The first holistic restaurant forecasting tool to reduce food waste by predicting future demand
Prognolite GmbH is a Swiss SME that is using artificial intelligence to combat the €20 billion food waste crisis within the restaurant sector. Through Prognolite software, restaurants can reduce food waste by up to 50% by accurately predicting food demand. The software has already caught the eye of six renowned Swiss and German multi-unit restaurants (including an international chain), testing it in 12 of their restaurants, reporting reduced food costs by up to 6%, and staff costs by 5-15%.

10.5 million tonnes of edible food is wasted each year by EU restaurants, primarily due to the difficulty of estimating the exact food demand. This complexity of accurately forecasting sales is causing restaurants to (i) dispose to waste over 10% of the purchased food and (ii) reduce efficiency of staff planning, resulting in poor customer service and unnecessary high staff costs. Traditional methods of demand forecasting of manually analysing historical data are inaccurate, highly dependent on staff experience and time consuming. The few digital solutions that exist fail to, within one software, optimise the two cost centres (food and wages) that gobble 80% of restaurateurs’ costs and often unaffordable to many. Moreover, most of these solutions are designed by Point-of-Sale (POS) systems providers and are only compatible with their own POS who cannot scale in an EU and global market where there are numerous POS systems.

As such, we have a unique advantage within the burgeoning €2.64tn global restaurant/food service market that has >2.5mn restaurants (EU & US only). With a product that enables restaurants to save, within a month, up to 8x what they would have paid us and widest POS compatibility (>80% of EU & US), we seek to be the global leader in demand forecasting solutions for the restaurant sector. We have estimated that we will need an additional investment of €1.3 million to achieve that and bring our product to the market.