Technical Architecture

Microservices Architecture

• Each major feature (e.g., Telegram, X analysis, sentiment engine) runs as an isolated service
• Scalable deployment via containers for modular maintenance

Real-Time Data Pipeline

• WebSocket and REST hybrid model
• Redis caching for instant signal propagation
• Stream processing for high-volume social data

Machine Learning Infrastructure

• Pipelines for fine-tuning and deploying AI models
• Supports continual learning with updated social sentiment patterns

Scalable Database Design

• Optimized for time-series data from sentiment streams
• Sharding and indexing for high-throughput queries
• Analytics snapshots for low-latency UI rendering

API Layer

• RESTful endpoints with TypeScript interface safety
• Rate limiting and batching mechanisms for stability
• Secure authentication with OAuth and JWT

Security Framework

• AES-256 encryption for data-in-transit and at-rest
• Role-based access control and API token management
• Anomaly detection for API usage

Monitoring & Optimization

• Real-time error tracking and performance metrics
• Alerting system for downtime and data anomalies
• Continuous integration with staging preview and auto-scaling logic