top of page


Forward-looking decision-support.


At the heart of Endobits lies our Computation Engine - a collection of proprietary algorithms that understand human physiology unlike any technology before.  


Each algorithm is a building block, together they construct a more powerful Engine to predict the onset of adverse glycemic events. These algorithms are the power behind Endobits, passively reviewing data and constantly cross-referencing each others’ insights, automatically flagging the early warning signs of adverse glycemic events.

Advanced Machine Learning


Endobits algorithms instantly optimize patient data to deliver clinically reliable decision support as soon as possible.

not hindsight!


The Endobits advanced Machine Learning algorithms are designed to identify adverse glycemic events before they happen. 

No Manual
Input Required


Patients enjoy a hands-free experience as Endobits interacts directly with sensor data and is used to capture the complete picture of our users' health. 

AI-based Advanced Glucose Modeling for Better Healthcare


Blood Glucose Decision Support for Patients

Leveraging advanced Machine Learning, our Endobits Blood Glucose Decision Support Model analyzes patient glucose data and calculates future blood glucose trends.  Using this model, the patient can anticipate and avoid abnormal glucose fluctuations.


Nocturnal Hypoglycemia Event Detection (NHE)

Our NHE model leverages the power of neural networks to analyze pre-bedtime data to determine whether a nocturnal hypoglycemia event might occur. Using this model, Endobits helps the patient avoid the possibility of dangerous lows during sleep.


Automated Insulin Dysregulation Detection

Our Insulin Dysregulation Model use advanced Machine Learning to analyze patient glucose data and determine if the patient has suboptimal glucose control. With Endobits the physician can see how many consecutive suboptimal days the patient has had and adjust treatment accordingly.


Severe Hypo/
Hyper Event Detection  

The Endobits Severe Events Model was developed as an additional safeguard layer on top of the Blood Glucose Decision Support model. This model uses advanced Machine Learning to analyze patient data  to  determine if there will be a severe hypo or severe hyper event in the  near future.

Better Patient Care from Machine Learning and Remote Patient Monitoring.

Endobits is a web portal for healthcare professionals. Using Endobits, physicians can view patients’ data without an appointment or a complicated data upload and sharing process.


Endobits streamlines workflows by summarizing analytics and insights for each patient on a user-friendly dashboard, prioritizing urgent cases. When healthcare providers use Endobits patients also benefit from having better control and a greater awareness of their health than ever before.

Mackbook New Endobits Mockup Right 2.png

Compatible with all Leading Continuous Glucose Monitors


Endobits integrates with all leading Continuous Glucose Monitors (CGM) including Dexcom G6/G7 and Freestyle Libre 2. Patients can set up the Endobits Companion App to work with their CGM in a few minutes and once connected with their clinics patients and physicians can all benefit from the advanced healthcare provided by Endobits.

bottom of page