Deployment of ModelMe Innovation

Informacje na temat projektu

ModelMe

Identyfikator umowy o grant: 101114220

DOI

10.3030/101114220

Projekt został zamknięty

Data podpisania przez KE 1 Czerwca 2023

Data rozpoczęcia 1 Lipca 2023

Data zakończenia 31 Stycznia 2024

Finansowanie w ramach

• European innovation ecosystems

Koszt całkowity

Brak danych

Wkład UE

€ 75 000,00

Koordynowany przez

MODELME UG (HAFTUNGSBESCHRAENKT)
Germany

Periodic Reporting for period 1 - ModelMe (Deployment of ModelMe Innovation)

Okres sprawozdawczy: 2023-07-01 do 2024-01-31

Podsumowanie kontekstu i ogólnych celów projektu

ModelMe is a Deep Tech company working on building intuitive generative tools that help fashion companies to create on-model fashion imagery. The overall objective of the project was to bring ModelMe's algorithm and web-based product to market maturity. The milestones within the project cover the development, refinement, and successful deployment of our AI software product to meet the needs of ModelMe's target customers and prepare for commercial launch. Prior to the project, ModelMe had a promising algorithm that could generate images of photo-realistic fashion models, however the algorithm needed further iterations to meet the quality standards demanded by the industry. Additionally, ModelMe had not yet built a user interface where future clients could access the algorithm, this was covered in the project. The results of the project contributed to generating high quality images that could be accessed using a scalable web-based front end.

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

1. Innovation and Interface Design Validation
Detailed document noting the steps required to improve the usability of the software and the areas in which the technology can further provide value to our target customers.

2. Interface Design Iterations
Figma document outlining new design improvements in order to increase software ease of use.

3. Algorithmic Iterations
Iterating on the algorithm based on feedback in the Roadmap stage. Iterations may include increasing the scope of what the algorithm can do or increase the performance of tasks it can already do. Here we will create a table showing the capabilities of the technology at the validation phase and after the algorithmic iteration phase to communicate the changes made.

4. Business Model and Go to Market Revision
Document outlining the go to market strategy in order to reach and acquire customers.

5. Product Deployment
Public release of our web-based software where customers can use our proprietary algorithms.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

Further Research: Continuous innovation is needed to refine algorithmic control and reduce artifacts (errors), enhancing the quality and reliability of generated images.
Skilled Engineering Talent: Attracting and retaining highly skilled engineers (Computer Vision Experts and Scientists) is essential for ongoing technological advancements, necessitating adequate funding and support.
Market Awareness: Increasing marketing efforts and public awareness is key to accelerating the adoption of this disruptive technology, as it replaces traditional manual processes with more efficient, tech-driven solutions. As with all new innovation, there is initial hesitation and skepticism that delays adoption.