Project description
AI’s green solution to clothing overproduction
In the glitzy world of fashion, the allure of trendy, affordable clothing has given rise to an environmental crisis. The fast fashion phenomenon, characterised by swift production cycles and mass consumption, has led to overproduction. Traditional methods, often analogue and non-data-driven, have resulted in shockingly low fit rates (just 15 %) and substantial unsold inventory. In this context, the EU-funded SAIZ project will harness the power of AI. Specifically, it will optimise product development for the target audiences, effectively curbing overproduction and its associated carbon footprint. By virtually fitting products to 2 million body types, this approach saves resources and offers an estimated reduction of 400 million tonnes of CO2 over the next 5 years.
Objective
SAIZ - AI for product development optimization in the fashion industry.
SAIZ enables fashion brands to optimize product development towards their own specific target groups, thereby minimizes the overproduction in the fashion industry.
Hugely analog and non-data-driven processes have caused extreme inaccuracy when producing fashion. An average fit rate (garment fits the target group) is estimated to be at 15%, sell-through rates (what gets sold during the season) is at 60-70%. Production of fashion items is water, energy and pollution intensive, but a large part of the produced garments are produced so poorly, that they never even make it to a customer.
SAIZ enables a fashion brand to fit their products to 2 Million bodies (of their target customers) virtually to prevent products going into mass-production that will not fit and will not be sold.
A huge monetary game changer for the industry, and a big relief for the planet. SAIZ estimates to be able to save 400Mio tonnes of CO2 with data-driven product development in the next 5 years.
Fields of science (EuroSciVoc)
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- natural sciences physical sciences astronomy planetary sciences planets
- natural sciences earth and related environmental sciences environmental sciences pollution
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.2 - European innovation ecosystems
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-CSA - HORIZON Coordination and Support Actions
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIE-2022-SCALEUP-02
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
10961 Berlin
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.