AIA MFlux - Scalable Machine Learning Platform

The main objective of AIA Science is to commercialize business oriented Artificial Intelligence solutions in reliable production environments, enabling businesses to become more efficient and enabling businesses to offer new and better services in the market. Today, there is no existing solution able to handle the massive amounts of data available in many operations in a easily digestible format by machine learning algorithms. Instead, the problem size has to be broken down in subsets, or simplified down to a manageable problem size. This is far from ideal when trying to solve complicated relational problems. One of our target sectors is the large-scale production industry (f.ex. oil, gas, and aluminum), and we are developing an analytics platform that provides the resources and tools necessary for massive-scale data collection, managed real-time operations, and analytics based on artificial intelligence. This will enable the industry sector companies to optimize their production and also prevent the occurrence of accidents with irreversible effect on the environment. The main objective of the SME Phase 2 proposal is to fully finance the development from TRL6 to TRL9 and to secure sufficient funding for the market introduction of AIA MFlux. The key areas to be addressed include: * Technical development - Necessary activities to complete development and optimization of the solution's different components to TRL9 * Commercial introduction - Introduction to first markets - Oil & Gas in the Nordics, Adjacent markets in the Nordics.