Detailed AI Schematic

Engine Architecture

In our AI engine schematic, we split the process into distinct stages that represent our comprehensive approach to AI-driven portfolio management. The process flows through data input and preparation, where we gather and clean vast amounts of financial data; feature engineering, where we transform raw data into meaningful indicators; models and initial predictions, which involve training and deploying various ML models; model aggregation, where we combine insights from multiple models; and finally, signal generation and portfolio construction for final predictions and actionable insights.