Medivice

Inspiration

The medical industry still relies heavily on legacy systems that often slow down processes for both patients and doctors. We saw an opportunity to modernize patient intake by reducing repetitive tasks and freeing up doctors’ time. Our idea began with figuring out how we could save time for doctors. We realized one of the ways we can do this is by automating the collection of preliminary patient information such as personal details, symptoms, and the reason for their visit.

What it does

Medivice allows patients to call an AI assistant that will gather important patient intake information and record the data. Then the application provides a dashboard for doctors to utilize and view updates from patients about their most urgent issues, symptoms, and conditions, and how they could be addressed.

How we built it

We used OpenAI, Vapi, Phenoml, Deepgram, and FastAPI for the backend, and NextJS for the frontend patient information dashboard.

Challenges we ran into

Integrating with Vapi and other APIs
Debugging null errors and handling edge cases with AI
Balancing speed of development with system reliability

Accomplishments that we're proud of

Building a working prototype in just a few hours
Creating a functional pipeline from patient call → AI intake → doctor dashboard
Demonstrating how AI can meaningfully save doctors time

What we learned

AI has enormous potential in healthcare and is very cool, but humans are still necessary. There's a lot that AI can do and it's pretty cool. Building Medivice made us realize that the future lies in continued collaboration between AI and humans.