In the IML4E project we are developing a systematic approach to support the European industry in setting up flexible end-to-end solutions for MLOps. The IML4E OSS platform shows how to realize the basic MLOps activities based on existing OSS solutions. The IML4E Framework, on the other hand, supports end customers in adapting, evaluating and continuously improving this or similar platforms according to their own requirements. In addition, we are reaching out with solutions for data quality assurance and efficient data preparation as well as continuous testing and monitoring, which are important topics with a high market potential.
The IML4E Framework will directly address the specifics of AI and ML by providing automation and reusability in the data and the training pipeline and will support continuous quality monitoring for different types of machine learning. IML4E will design the IML4E Framework and its solutions in such a way that they
- integrate seamlessly with existing best practices in software engineering, data science, and ML,
- fit in industrial settings, i.e. by means of case studies that heavily rely on AI and ML from relevant European industrial domains like e-Health, industrial IoT, invoicing operations, building automation, and consulting business,
- are relevant European and international standardization bodies (e.g. DIN, ETSI, ISO) that deal with the standardization of methods dedicated to the development of AI and ML,
- support the European software development and data science industry with open-source tools and frameworks dedicated to the development of AI.