3D Polygon Food Restoration — GlucoUs Core Tech
Launching July 2026

Precise Meal Measurement
is the Start of Precise Logging

Accurate carb counting with a single photo,
making meal logging easier.

*Measurement results are for reference only and may vary by individual.

Core Technology

Why Precise Measurement is Possible
Without a Scale

We restore food from photos into 3D objects to calculate actual volume.
Simpler than a scale, more accurate than guessing.

2D Food Photo
2D PHOTO
① 2D Photo
A single smartphone shot
360° Rotation of 3D Restored Food Model
3D MESH
AI 3D Mesh Conversion
② 3D Volume Restoration
Calculating hidden volumes
Accuracy Comparison
Carb Margin of Error (Lower is better)
~40%
Legacy AI¹
Image Analysis Based
≤20%
GlucoUs
Physical Measurement Based
③ Meal Size Estimation
Aiming for 2x higher accuracy than GenAI
¹ Pouladzadeh et al., IEEE TIM, 2014 · Internal CGM n=30,673
3D Mesh Restoration

Precise with a single photo,
calculating even the hidden carbs.

Just take a picture showing the plate. AI restores the food surface into a 3D mesh, precisely measuring unseen volume and carbohydrate amounts.

Food recognition via smartphone photo
AI-based precise meal measurement
From decision to logging in just 2 steps
Calculate Today's Carbs
GlucoUs App Camera Screen
Start carb counting with one photo
Data Flywheel & Ecosystem

A virtuous cycle of precise records,
transforming the future of the dietary habit ecosystem.

Beyond a simple logging tool, GlucoUs acts as the core terminal and engine where precise user data creates a virtuous cycle, driving a massive ecosystem of artificial pancreas system integration, dietary habit research, and awareness.

The Engine

Data Flywheel

Precise logging creates high-quality data, and improved services return as better records. The three gears interlock to start a virtuous cycle.

Virtuous
Cycle
User Engagement
High-Quality
Data Collection
Research &
Improvement

※ All data collection is consent-based, safely pseudonymized, and used solely for metabolic research and algorithm enhancement.

The Impact

One Terminal, Three Futures

Advanced precise carb data, refined through the flywheel engine, extends beyond individual logging to innovate the entire dietary habit ecosystem.

APS Guide

Artificial Pancreas System Integration

Precise meal data is a core input for artificial pancreas algorithms. We lay a solid foundation for building fully automated closed-loop APS.

View Guide
Coming Soon

Providing Precision Dietary Habit Research Data

Real-world multimodal data of meals and CGM accumulated through research institution collaborations can directly contribute to next-gen dietary habit and metabolic research.

To be released after app launch
Awareness

Improving Metabolic Metrics & Dietary Awareness

Through our proprietary metabolic simulator, anyone can intuitively experience the relationship between meals and metabolic response, expanding healthy awareness.

Experience Simulator
Our Findings

"When you estimate by eye,
you can't know your meal accurately."

GlucoUs analyzed over 30,000 actual meal log data points over 7 months. The result was clear: roughly estimated logs were of little help in understanding our bodies.

Conventional Method (Guessing)
Relation between Meal Size & Logging Accuracy
No Pattern

The graph is scattered randomly. Even when thinking you ate less, the actual amount was often much higher. Eyeballed records made it completely impossible to gauge actual meal size.

Precise Measurement (Scale)
Relation between Meal Size & Logging Accuracy
Consistent Logs (20x Clearer)

Knowing the exact amount reveals a consistent diagonal pattern. It clearly shows a pattern where the logged amount matches exactly what was eaten, being 20 times more accurate than guessing.

* GlucoUs internal data analysis (approx. 30,000 logs, over 7 months) · This data is not for medical diagnosis.

Phase 1 Closed · Phase 2 Preparing

Phase 2 Recruiting,
We'll let you know first.

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