Project cooperationUpdated on 11 July 2025
AI-Driven Circular Fashion Digital Paltform: MODA App
About
At ModaApp, we aim to build a new digital platform that matches people with similar body profiles using advanced AI-powered algorithms. This platform will enable users to sell, rent, or exchange clothes that genuinely fit—reducing returns and promoting a more personal, circular, and sustainable fashion experience.
Key Features
- Body-Based Matching Algorithm: Users are matched based on measurements to ensure fit, reducing return rates and waste.
- Reuse-First User Journey: All listings are second-hand. Reuse is the core model, not a side feature.
- Mobile-First, Consumer-Centric: Designed for intuitive reuse and traceability for everyday users.
- Optional DPP Data Integration: Ability to display DPP tags and metadata when available, creating digital transparency.
Stage
- Early idea
Topic
- Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
- Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
- Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
- Enabling technologies | Network design of reverse supply chains
Type
- Consortium seeks Partners
Attached files
Organisation
Similar opportunities
Project cooperation
Global Digital Product Passport Consortium
- Early idea
- Consortium seeks Partners
- Data technologies | Design of an adaptable Digital Product Pass:
- 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)
Andres Alcayaga
Independent Consultant & Researcher at Johannes Kepler University Linz
Dusseldorf, Germany
Project cooperation
- Early idea
- Already defined
- Consortium seeks Partners
- Enabling technologies | Robotic / handling - and assistance systems
- Enabling technologies | (Advanced) Materials and additive manufacturing
- 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
- 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
Athina Kotrozou
Student
Stuttgart, Germany
Project cooperation
- Early idea
- 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
- 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
Rebecca Pahmeyer
Research Scientist at Fraunhofer IPA
Stuttgart, Germany