Non Invasive Glucometer
Artificial vision device for glucose measurement capable of classifying glucose levels with greater assertiveness than operating puncture glucometers.
Our Technology

Computer Vision
Computer vision is a field of Artificial Intelligence, which uses self-training Machine Learning algorithms (specifically Deep Learning or Neural Networks) to enable computers and systems to derive meaningful information from digital images, videos and other visual inputs. We use Computer Vision to identify glucose levels in live tissue images by processing the image under different parameters.

Deep Learning
Deep Learning is the automated process of using data and algorithms to improve the accuracy of a system. We use semi-supervised and supervised learning methods, which enable our algorithms to train by clustering unlabeled data sets to identify basic glucose parameters, and then guide our readings towards higher accuracy by introducing labelled data sets such as known high or low glucose levels.

Recommendation Engine
Recommendation Engines are an application of Machine Learning algorithms that allow to discover trends within relatable data sets. Once we have identified and organized data from our users and their glucose level readings, we correlate their values with external data sets that provide us with the possibility to generate health recommendations according to user preferences and lifestyles.
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Help us create a healthier future.
Prediabetics in the U.S.
It is estimated that 1 out of 3 adults has prediabetes, that would mean that 80 million adults in the U.S. may develop a serious condition. All of them could benefit greatly from easy to deploy prevention models.
Diabetics in the U.S.
As of 2020, there were more than 34 million people in the U.S. with diabetes, however, it is estimated that close to 10 million people may be undiagnosed and unaware of their condition. The numbers could be much more accurate if diagnosis were more accessible.
Cost of diagnosis in the U.S.
The cost for diabetes diagnosis in the U.S. was close to $ 245 billion dollars in 2012 and has been rising yearly on account of new cases. If more accesible diagnostic devices were to be implemented, the cost could decrease drastically.
Diabetics in 2030
It is estimated that 578 million people in the world will have diabetes by 2030, that number is expected to rise to 700 million by 2045. We are in urgent need of massive prevention campaigns through improved glucose measurement.
Credentials and Validations
CENAM
Validation protocol with the Mexican National Metrology Center for observing diluted glucose.
SECTEI
Categorized as a strategic project for Mexico City’s Science and Technology Department.
IMSS
Joint validation protocols with the Mexican Social Security Institute for glucose identification.
SEDESA
Validation protocols with Mexico City’s Health Department for glucose measurement.
INCMNSZ
Validation protocol with the Mexican National Institute for Medical Sciences and Nutrition for glucose observation.
CONACYT
Project selection and funding by the Mexican National Council for Science and Technology.