Meet the 3.0 Finalists: Jabu (France)

In collective catering, restaurants must plan weeks in advance. Menu items are fixed; orders are placed early and purchasing decisions are locked in. But this planning is often miscalculated by 15 to 20 percent, and that gap leads directly to overproduction and food waste. 

In France alone, nearly 200,000 tons of food are wasted each year in collective catering due to overproduction. That represents more than one billion euros in losses. This is not a marginal issue. It is a systemic one, driven by a lack of reliable anticipation. 

Jabu was created to solve this problem. Jabu is an AI that predicts guest attendance and food selection weeks in advance. This allows chefs to focus on what they do best: cooking the right amount of food, at the right time. 

To make this possible, we work with data that already exists. On the kitchen side, we use for example menus and historical attendance. We then enrich this with external signals such as weather forecasts and nearby events. From there, our AI identifies clear, recurring patterns and turns them into forecasts that chefs can trust and act on. Where planning was once based on instinct, Jabu now delivers up to 95 percent accuracy. 

That level of precision changes outcomes immediately. Our clients cut food waste by up to 50 percent and recover between 5 and 10 percent of revenue that would otherwise be lost. The benefits are felt quickly, both financially and in reduced environmental impact. 

This work is deeply personal to me. While working with large food service providers, I saw how much food was wasted simply because demand could not be anticipated with confidence. Later, during my time with the UN World Food Program, I realized this was not a local or regional issue. Food waste exists alongside food insecurity across the Global South, Asia, the United States and beyond. That imbalance is global, and it demands practical solutions that can be deployed now. 

Initially, we tried to collect data directly from guests through an application. But we quickly learned that this required too much commitment. When we sat down with more than 150 chefs, we realized something important. The data we needed already existed on their computers. So instead of asking for more input, we focused on using what was already there and building an AI around it. That is how Jabu was born. 

Jabu is a SaaS solution. It is easy to deploy, requires no installation and works wherever there is a stable internet connection and a food waste issue to solve. We are already operating in France and are ready to scale internationally, including in the UAE and other tech-ready markets. 

In the UAE, food waste is growing alongside population growth and tourism. Initiatives such as ne’ma are pushing strongly to reduce waste, and we want to contribute. By working with public institutions, hospitals, schools, and the hospitality sector, we believe data-driven anticipation can play a meaningful role in reducing waste at scale. 

Food waste is a massive challenge, but it is also one we can act on now. With the right data and the right tools, kitchens can waste less, save more, and focus on delivering good food to the people they serve. 

Kenny Laport

Co-founder of Jabu