Savvie – the first AI-powered app to reduce food waste in cafés

“When I realised that the annual emissions related to food waste are greater than the carbon footprint of India, I knew more had to be done in this space,” explains Li.

“My co-founder, Puteri Myrasandri, and I are big foodies. We’re passionate about reducing food waste and saw a particularly urgent need within the bakery and cafés segment. These businesses need to know exactly what they will sell days before the customer arrives in the store. But forecasting sales is difficult, so they consistently over-order to avoid being undersold. Yet day-old bread can rarely be sold, so all this ends up becoming food waste. In addition, the costs and labour that goes into producing this food also becomes waste,” she adds.

The Savvie digital assistant gives small bakery and café owners data-based guidance to make better business decisions. The app allows owners to monitor sales, register deliveries and track trends. They can also log waste, set budgets and see product-specific sales forecasts.

“Savvie uses machine learning algorithms to translate large amounts of data into helpful business insights. Showing owners how to reduce food waste is a key part of this,” says Li. The app integrates with a café’s point of sale (POS) and other systems. It also incorporates historical data specific to the shop. This gives owners real-time access to all kinds of useful information, especially when it comes to planning and forecasting.

Take cupcakes, for example. Owners can find out how many cupcakes they should order on any given day, how the weather, day of the week and holidays affect their cupcake sales, and whether their cupcakes are increasing or decreasing in demand.

All of this is made possible by the company’s custom-built algorithms.

“Savvie provides precise forecasts of specific product sales. We help owners to strike the perfect balance between selling out early and having lots of leftovers,” explains Li. “The app also forecasts sales revenues with 90 per cent accuracy,” she adds.

Users of Savvie report much less food waste and time spent on administrative tasks. The combination of less waste and greater efficiency yields higher profits.

“According to our numbers, Savvie reduces food waste by up to 75 per cent. It also increases profitability by an average of 20 per cent, at less than 2 per cent of the cost. We also help each store to reduce its carbon emissions by 3.6 metric tons a year,” says Li.

Moreover, Savvie empowers local food businesses to succeed in a market dominated by global chains.

There are some 344 000 cafés in Europe with total sales of EUR 47 billion. About 98 per cent of these are independent. Until now, no business tools have been tailored to meet their specific needs.

“Our customers are early-stage cafés and bakeries in a growth phase, anywhere in the world,” says Li.

Established in 2020, Savvie has 300 active users in Denmark, Indonesia and Norway, and seeks to expand worldwide. The company was named one of the top 25 machine learning start-ups by Forbes.

“We’re spending our time making the planet greener and helping to make people’s lives easier – that’s a really powerful ‘why’ for me,” concludes Li.