Prioritizing physical health is very important, and ignoring our well-being can really affect our overall health. The traditional healthcare system needs many appointments and referrals, making it hard for patients to get care when they need it. Our client, a healthcare provider, wanted to fix this problem and asked us at vrinsoft to make a new telehealth app with AI. This app helps patients take control of their care and makes healthcare delivery more efficient. This case study will provide detailed information on how we approached and completed this project.
Our client operates primary care clinics that offer accessible and comprehensive healthcare services to local residents. They focus on patient convenience and use technology to improve efficiency and patient engagement. To meet the growing demand for telehealth services, they approach Vrinsoft to create a user-friendly AI-based telehealth app to improve patient access to quality care.
We proposed an AI-powered telehealth app built with native app development for Android and iOS. We built this app using AI for symptom analysis to streamline healthcare. We have also integrated with third-party health monitoring devices and facilitate secure video consultations. To help clinic manage the app, we provided web-based admin panel with management tools for users, appointments, and data.
To provide a performant and cutting-edge AI inventory application, we developed this app using native app development. Here is why we choose this solution.
We utilize native app development so that it can offer better performance with AI. Patients can easily learn about the symptoms, and the app can help them get started by suggesting a healthcare provider and booking an appointment. It will improve healthcare professionals’ time as AI already narrows down the symptoms.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.
Analyzes user-reported symptoms using machinelearning algorithms to suggest potential causes and recommend next steps, empowering patients withinitial health insights.