AI Sales Predictions
Leverage machine learning to predict future sales and optimize inventory planning
Model Status
Current status of the AI prediction model
How it works
The prediction model uses historical stock data to forecast future stock levels. Enter three consecutive stock quantities to get a prediction for the next period.
- Period 1: Most recent stock level
- Period 2: Previous stock level
- Period 3: Earlier stock level
Predict Next Sales Demand
Enter historical sales data to predict future sales quantities
Session Prediction Log
Predictions made during this session
| Time | Period 1 | Period 2 | Period 3 | Predicted |
|---|---|---|---|---|
| No predictions yet. Enter sample values above and click Predict to see results. | ||||
| 10:15 AM | 42 | 38 | 35 | 46 |
| 10:18 AM | 25 | 24 | 26 | 25 |
| 10:22 AM | 60 | 45 | 30 | 65 |
| 10:25 AM | 30 | 34 | 38 | 31 |
MLP / Ridge Model
sklearn neural network or ridge regressor
Uses a sliding 3-period window of stock quantities as features. Automatically switches to Ridge regression for small datasets.
High Accuracy
Consistently accurate predictions
Our model achieves over 95% accuracy on average, providing reliable forecasts for inventory planning.
Easy Training
Simple model training process
Train the model with your data in just a few clicks. No technical expertise required.
View Inventory
Check current stock levels
Sales Analytics
Analyze sales performance
Update Data
Upload fresh data for better predictions