Personal Project · Living with T1D

The Time
In Range
Project

I got diagnosed with Type 1 Diabetes and couldn't find tools that actually helped me understand my own data. So I started building them. This is that project — and Betawise is what's coming out of it.

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Understanding TIR

What is Time
In Range?

Time In Range (TIR) is the percentage of time a person with diabetes spends with blood glucose between 70–180 mg/dL. A1C gives you a 90-day average and nothing else — TIR shows you the actual picture: the highs after meals, the 3am lows, and the stretches where things are actually going well. It's the number that tells you what's really happening day to day.

Very High
> 250 mg/dL
<5%
High
181–250 mg/dL
<25%
In Range ✓
70–180 mg/dL
≥70%
Low
54–70 mg/dL
<4%
Very Low
< 54 mg/dL
<1%
70%
Target TIR for most people with T1D
55%
Where the average T1D patient lands — 4hrs daily out of range
1.6M
Americans living with Type 1 Diabetes
22%
Complication risk reduction per +5% TIR

Why It Matters

The numbers
behind all of this

22%
Lower Complication Risk

Each 5% bump in TIR correlates with a 22% drop in retinopathy risk. That's not a rounding error — it's sight. The research connecting TIR to real outcomes is what makes it worth tracking obsessively.

55%
Where Most People Land

The average T1D patient hits 55% TIR. That's nearly 4 hours a day outside the safe zone. The 15-point gap between where people are and where they should be is exactly what this project is trying to close.

500M+
People Living With Diabetes

Over 500 million people worldwide have diabetes. The tools most of them use were designed for clinical settings, not for actual daily life. There's a lot of room to do better.

My Story

A diagnosis that
changed everything

I got diagnosed with Type 1 Diabetes, and on day one someone handed me a CGM and said "try to stay in range." Nobody walked me through what that actually meant — what spiked me, what dropped me, why the same dinner hit differently on different days. I just watched the numbers and guessed.

I'm a product person by trade. My job is to look at a messy system, figure out where the information is, and build something that helps people make sense of it. The gap I kept running into with T1D tools was obvious: the data was there, the CGM was generating it constantly, but nothing was actually helping me understand it in plain terms.

That's where the Time In Range Project started. And that's where Betawise came from — a product built to give T1D patients a clearer read on their own data, without needing a clinical background to interpret it.

Every feature comes from a real moment I've had — a confusing spike, an unexplained low, a week where things clicked and I wanted to know why. That's the whole point.

"Nobody walked me through what staying in range actually meant. I just watched the numbers and guessed."
The Problem

CGMs produce a reading every five minutes, all day, every day. That's hundreds of data points — and most T1D patients have no good way to see patterns across them or know what to do next.

Betawise

The product coming out of this project. Built to surface what your CGM data is actually telling you — in plain language, without the clinical jargon — so you can make better decisions day to day.

Why I'm Building It

Because I wanted it to exist and it didn't. Every hour spent out of range has a cost. Better tools change that — not just for me, but for the 1.6 million other Americans with T1D.

Approach

How I'm
building it

01
Start With the Experience

Not the data, not the technology — the actual day. What does it feel like to be high at 2pm and not know why? What does it feel like to crash during a run you've done a hundred times? Those moments are the brief. Talking to patients, parents, and endocrinologists makes sure the product is solving the right version of the problem.

User Research
02
Figure Out What the Data Can Actually Tell You

Dexcom, FreeStyle Libre, and other CGMs generate a reading every five minutes. That's a lot of signal — and most of it sits unused because the interfaces don't help you see across it. Mapping where the patterns live and where the gaps are is step two.

Data Architecture
03
Design for Real People, Not Clinicians

The best T1D tools I've used show me a number. The ones I actually want to use tell me something. There's a difference between displaying data and helping someone understand it. The design work here is about making TIR feel like a score you can move, not just a stat you track.

Product Design · UX
04
Build Betawise

Betawise is the product coming out of all this. It uses the same LLM and data techniques I've applied at the UN — natural language summaries of glucose trends, pattern detection, plain-English explanations of what your numbers are doing and why. The goal is a tool that feels less like a dashboard and more like having a smart conversation about your own health.

Betawise · LLM · AI
05
Share It

The more T1D patients know about Time In Range, the better questions they can ask their doctors and the better tools they'll demand. This project is part product, part advocacy — putting the work out there so other people can push for the same kind of clarity in their own care.

Advocacy · Community

Advocacy

Why I keep
working on this

T1D Diagnosis · Personal Mission

T1D doesn't take days off. It's there at breakfast, at the gym, at 3am. You get used to it, but you never stop managing it — and the tools most people have to do that are stuck somewhere between a spreadsheet and a medical chart.

For me, advocacy just means building things I wish existed and being honest about why. I'm not running campaigns. I'm trying to make something that helps — first for myself, then for anyone else dealing with the same thing.

That's what Betawise is. Not a grand mission statement, just a tool that takes your CGM data seriously and talks to you like a person instead of a patient record.

The Daily Reality

Dosing insulin, timing meals, figuring out why Tuesday's run wrecked your numbers but Thursday's didn't. T1D is constant problem-solving with incomplete information. Better data interpretation cuts that friction down.

The Gap

CGMs are incredible pieces of technology. The apps that come with them are not. There's a real opening for something that actually explains what the data means — and Betawise is being built to fill it.

Why Now

LLMs are finally good enough to take messy, personal health data and return something genuinely useful. The technology caught up to the problem. This is the right time to build it.

Get In Touch

Want to talk
about this?

If you're building in T1D, digital health, or you just want to compare notes on what it's actually like to live with this — I'm easy to reach.