Deployment of ModelMe Innovation

Project Information

ModelMe

Grant agreement ID: 101114220

DOI

10.3030/101114220

Project closed

EC signature date 1 June 2023

Start date 1 July 2023

End date 31 January 2024

Funded under

• European innovation ecosystems

Total cost

No data

EU contribution

€ 75 000,00

Coordinated by

MODELME UG (HAFTUNGSBESCHRAENKT)
Germany

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

Reporting period: 2023-07-01 to 2024-01-31

Summary of the context and overall objectives of the project

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.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

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.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

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.