AI and machine learning for less overproduction and more sustainable consumption in the fashion industry - a deep learning approach to understand products and customers better.

Información del proyecto

SAIZ

Identificador del acuerdo de subvención: 101114114

DOI

10.3030/101114114

Proyecto cerrado

Fecha de la firma de la CE 23 Mayo 2023

Fecha de inicio 1 Junio 2023

Fecha de finalización 31 Mayo 2024

Financiado con arreglo a

• European innovation ecosystems

Coste total

Sin datos

Aportación de la UE

€ 75 000,00

Coordinado por

SAIZ GMBH
Germany

Periodic Reporting for period 1 - SAIZ (AI and machine learning for less overproduction and more sustainable consumption in the fashion industry - a deep learning approach to understand products and customers better.)

Período documentado: 2023-06-01 hasta 2024-05-31

Resumen del contexto y de los objetivos generales del proyecto

SAIZ is an Enterprise SaaS Startup. We are on a mission to revolutionize the fashion industry by solving the age-old challenge of size and fit. Returns related to sizing and fit pose significant financial, regulatory, and environmental challenges for fashion companies. In specific, returns cause considerable costs and lost sales and put fashion companies under enormous regulatory pressure due to their adverse environmental impact. Powered by advanced analytics and artificial intelligence, SAIZ provides accurate size recommendations and fit solutions, empowering brands to reduce returns, enhance customer satisfaction, and embrace sustainability.

Before initiating the project, SAIZ had already launched two MVPs – SAIZ Recommender and SAIZ Studio - in the market. SAIZ Recommender offers accurate size recommendations to online shoppers through advanced machine learning algorithms. SAIZ Studio gives apparel brands the opportunity to learn more about their customers, products, and the product performance and provides insights for product optimization.

One primary objective within the Horizon Europe Programme was to ensure product-readiness for mass scaling. Additionally, we aimed to expedite the scaling and go-to-market strategy of SAIZ, ensuring broader reach and impact. Thereby, our focus remains on continuously improving our offerings to deliver maximum value to both online shoppers and apparel brands.

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

We are very happy that we could promote the development of our company, products, and traction. This enables us to be a driver of innovation in Germany's fashion industry, take on new funding, and expand internationally.

On the technical side, we have prioritized initiatives to facilitate self-onboarding for customers, focusing on implementing essential elements such as automated testing protocols, scalable database management systems and a robust infrastructure tailored to machine learning and data storage. By strategically investing in these areas, we have strengthened our platform to seamlessly support client onboarding processes. These concerted efforts have not only improved our operational efficiency, but also enabled us to effectively serve a growing user base. A remarkable result is that we now serve 5 million users per month with our SAIZ Recommender, with a loading time of under 200ms, highlighting the great strides we have made in delivering an exceptional user experience.

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

We are dedicated to providing actionable and relevant insights to help our clients be resilient and innovative. In this process, we place a strong emphasis on customer centricity, product innovation, and operational excellence. Our visionary goal is to empower our clients to revolutionize their production processes, such that they can develop better-fitting products. By doing so, we address the root causes of sizing and fit-related issues, as well as prevent waste. This would mark a significant contribution to establishing new industry standards, aimed at reducing environmental footprints and enhancing operational efficiency.

To ensure the realization of this goal, key needs include substantial investments in research and development, securing necessary funding, and advocating for a supportive regulatory framework that incentivizes apparel brands to embrace data-driven approaches in product design and innovation.