AI-powered ordering to cut waste in fresh produce retail with Freshflow

Fresh produce ordering presents specific forecasting challenges, such as shelf lives measured in days, quality that varies by supplier and season, and demand that shifts within a single day. Most existing forecasting tools were built for shelf-stable goods and do not address these variables adequately, leaving many produce managers to order by intuition.

Freshflow (Germany, founded 2020) was co-founded by Carmine Paolino and Avik Mukhija, who developed the idea during a university placement on the shop floor of a supermarket, observing the manual, estimation-based processes behind daily fresh produce orders.

The platform uses probabilistic machine learning to generate daily ordering recommendations for fresh departments, ingesting over 350 signals including weather, promotions, store layout, spoilage rates, and local supplier variability. It integrates with existing retail IT systems and is operated via an in-store app designed for produce managers. The company reports average food waste reductions of over 20% and revenue increases of 2–5%, alongside a 93% order acceptance rate.

In May 2025, Freshflow raised €6.5 million, bringing total funding to €8.7 million. The round was led by World Fund, Capnamic, and Venture Stars, with participation from Caesar Ventures and Catatumbo Capital, all returning investors. The company plans to grow its team and expand into dairy, meat, bakery, and distribution centre ordering.

The revised EU Waste Framework Directive requires member states to achieve a 30% per capita reduction in food waste across retail, restaurants, and households by 2030 - placing direct measurement and reporting obligations on grocery operators for the first time.

Sources: Freshflow | World Fund | European Commission

Founders: Avik Mukhija, Carmine Paolino