The owner wanted to track the sales report of all the branches under a single platform.
Owner is unable to predict the forecast based on historical data patterns.
Solution
ML model trains on a continuous basis with the restaurant data collected. It helps predict customer traffic on week-days and week-ends.
Created an end-to-end solution, where users can login as per their respective roles. Users can login as owner, admin, cashier, manager, supplier, operations manager, chef, waiter, and driver.
Role-based access to various modules of the application.
Admin has control over adding and deleting identities (users).
The owner has separate super-admin access to track all the restaurant branches.
The order is taken by the cashier, which is passed onto the kitchen chef with all the details. Once the order is prepared, the waiter is notified to serve it to the respective table.
Sales and profit reports can be generated using the application. Graphical comparisons based on different timelines can be performed.
Under the inventory section, details about various ingredients can be found. Inventory management helps to supply the needed ingredients to the appropriate location on time using ‘Request’ and ‘Send’ functionalities.
Staff attendance sheets and HR management help in keeping an effective log of worker attendance and their working hours.
Solution is available in two languages: English and Arabic.
The solution supports both web and mobile interfaces.
Key Benefits
ML model made precise predictiones which eventually resulted in increased sales by 23% in just one quarter.
Better inventory management, with no last-minute rush for the necessary items.
Customer traffic predictions made by the model, helped the restaurant management to have enough staff to take care of customer needs.
Increased smoothness in the functioning of the restaurant.