Churn Prediction
Price Prediction
Conversion Prediction
Data Pipeline & Model Training
Agentic Coding Coaching
Large Language Models
Accurately forecast demand for improved planning
Most mid-size companies plan inventory and purchasing based on spreadsheets, last year's numbers, or instinct. That leads to overstock, stockouts, and missed revenue — problems that compound as you grow.
We build forecasting models from your historical sales, inventory, and seasonal data. You get a working model that predicts what will sell, when, and in what quantity, so you can plan purchasing, staffing, and inventory with real numbers instead of gut feel.
Inventory distortion, the combined cost of stockouts and overstock, represents 6.5% of total sales revenue. IHL Group.
A model that turns your sales history into a reliable view of what comes next
Three places this changes your business
Accurate demand forecasts change when you buy and how much you commit to. If you can see a spike coming six weeks out, you order before the price rises and before stock runs short. If demand is soft, you wait.
A kitchen equipment wholesaler forecasts demand per SKU 8 weeks out, reducing emergency reorders by 60% in the first quarter after deploying the model.
Overstock ties up cash. Stockouts cost sales. A forecast-driven replenishment model finds the right level between them, adjusted for lead times, storage costs, and seasonal patterns specific to your business.
A health supplements brand cuts warehouse holding costs by a third after switching from gut-feel to model-driven inventory targets.
Promotions create demand. The question is how much, for which products, and how long the tail lasts. A model trained on your past campaigns tells you what to expect and what to prepare for.
A fashion retailer uses demand forecasts to size inventory ahead of seasonal campaigns, avoiding the stockouts that previously cut promotions short.