PACE · Packaging with AI for Circular Economy - strengthening Digimind's market position

Packaging is the biggest contributors to the global waste problem because it is not designed for circularity. Given the changes in the legislations and the increasing customer awareness the packaging industry is under pressure to solve this problem at the design phase of their products. One of the main difficulties is to manage the trade-off of cost, performance and sustainability criteria, which leads to package performance uncertainties. In this context, Digimind was created with the mission of accelerating the transition to circularity by dePackaging waste is one of the biggest contributors to the global waste problem, especially plastic packaging accounts for almost half the global plastic waste. Packaging design is driven mainly by marketing requirements, not incorporating any circularity, such as recyclability or reusability. With nowadays pressure due to limited material resources as well as the need to reduce CO2 emissions, circularity in packaging design becomes the new key driver. For the packaging industry this poses immense challenges to manage the new complexity of the trade-off of cost, performance and sustainability criteria. Digimind is developing an innovative software solution specifically for the packaging industry to tackle these challenges using digitalization and artificial intelligence.PACE objective is to strengthen Digimind’s position to successfully raise funding for the next phase of growth. The workplan to achieve this goal is twofold: Setting up a technical use case with a glass packaging proving Digimind’s technology on a second material as well as improving our business plan and pitch deck. This consolidation of Digimind’s position in the market will allow me to raise money to lead the company to its next steps in delivering its unique value proposition. This will create a strong example of a female co-founded deep tech company successfully build within Europe with a strong vision of solving our waste problem using digitalization.