AI Insights for Crypto & Stocks

The system is designed to forecast future market prices by integrating a wide range of influential data sources into a deep learning pipeline. We aggregate and sync historical data across key economic and behavioral dimensions.

The multi-source data is normalized and used as time series input to train our Long Short-Term Memory (LSTM) model, a type of Recurrent Neural Network (RNN) designed for sequential data forecasting.

This architecture enables smarter trading decisions by combining traditional financial signals with behavioral and macro-level insights, pushing the boundary of what AI can do in predictive finance.