Predictive analytics and ML

Choose the decision to improve

We build models for demand and sales forecasts, customer churn risk, price forecasting and anomaly detection. We start with a decision, such as replenishing stock or reviewing an unusual transaction, and agree on how forecasts or scores will support it.

Check what the data can support

We review historical coverage, missing values, seasonality and recorded outcomes. Evaluation uses information that would have been available when each prediction was made. We compare results with your current method and examine errors across relevant products, periods or customer groups.

Put predictions into use

Models can run in an approved cloud, private cloud or on your own infrastructure. We connect outputs to planning tools, dashboards or review queues. After launch, monitoring tracks changes in data and prediction quality so the team can decide when to investigate or retrain.