Industry-leading demand forecasting
Applying cutting-edge AI research to fresh forecasting to accurately predict future sales for each product, at each store, on each day.
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An intelligent brain for item-level forecasting
Developed out of AI research, our proprietary algorithm takes a novel approach to deep learning that goes beyond traditional machine learning: it mimics the way that a human brain learns complex causal patterns at a very granular level.
Traditional ML models get easily overwhelmed by too much data, struggling to capture individual nuances and often confusing correlation for causation. Our model architecture allows us to process billions of data points and better identify the causal interactions between the data points.

More real world data = more accurate
Your stores’ demand changes based on what is happening in the real world: Is it raining? Is there a sports match near your store? Is graduation for your local school happening today?
We incorporate thousands of local data points that are specifically relevant to your stores into our algorithm.
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Examples of forecasting intelligence
Promotions Data
We incorporate how different promotion types affect sales differently: discounts, multi-unit (“2 for $10”), EDLP, and even social media promotions.
We capture halo & cannibalization effects of promotions to reflect true cross-product impacts.
We capture how sales go “back to normal” after a promotion ends.
Weather Data
We incorporate weather data for the square mile radius around each of your stores.
We look at 10+ variables to contextualize weather, including the difference between weather forecasts and actual weather.
We incorporate how snowfall in Texas is different from snowfall in Maine — and we look at proxy datasets (e.g. road closures) to capture extreme weather events.
Local Data
We incorporate different local school term dates and key events (e.g. prom, graduation) for the specific school district that each of your stores is in.
We use demographic data from each of your stores’ zip codes to capture demand drivers like SNAP EBT deposit schedules and cultural holidays.
We look at over 200 local variables to better understand how each of your customers shop.
We train a custom algorithm that is unique to your stores.
We work closely with you to add in any external variables to reflect the realities of your stores, not of an average grocery store.
Meet with our team
We know that every retailer is different and that each department has its own unique needs. Share with us your specific business needs, and we’ll build a solution that is perfect for you.