleep stages for the past 7 days"

\- "Show me a dashboard of my SpO2 and stress trends this month"

\- "Graph my HRV trend over the last 30 days"

We've learned a lot very fast by being daily users. My wife's question — "How was my stress while I slept?" — actually broke our first architecture. It seems simple, but it requires pulling two data streams (stress + sleep), aligning them temporally, and understanding that she wanted stress during sleep hours specifically, not just "stress and sleep." We had to rebuild our entire context protocol because of it.

Another thing: Garmin stores data in UTC. When you work out at 5 PM in Denver, it might register as the next calendar day. Our first version would miss that workout entirely if you asked about "today." Technically correct, completely useless. Those are the kinds of real-world edge cases you only find by actually living with the system.

What this isn't...

\- This is not medical advice and doesn't replace your doctor

\- It's not a fitness app — it's health data reasoning with medical research grounding

\- I don't sell user data. I don't train on user data. No VC. No employees. Just me, in my basement in Colorado, trying to make health data actually useful.

I'm posting here because you all understand the frustration of having data everywhere and insight nowhere. I've been building this for over a year now and I think the quantified self-community is exactly who would push this the hardest and give the most honest feedback.

If you wear a Garmin and you've ever wished you could just ask your data a question — especially one that connects your wearable data with your labs, your medical history, or published research — I'd love to hear what questions you'd want to ask.

The project is called OttnoAI — [ottnoai.com](http://ottnoai.com)

Happy to answer any questions about my background, the architecture, the Garmin integration, or how any of this works under the hood. I'm an open book.

I built something that lets me ask my Garmin data questions I never thought possible — and it changed how I understand my health