🤖 ClinicFlow – AI-Powered Patient Intake System

ClinicFlow is an AI-powered patient intake and triage platform that automates clinic check-ins. Patients interact with a conversational chatbot built in React Native, data flows securely through a Node.js + MongoDB backend, and staff manage submissions in a React web dashboard.

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🚀 Live Deployment

Component	Description	Deployment	Status
Backend (API Server)	Node.js + Express + MongoDB REST API	Live API on Render	✅ Live
Dashboard (Web)	React dashboard for clinic staff	Live Dashboard on Vercel	✅ Live
Mobile App (Android)	React Native chatbot (Dialogflow CX)	Distributed via Firebase App Distribution (Private Tester Access – invite available on request)	🔒 Private

All three components are live and connected — the chatbot communicates with the production backend, and new check-ins instantly appear on the staff dashboard.

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✨ Features

• AI Chatbot (React Native): Uses Google Dialogflow CX to handle patient check-ins through a conversational flow.
• Backend (Node/Express/MongoDB): Handles API requests, stores intake data, and connects to Dialogflow.
• Dashboard (React): A web panel for staff to review patient intakes, mark them as complete, or filter based on status.
• Real-Time Data Flow: Chatbot → Backend → Dashboard (synced automatically).
• Modular Structure: Clear separation between backend, app, and dashboard for easy maintenance and scaling.

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🏗 Architecture Overview

🤖 Patient (Mobile)
↓
📱 React Native Chatbot (Dialogflow CX)
↓ API requests
🌐 Express Backend (Node.js + MongoDB Atlas)
↑ REST APIs / WebSocket sync
💻 React Dashboard (for Clinic Staff)

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🧰Tech Stack

Backend (clinicflow-backend)

• Node.js, Express
• MongoDB, Mongoose
• Dialogflow CX SDK (@google-cloud/dialogflow-cx)
• Morgan, UUID, dotenv

Mobile App (ClinicFlowApp)

• React Native
• Axios (with interceptors for API logging)
• Animated + KeyboardAvoidingView for smoother chat
• Tested on Android (emulator + real device)
• Released via Firebase App Distribution

Dashboard (clinicflow-dashboard)

• React (CRA)
• Axios
• React Testing Library + Jest
• Deployed via Vercel

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⚙️ Running Locally

1. Clone the repo

   git clone https://github.com/your-username/clinicflow.git
   cd clinicflow

2. Backend setup

   cd clinicflow-backend
   npm install

   Create .env:

   PORT=5000
   MONGO_URI=your_mongodb_connection_string
   GOOGLE_PROJECT_ID=your_dialogflow_project_id
   GOOGLE_CLIENT_EMAIL=your_service_account_email
   GOOGLE_PRIVATE_KEY="your_private_key"
   DIALOGFLOW_AGENT_ID=your_agent_id
   DIALOGFLOW_LOCATION=us-central1

   Start server:

   node server.js
   # http://localhost:5000

3. React Native App

   cd ../ClinicFlowApp
   npm install

   In one terminal, start Metro:

   npx react-native start --reset-cache

   In another terminal, run the app:

   npx react-native run-android

4. Dashboard

   cd ../clinicflow-dashboard
   npm install
   npm start
   # http://localhost:3000

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🗂 Folder Structure

clinicflow/
├── clinicflow-backend/ # Node.js + Express + MongoDB backend
├── ClinicFlowApp/ # React Native mobile chatbot app
└── clinicflow-dashboard/ # React dashboard for staff

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📜 License & Usage Notice

This project is licensed under a Proprietary License.
It is provided for production-ready demonstration purposes only.

See full LICENSE

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🔒 Environment & Security

ClinicFlow follows standard production security practices:

• Firebase, Google Cloud, and MongoDB credentials are securely managed via environment variables.
• Sensitive files like google-services.json are excluded from version control.
• API keys and private keys are never exposed in builds or repositories.
• The backend connects to Dialogflow CX using a service account with restricted access scope.

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👨‍💻 Author & Credits

Tanvik Reddy Kotha
Full-Stack Developer | AI & Cloud Enthusiast

Email ID: tanvikreddy123@gmail.com
🔗 LinkedIn · GitHub