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EASY LIFE
WITH DIABETES

AI based APS for people with type 1 diabetes

Clinical trials phase

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VISION

We’re Changing the Way the World Thinks About Diabetes

Most of existing APS solutions are very complicated and takes lots of time and knowledge to start using them.

The key goal of OMNIA to make life with diabetes a lot easier. You need only 10 minutes to start.

About

About

OMNIA is a unique algorithm based application designed to protect against the possible complications associated with diabetes.

The main task of the application is to maintain glucose within the target safe range of 3.9-10 mmol / L and to avoid the occurrence of low blood glucose values (blood hypoglycemia).

OMNIA
TODAY

Application
Fully working app with build-in unique OMNIA algorithm

Community
More than 2000 people involved in chats
and social media

Strong team
Professional endocrinologists, developers designers and managers from France, Austria and Russia.

FUTURE ECOSYSTEM

Online doctor support
Stay connected with your doctor online in the app
Multiple devices
Smartphones, watches & web
Type 2 ready
Covers patients with both T1D & T2D

Public Monitoring
Integration with health care systems

More pumps & pens
Adding new pumps, pens & sensors to fit more users

Growing community
To help each other and share usage tips

Child control
Parents are watching after child's compensation

Tech

Tech

To develop the final algorithm we first had to create several unique technologies

Metabolism simulator

The simulator allowed us to generate more than 100 million values for training the neural network, giving us training to implement the glucose prediction by the neural network.

Carbohydrate absorption monitoring

A detailed analysis of carbohydrate digestion allows you to achieve accuracy in calculating the coefficients and efficiently process information about carbohydrates.

Neural network training platform

A platform developed by the OMNIA team for building various neural network architectures designed to build, train and use neural networks. Based on this platform, a suitable neural network architecture was created to calculate the sensitivity to insulin, carbohydrates and natural glucose growth (coefficients).