ExpertAI-Lux (EAI) helps its customers in designing, implementing, and deploying Machine Learning and Artificial Intelligence project. Its team engages in all stages of the customer’s project from data collection and consolidation to the selection of most effective machine learning model for the problem at hand. EAI applies proven methodologies for mining large datasets such as CRISP-DM and KDD. Moreover, it makes use of state of the art technologies and tools for machine learning and deep learning, including advanced tools like Automatic Machine Learning (AutoML) for selecting the best neural network architecture and Explainable Artificial Intelligence (XAI) for producing transparent AI solutions that suit best the customer’s business needs. When needed, its technical experts are able to combine AI solutions with other leading edge technologies such as cloud computing, BigData, distributed ledger technoloiges, and the Internet of Things. EAI makes use of state-of-the-art technologies and tools for machine learning and deep learning.

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The company also supports organizations in ensuring the compliance of their AI processes to mandatory regulations. Its team includes experts in the legal and regulatory issues of AI, including issues associated with transparency, trustworthiness, and ethics. ExpertAI supports organizations in ensuring the compliance of their AI processes to mandatory regulations (e.g., GDPR, the emerging European AI Act and AI Liability Directive), while at the same time providing solutions for ethical, responsible, and transparent AI. The team includes consultants with proven experience in the ethical, legal and policy implication of BigData, AI and related technologies (e.g., cloud computing, internet of things, blockchain).

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EAI contributes in AI REDGIO 5.0 in two directions: i) ethical analysis and regulatory compliance of AIREDGIO 5.0 developments, with emphasis on AI Ethics, to ensure that the AI systems of the project are design and developed in-line with regulatory mandates and the principles of the Ethics Guidelines for Trustworthy AI and the AI Act, and  ii)  development of edge AI systems, notably edge ML systems such as embedded machine learning.