Care Predict is advancing healthcare technology to specifically focus on Seniors living independently or in group living settings. The following short video explains how CarePredict™ Tempo™ works:

Tempo makes it easier for Seniors to live on their own, while reassuring their family members and friends that they will be alerted when care is needed.
This wrist-worn sensor employs sophisticated software technology and monitors Seniors continuously while learning their activity patterns. CarePredict™ Tempo™ takes motion type, speed, number of steps, duration, and frequency –and combines it with location data. It uses machine learning to learn what is normal activity and what isn’t, and notifies families and caregivers when there is an anomaly. For instance, missing meals, reduced grooming and hygiene, and restless sleep may signal depression while repeating activities abnormally may indicate dementia.
For Founder Satish Movva, the development of this product struck home because he was in search of a better way to monitor his parents’ health when he was not physically near them. With the help of Co-Founder Dr. Krishna Vedala, Satish derived a solution with technology, data, and machine learning.
“We brought Elementz Interactive in early on in the development process when the UX design had just been completed and the features had not been fully thought through and architected, said Satish Movva, founder of CarePredict; this allowed Elementz Interactive to build the foundation of our platform in a way that allowed feature extensibility, flexibility, and takes into account the scalability needed for a global platform that supports multiple languages and country regulations, supporting each of the stakeholders in an aging person’s care circle, from family, caregivers to payers, and group living operators.” Satish Movva
As a technology development partner, Elementz Interactive built the software platform for CarePredict, making it easier for caregivers to sign on and evaluate accurate information in real time.
“We were excited to partner with Care Predict to build their backend administrative dashboards as well as their mobile applications. The challenge was building a product that could be deployed to many different environments and institutions throughout the world. We are privileged to make Care Predict’s vision a reality by using cutting-edge technologies to overcome these challenges.” Niall McSheffrey

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