Helping manufacturers make better product and supply chain decisions

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        #News(Startup) [ via IoTGroup ]


        Stuttgart-based Makersite has raised €18 million in a Series A funding round.The service offers supply chain digital twins for product sustainability, risk, and cost optimisation to brands on a global scale.

        The new capital is expected to continue supporting the company’s solutions as it further expands sales efforts.To date, Makersite has raised approximately €18.8 million.Makersite’s €18 million Series A round was led by Hitachi Ventures, the global venture capital arm of Hitachi, Ltd., and Translink Capital with KOMPAS and existing investor Planet A participating.

        According to Makersite, 100% of the world’s carbon emissions come from products, the way they are made, the things we need for using them, and their end of life.Still, less than 1% of all products have sustainability as a design parameter.By employing AI, data, and apps to drive sustainable product and supply chain decisions at scale, Makersite helps client including Microsoft, Lush, Vestas, Cummins, and Procter & Gamble to make better decisions about what to buy and from where.It’s AI maps a company’s lineup of products, suppliers, and manufacturing processes and then compares this against more than 140 material and supply chain databases.From here, precise digital twins of each product are generated, including how they are made, used, and disposed of.

        These models and integrated apps enable transparency and understanding of multiple factors, including environmental footprints and compliance risks, at a speed according to Makersite faster than any current approach.”We put decades of experience into solving a problem that has eluded the manufacturing industry until now,” says Makersite founder Neil D’Souza.“In an increasingly complex environment, how do you make better products faster?One of the answers we found is to simplify and decentralize decision-making by providing accurate, instantaneous, and actionable multi-criteria data on sustainability, cost, and risk implications of decisions.”


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