Cura | Devpost

🩺 Project Story: Cura

About the Project

Cura is an AI-powered medical voice assistant designed to make healthcare more accessible and responsive. It listens to patient symptoms, provides personalized guidance, connects users to doctors, and schedules appointments — all through natural, human-like conversation.

We were inspired by how difficult it can be to access immediate medical advice, especially when clinics are overwhelmed or unavailable. Our goal was to create an intelligent assistant that supports both patients and healthcare professionals by automating symptom triage, appointment scheduling, and follow-up care.

Through building Cura, we learned how to integrate real-time voice AI, generative language models, and healthcare data systems into one cohesive workflow. We explored challenges in conversational design, natural language understanding, and securely managing patient interactions.

Cura’s architecture combines:

🎙️ LiveKit Agents — for real-time voice calls and natural dialogue
⚙️ FastAPI and MongoDB — for backend data storage and healthcare logic
🧠 Chroma — as a vector database for symptom similarity search and matching, which diagnose patient's issue and give advice based on healthcare service's internal data
📅 CreaoAI — for intelligent scheduling and calendar integration
💻 Creao (React web) and Swift (mobile) — for patient and provider dashboards
Gmail API for appointment booking confirmation *

Challenges Faced

Building Cura presented several key challenges:

Designing natural and empathetic voice conversations that adapt to user tone and intent
Managing speech latency for real-time responses
Algorithm to match the most similar symptoms from user's input. We separate each symptom from healthcare data and embed each of them to count the number of matching symptoms and get average cosine similarity that receives best result *
Structuring a scalable database that connects patients, clinicians, and appointment data
Integrating multiple APIs (LiveKit, Chroma, Gmail) into a seamless workflow
Ensuring that AI-generated responses remain medically cautious and privacy-aware

Despite these challenges, we successfully created a working prototype that listens to patients, identifies symptoms, connects them with doctors, and schedules appointments — all through an intelligent voice interface.

Built With

chromadb
creao
fastapi
livekit
mongodb
python
swift

Submitted to

Cal Hacks 12.0
- Winner Regeneron: Honorable Mention

Created by

I worked on the iOS app and branding

Sarah Akhtar
I worked on the backed, I built an API that utilized the technologies FastAPI and Mongodb to return user data for our user mobile app and frontend management dashboard. I also helped integrate the backend onto the frontend.

Charles Mendez
I built an AI agent using Livekit with their STT and TTS combined with OpenAI model, apply prompt engineering to make models understand clearly user requests, and built Chroma Cloud as a RAG pipeline for the agent to diagnose issue. I designed the algorithm to work with cosine similarity in Chroma that reduce the hallucination of the result sent to the agent. I also integrate mongodb as a core database to check available appointments.

Hong Doan
I created and developed the front-end with the help of Creao AI to create and build the landing page, sign-up page, dashboard, calendar, appointments, and patients list. My main attention was on the development of a clean and responsive interface that would be responsive to the backend API. The application of Creao AI allowed accelerating the design process and ensuring that all pages use the same visual style.

Brandon Hann

Updates

Sarah Akhtar started this project — Oct 26, 2025 12:25 PM EDT

Leave feedback in the comments!

Log in or sign up for Devpost to join the conversation.