JOG

Date de soumission 11 juillet 2023 Fondateurs Maya Hamadi Lieu de développement Paris, France, France

Le projet en détails

NB : cette fiche est intégralement remplie par les personnes proposant l’innovation.

Quel est le problème résolu ?

Traditional demand forecasting methods are inaccurate and time-consuming, restaurant managers spend hours poring over spreadsheets and manually adjusting their predictions. The food waste that results from this gut-instinct forecast represent 1.3B kg, 6% of global CO2 emissions (3x aviation)

Comment est-il résolu ?

A SaaS for restaurants that uses the power of AI and Machine Learning to analyze POS data and exogenous factors, creating precise forecasts for sales, demand, production, food orders quantities, and staff scheduling, reducing food waste and labor shortage

Qui sont les clients potentiels ?

Global Restaurant chains (fast food or full service chains) and Mass catering : $8B global market. The buyers and users are CEO, COO, owners, franchisee. Users are restaurant managers

En quoi cette solution est-elle différente ?

Forecast not as a feature but the heart of the business. Fully integrated, no switch costs. Created by restaurateurs, problem lived by the founder and shared by the clients. End-to-End Operational Optimization, impacting the waste and optimizing the labor