Project cooperationUpdated on 4 July 2025
AI-powered platform for take-back, refurbishment, branded resale
About
We are developing a digital platform that enables manufacturers and retailers to create profitable circular business models through take-back, refurbishment, and branded resale. The platform will leverage AI-based decision support, use data ecosystems with API integration, and enhance Digital Product Passports (DPP).
We are looking for partners with durable, high-quality products who want to pilot circular models to build customer loyalty, capture value from second-life markets, and reduce emissions. Ideally, partners have first experience with circularity or DPP and are open to international cooperation.
Industries: textiles, kids, electronics, furniture, and machinery
Stage
- Already defined
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) process and system control technologies
- Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
- Enabling technologies | Network design of reverse supply chains
Type
- Consortium seeks Partners
- Expertise offered
Attached files
Organisation
Similar opportunities
Project cooperation
Digital Product Passport for Circular Economy
- Already defined
- Expertise offered
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Data technologies | Design of an adaptable Digital Product Pass:
- Enabling technologies | (Advanced) Materials and additive manufacturing
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- 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 | 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.
- 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)
Ralph Weissnegger
Director Innovation & Funding at CISC Semiconductor GmbH
Klagenfurt, Austria
Project cooperation
- Already defined
- Consortium seeks Partners
- 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.
Karoline Borner
Project manager and researcher in information architecture and biochar at Offenburg University
Offenburg, Germany
Project cooperation
Reverse value chain for circular electronics management - supported by postal networks
- Early idea
- Already defined
- Consortium seeks Partners
- Enabling technologies | Network design of reverse supply chains
- 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
- Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- 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
Koeun Lee
Circular economy and value chains consultant at Universal Postal Union (UPU)
London, United Kingdom