# Data Processing & Prediction Logic

Datanaut’s backend processes involve a combination of real-time data aggregation and predictive modeling. The platform integrates live market feeds from multiple trusted sources to ensure accurate and up-to-date information. This data is filtered, normalized, and analyzed using machine learning algorithms, which are optimized to detect both micro and macro trends.

The prediction engine uses a blend of technical analysis models, such as moving averages, RSI, MACD, and Bollinger Bands, along with pattern recognition techniques to forecast short-term price actions. These predictions are not presented as rigid signals, but rather as probabilistic insights—helping users understand potential scenarios rather than blindly follow instructions. As more users interact with the platform, the AI adapts and learns from feedback, making the predictive output increasingly personalized and context-aware.
