sewts

sewts

Sewts develops an AI and robotics software to completely automated clothing production.

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DateInvestorsAmountRound
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investor investor investor investor investor

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round
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€7.0m

Series A
Total Funding000k

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EUR20212022
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More about sewts
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Sewts is a Munich-based startup that is revolutionizing the field of robotics by focusing on the automation of tasks involving easily deformable materials, such as textiles. The company leverages advanced machine learning and computer vision technologies to develop intelligent robotic systems that can handle materials traditionally considered too complex for automation.

Sewts' flagship product, the VELUM system, is designed specifically for the industrial laundry sector. This system automates the handling of laundry items, a task that has historically required significant manual labor due to the flexible and variable nature of textiles. By automating these processes, Sewts aims to increase efficiency, reduce labor costs, and improve overall productivity for its clients.

The primary market for Sewts is the industrial laundry industry, which includes large-scale laundry service providers and textile maintenance companies. These clients benefit from the company's innovative solutions that streamline operations and reduce the need for manual intervention.

Sewts operates on a business-to-business (B2B) model, generating revenue through the sale and implementation of its robotic systems. Additionally, the company may offer ongoing maintenance and support services, providing a recurring revenue stream.

The company's mission extends beyond just laundry automation. Sewts envisions its technology being applied to various other industries where the handling of flexible materials is a challenge, thereby opening up new markets and applications for its robotic solutions.

In summary, Sewts is at the forefront of integrating robotics into industrial applications, particularly in the textile and laundry sectors. By automating complex manual tasks, the company not only enhances operational efficiency but also contributes to broader sustainability goals by reducing the environmental impact of industrial processes.

Keywords: robotics, automation, textiles, industrial laundry, machine learning, computer vision, B2B, efficiency, sustainability, Munich.

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