A US-based health technology company wanted to enhance its smart health bands with intelligent, voice-enabled capabilities that go beyond routine activity tracking. The goal was to make health information more accessible, provide personalized insights, and help users identify potential health concerns earlier.

To address this need, eInfochips developed an AI-powered solution integrating a voice bot, a web-based health dashboard, real-time sensor data processing, and machine learning models. The solution enables users to retrieve health metrics through voice commands, receive alerts about abnormal readings, and access personalized health insights. It also incorporates machine learning models for identifying potential eye diseases and respiratory abnormalities through image classification and audio signal analysis.

Built on Microsoft Azure, the solution achieved over 80% accuracy in identifying potential illnesses, based on the implemented models, and established a scalable foundation for future wearable health features.