BloodLink AI

🛠️ Built With

A mix of modern web technologies, cloud services, and AI/ML frameworks helped bring BloodLink AI to life:

👨‍💻 Languages

• Python – for AI/ML model development
• JavaScript – core language for frontend and backend
• HTML & CSS – for interface layout and design

🧠 AI / ML Frameworks

• Scikit-learn – machine learning models and clustering
• XGBoost – donor prediction model
• TensorFlow / Keras – time-series forecasting
• OpenAI GPT API – AI-powered chatbot (ThalaBot)

🌐 Frontend

• React.js – modern, responsive UI
• Tailwind CSS – utility-first CSS framework for styling
• Chart.js – visualizing donation patterns and trends

⚙️ Backend

• Node.js + Express – REST API and server logic
• Firebase Functions – for serverless logic
• Socket.IO – real-time communication (for blood request alerts)

☁️ Cloud & Hosting

• Firebase Hosting – fast, reliable frontend hosting
• Google Cloud Platform (GCP) – model hosting and data storage
• Netlify – alternative static hosting (for demo deployment)

🗄️ Database & Authentication

• Firebase Firestore – NoSQL cloud database
• Firebase Authentication – secure login system (donor/patient/doctor roles)

🗺️ APIs & Integrations

• Google Maps API – routing and geolocation
• e-RaktKosh API (planned integration) – for real blood bank data
• Blood Bridge (NGO network) – partner integration
• Twilio API / FCM – SMS and push notifications

💡 Built with scalability and real-world integration in mind, BloodLink AI is future-ready for impact.

Built With

• blood-bridge
• chart.js-backend:-node.js
• cloud
• css-ai-/-ml-frameworks:-scikit-learn
• e-raktkosh-api
• express.js
• firebase
• firebase-authentication-apis-&-integrations:-google-maps-api
• firebase-functions
• google-cloud-platform-(gcp)
• html
• javascript
• keras
• languages:-python
• netlify-database-&-authentication:-firebase-firestore
• openai-gpt-api-frontend:-react.js
• socket.io-cloud-&-hosting:-firebase-hosting
• tailwind-css
• tensorflow
• twilio
• xgboost