AI-powered forecasting that helps local retailers stock smarter, not harder
Try ForecastingUpload historical sales data and get accurate demand forecasts in minutes.
We learn from your patterns and tailor predictions to your store.
Optimize inventory levels and avoid overstocking or shortages.
Upload a CSV file with two columns: date and sales.
When you upload your sales data, each number in the forecast represents the expected units you might sell on a future day. For example, if the forecast shows Day 1: 52, that means the model predicts that you may sell around 52 units on the next day based on your past sales patterns.
These predictions help you understand demand so you can stock the right amount of inventory. If demand looks high, you can order more. If it looks low, you can avoid over-ordering. Using forecasts helps reduce waste, prevent lost sales, and make smarter purchasing decisions.
The forecast you see above is generated using a simple moving average model. It looks at your most recent sales history and calculates the average of the last few days to predict what future demand may look like. This approach works well for steady retail patterns and gives you a quick snapshot of what to expect.
To get the best results, upload a clean CSV file with two columns labeled date and sales. Each row should represent one day of sales for a single product or category. The more consistent and complete your data is, the more accurate your forecast will be.