Turning historical data into automated decision-making engines.
Predicting demand, revenue, and resource needs using ensemble methods and transformer-based forecasting models for high-accuracy temporal predictions.
Predicting churn, customer lifetime value (LTV), and propensity to buy to help businesses proactively manage retention and lead scoring.
Automating data extraction from unstructured business documents (bank statements, reports, tickets) to reduce manual processing overhead.