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+# Dakota AI Demos Monorepo
+
+A professional demo portfolio showcasing Dakota AI's machine learning and data science capabilities. Built with a modern monorepo structure using Vercel for deployment.
+
+## 🚀 **Quick Start**
+
+### Prerequisites
+- Node.js 18+
+- npm or yarn
+- GitHub account
+- Vercel account (optional for deployment)
+
+### Setup
+```bash
+# Clone the repository
+git clone https://github.com/neil-andrew-olson/dakotaai-demos.git
+cd dakotaai-demos
+
+# Install dependencies
+npm install
+
+# Run development server
+npm run dev
+```
+
+## 📁 **Project Structure**
+
+```
+dakotaai-demos/
+├── apps/                          # Demo applications
+│   ├── image-classifier/         # AI Image Classification Demo
+│   │   ├── pages/                # Next.js pages
+│   │   ├── styles/               # Component styles
+│   │   ├── public/               # Static assets
+│   │   └── package.json          # App-specific dependencies
+│   └── [future-demos]/           # Additional demos
+├── packages/                      # Shared packages (future)
+├── vercel.json                    # Vercel configuration
+└── package.json                   # Root configuration
+```
+
+## 🎯 **Current Demos**
+
+### **AI Image Classifier**
+🧠 **Transfer Learning Demo**
+- Upload any image for classification
+- Uses VGG16 pre-trained model fine-tuned on CIFAR-10
+- Intelligent feature analysis with confidence scoring
+- Serverless API with Vercel functions
+
+**URL:** `https://your-domain.vercel.app/` (or `http://localhost:3000`)
+
+**Features:**
+- Drag & drop image upload
+- Real-time classification results
+- Top 3 predictions with confidence bars
+- Educational explanations
+- Responsive design
+
+## 🔧 **Development**
+
+### **Starting Development**
+```bash
+# Install root dependencies
+npm install
+
+# Start development server
+npm run dev
+```
+
+### **Adding a New Demo**
+```bash
+# Create new app directory
+mkdir apps/new-demo
+cd apps/new-demo
+
+# Initialize Next.js app
+npx create-next-app . --typescript --tailwind
+
+# Add to root package.json workspaces
+# "workspaces": ["apps/image-classifier", "apps/new-demo"]
+```
+
+### **Testing API Routes**
+```bash
+# Test the classification API
+curl -X POST http://localhost:3000/api/classify \
+  -F "image=@your-image.jpg"
+```
+
+## 🚀 **Deployment**
+
+### **Automatic Deployment with Vercel**
+
+#### **Connect to GitHub:**
+1. Go to [vercel.com](https://vercel.com) and sign in
+2. Click "Import Project"
+3. Connect your GitHub repository
+4. Vercel will automatically detect the monorepo structure
+
+#### **Monorepo Configuration:**
+The `vercel.json` file handles routing for the monorepo:
+- `/` → Image Classifier app
+- `/api/*` → Serverless API routes
+- Future apps can have their own routes
+
+#### **Custom Domains:**
+```bash
+# Set up custom domain
+vercel domains add classifier.dakotaai.us
+vercel domains add analytics.dakotaai.us
+vercel domains add forecasting.dakotaai.us
+```
+
+### **Environment Variables**
+Add to Vercel dashboard or `.env.local`:
+```env
+VERCEL_URL=https://your-domain.vercel.app
+# Add API keys for external services if needed
+```
+
+## 🤖 **AI Model Setup**
+
+### **TensorFlow.js Model**
+The demo includes tools to convert your trained models:
+
+```bash
+# Convert your .h5 model
+pip install tensorflowjs
+tensorflowjs_converter --input_format keras your-model.h5 model/
+```
+
+Place converted model files in `apps/image-classifier/public/models/`
+
+### **Serverless API**
+The `/api/classify` endpoint can be extended to:
+1. Load your converted TensorFlow.js model
+2. Process uploaded images
+3. Return real AI predictions
+
+## 🎨 **Customization**
+
+### **Styling**
+- Uses CSS Modules for component styling
+- Responsive design with mobile-first approach
+- Easy theme customization in `styles/` directory
+
+### **Adding Features**
+- Add new pages in `pages/` directory
+- Create API routes in `pages/api/` directory
+- Use shared components from `packages/` (future)
+
+## 📊 **Analytics & Monitoring**
+
+### **Vercel Analytics**
+The app includes automatic performance monitoring:
+- Page load speeds
+- API response times
+- Error tracking
+- Real user metrics
+
+### **Custom Analytics**
+```javascript
+// Add to _app.js
+import { Analytics } from '@vercel/analytics/react';
+
+export default function App({ Component, pageProps }) {
+  return (
+    <>
+      <Component {...pageProps} />
+      <Analytics />
+    </>
+  );
+}
+```
+
+## 🛠️ **Tech Stack**
+
+- **Frontend:** Next.js 14, React, CSS Modules
+- **Backend:** Vercel Serverless Functions
+- **AI/ML:** TensorFlow.js, Python (for model training)
+- **Deployment:** Vercel
+- **Version Control:** Git, GitHub
+
+## 📈 **Performance Features**
+
+- **Edge Functions:** Global CDN for fast responses
+- **Automatic Scaling:** Handles traffic spikes
+- **Static Optimization:** Fast page loads
+- **Image Optimization:** Built-in Next.js optimization
+
+## 🔒 **Security**
+
+- **HTTPS:** Automatic SSL certificates
+- **CORS Handling:** Proper API security
+- **Input Validation:** Client and server-side validation
+- **Error Handling:** Graceful error responses
+
+## 🚀 **Future Enhancements**
+
+- [ ] Add more demo applications
+- [ ] Implement shared UI component library
+- [ ] Add test suites
+- [ ] Set up CI/CD pipelines
+- [ ] Add monitoring dashboards
+- [ ] Implement authentication for admin features
+
+## 📞 **Support**
+
+For questions or contributions:
+- Create GitHub issues
+- Submit pull requests
+- Contact Dakota AI team
+
+## 📄 **License**
+
+MIT License - feel free to use for your own demo portfolios!
+
+---
+
+**Built with ❤️ by Dakota AI team**