markdown
# AI Forge Technical Architecture

## Core Components

### 1. No-Code Studio
- **Drag-and-drop interface** for assembling AI pipelines
- **Template Marketplace**: Pre-built industry solutions (marketing/healthcare/e-commerce)
- **Visual Workflow Builder**: Node-based editing of data flows and model interactions

### 2. Model Types Supported
- **Text Generation**: GPT-4/Claude 2/Llama 2 fine-tuning
- **Image Generation**: Stable Diffusion/DALL·E pipelines
- **Predictive Models**: Scikit-learn/PyTorch/TensorFlow automl
- **Code Generation**: Fine-tuned Codex models

### 3. Backend Services
mermaid
graph TD
    A[Client] --> B[API Gateway]
    B --> C[Authentication]
    B --> D[Project Management]
    B --> E[Model Training]
    B --> F[Prediction Serving]
    C --> G[Auth0/Ory Hydra]
    D --> H[PostgreSQL]
    E --> I[Kubernetes Job Queue]
    F --> J[FastAPI Servers]
    I --> K[GPU Workers]
    J --> L[Redis Cache]


## Tech Stack

### Frontend
- **React** with TypeScript
- **Tailwind CSS** for styling
- **React Flow** for workflow visualization
- **Vanta.js** for interactive backgrounds

### Backend
- **Python** with FastAPI
- **Celery** for async task queue
- **Ray** for distributed training
- **PostgreSQL** for metadata
- **Redis** for caching

### AI/ML Infrastructure
- **Hugging Face Transformers**
- **ONNX Runtime** for optimized inference
- **MLflow** for experiment tracking
- **Seldon Core** for model serving

## Data Flow

1. **Ingestion**: CSV uploads, DB connectors (Postgres/MySQL), API integrations (Salesforce/Zapier)
2. **Preprocessing**: Auto-cleaning, anonymization (HIPAA/GDPR), feature engineering
3. **Training**: Distributed on Kubernetes with GPU/TPU support
4. **Serving**: REST/gRPC endpoints with auto-scaling
5. **Monitoring**: Drift detection, performance metrics

## Scalability Features
- **Autoscaling**: Kubernetes HPA for prediction servers
- **Spot Instances**: Cost-effective GPU training
- **Model Caching**: Frequently used models kept warm
- **Edge Deployment**: Export to ONNX/TensorRT

## Compliance
- **Data Encryption**: AES-256 at rest, TLS 1.3 in transit
- **Access Control**: RBAC with JWT claims
- **Audit Logs**: All actions recorded in SIEM
- **Compliance Certifications**: SOC2 Type II, HIPAA, GDPR

## Deployment Options
1. **Cloud**: AWS/GCP/Azure (1-click deployment)
2. **Hybrid**: On-prem GPU cluster + cloud management
3. **Edge**: Export as Docker container for local deployment

## Freelancer Features
- **Template Licensing**: Sell custom workflows in marketplace
- **White-labeling**: Rebrand models for client delivery
- **API Monetization**: Charge per prediction call
- **Collaboration**: Shared project spaces

</html>