Project cooperationUpdated on 15 May 2025
Looking for R&D Partners in AI-Driven Data Governance and Circular Ecosystems
About
At DIP Bilgisayar Yazılım Ticaret A.Ş., we are developing MetaWorks, a comprehensive data governance and analytics platform.
MetaWorks offers metadata management, data lineage, data quality scoring, masking, and GenAI-supported SQL generation – designed for enterprises aiming to manage data effectively and compliantly.
We are actively looking for project partners for Eureka, Horizon Europe, or other collaborative programs in areas such as:
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Circular data ecosystems and semantic interoperability
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AI-powered data preparation and impact analysis
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Data compliance automation and digital product passports
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Low-code platforms for data integration and transformation
We bring technical expertise and a robust platform to co-develop innovative solutions with shared value. Let's collaborate to unlock the future of smart and sustainable data ecosystems.
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
- 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
- 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 | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
Type
- Consortium seeks Partners
- Expertise offered
Organisation
Similar opportunities
Project cooperation
- Early idea
- 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
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- 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.
ocean_mint ocean foods
Founder/Director at Ocean Mint UK Limited
Essex, United Kingdom
Project cooperation
Al and Circular Economy in Coating and Insulation
- Consortium seeks Partners
- Data technologies | Assistance and Expert systems
- Enabling technologies | Network design of reverse supply chains
- Data technologies | (AI based) process and system control technologies
- Data technologies | (AI based) Material and Product Design, Decomposition and Separation
- 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 | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
- 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.
Kaan AKSOY
Advanced Technologies and Sustainability R&D Department at BETEK BOYA VE KİMYA SANAYİ A.Ş
İSTANBUL, Türkiye
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