For Researchers

Structured insulin-sensitivity data, without building your own app.

Mirri Med gives research teams a faster path to structured, device-agnostic data on real-world insulin sensitivity.

Real-world diabetes data is messy by nature — different devices, different logging habits, different definitions of 'a normal day.' Mirri Med was built to bring some structure to that mess without asking participants to change hardware.

01

Real-world data is messy. Yours doesn't have to be.

Mirri Med organizes participant entries around a consistent structure — the CarbIn Factor™ — instead of leaving your team to reconcile a dozen different logging formats.

One structure across participants
Structured entries

02

Participants use what's already in their pocket.

Bring-your-own-device data collection lowers the barrier to enrollment — no new hardware to distribute, track, or collect at the end of the study.

Lower friction, faster enrollment
BYOD collection

03

CarbIn as a structured variable.

The CarbIn Number gives your study a consistent way to compare insulin response across participants, meals, and activities — built from the ground up as a research-usable metric.

A study-ready metric
CarbIn Factor™

04

Local-first storage, IRB-minded from day one.

Data is stored locally to support the privacy and security expectations your protocol already has to meet.

Built for IRB review
Data handling

Why it works

What academic & clinical researchers get from Mirri.

A ready-made insulin-sensitivity metric

The CarbIn Number gives your study a consistent way to compare insulin response across participants.

Bring-your-own-device data collection

Reduce enrollment friction — participants don't need new hardware to take part.

Built with IRB standards in mind

Local-first data storage supports your protocol's privacy requirements.

Mirri Med exists to save your team the months it would take to build this tooling from scratch.

MIRRI FOR ACADEMIC & CLINICAL RESEARCHERS

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Explore Mirri Med for your study.

We're partnering with a small number of research teams early on.