Project cooperationUpdated on 17 September 2025
Circular Pet Apparel & Accessories Start Up using Textile Waste
About
Premium pet apparel and accessories brand made from post industrial and consumer textile waste. Sustainable production in Portugal, with EU-wide e-commerce direct-to-consumer and business to business distribution. Looking to create entire supply chain within a 30k radius in northern Portugal.
Strategic Highlights for Investors
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Circular Economy Model: Upcycled textile waste minimizes material cost and environmental impact.
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Also seeking Cradle to Cradle and Fair Trade certification.
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Portugal Advantage: Access to skilled textile labor, EU manufacturing proximity, and sustainable production hubs.
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Premium Pet Market: EU pet care market worth €25B+ and growing rapidly, especially in premium and eco-conscious niches.
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Scalable DTC and BTB Model: Low overhead, digital-first infrastructure allows for efficient customer acquisition and expansion.
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Strong Brand Positioning: High-quality, design-forward, sustainable products—an underserved segment in the pet space.
Stage
- Early idea
Topic
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Assistance and Expert systems
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
Type
- Consortium seeks Partners
- Expertise offered
Attached files
Organisation
Similar opportunities
Project cooperation
- Early idea
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | (AI based) process and system control technologies
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Donna Bowman-Coe
Founder/CEO at Por Amor Ao Ofício
Arcozelo VNG, Portugal
Project cooperation
- Early idea
- Expertise offered
- Consortium seeks Partners
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
Laura Bies
Lab Lead Smart Quality at August-Wilhelm Scheer Institut
Saarbrücken, Germany
Project cooperation
Digital ecosystem for circular value creation
- Already defined
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- Data technologies | Approaches to support SME fully exploit the value of existing CVC-related data
- Enabling technologies | (Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurement
- Data technologies | Interoperability of CVC-relevant data ecosystems, quality assurance and traceability across systems
- Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
- Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
- Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
Yoav Nahshon
Team Leader Materials Informatics at Fraunhofer IWM
Freiburg, Germany