GlucIQ exists because diabetes meal decisions still feel like guesswork.

We are building a focused mobile app for people who need more than a carb total: meal photos, editable estimates, glucose response, insulin context, and a record that is easier to discuss later.

Privacy-led data model

Designed for local-first storage.

GlucIQ is designed to manage core records locally. Cloud processing and integration data flows will be documented in the relevant app flow before launch.

  • Local core

    Core records are intended to be managed on the device first.

  • Explicit exceptions

    Cloud, support, and integration flows will be explained in context.

  • Deliberate sharing

    Export and sharing remain explicit user actions.

Built by AviyanLabs LLC

GlucIQ is launch-stage software. Public claims stay tied to implemented mobile workflows, documented integrations, and clear safety boundaries.

Meal → response

one editable record from estimate to review

Dexcom + LibreLinkUp

documented integration paths in launch validation

Fat-Protein Units

FPU-aware insulin math, rare in consumer apps

Editable by design

AI estimates stay reviewable before saving

Make every logged meal easier to trust, correct, and review.

Food tracking apps often stop at macros. Diabetes routines need the next layer: what the estimate meant, what glucose did after the meal, whether device data was connected or manual, and what should be discussed with a clinician.

GlucIQ is designed around that record. The app helps capture a meal quickly, keeps estimates editable, shows reasoning when insulin context is displayed, and keeps medical authority with the user and licensed care team.

Editable first

AI should start the record, not finish it. Every estimate has to be easy to correct before it becomes part of a diabetes timeline.

Clear boundaries

GlucIQ can organize meal, glucose, and insulin context, but it does not replace licensed clinical advice or issue dosing instructions.

Useful without perfect sync

Device integrations matter, but manual logging has to remain a first-class path when a CGM connection is incomplete or unavailable.

Privacy by default

Health-adjacent data should stay local-first wherever possible, with sharing and support workflows explained before users rely on them.

What we are shipping, and what comes next.

The website should earn trust by saying what is real today and what is still being prepared.

Now

Meal photo analysis, editable nutrition estimates, glucose timeline context, and insulin formula visibility.

Launch

Public mobile app release, store-ready privacy/support pages, founding-member pricing, and expanded onboarding documentation.

Next

More device/provider coverage, clinician-friendly review exports, and a stronger evidence library for diabetes education content.