The Research to Business project explores commercialization pathways and prerequisites for a completely novel white-box AI solution that offers a transparent and human-understandable alternative to traditional black-box approaches in data analytics. The classifiers produced by the solution can be expressed as short, plain-language conditions, making their internal logic easy to understand and communicate. The white-box approach directly addresses explainability requirements arising from various regulations and legislation. While meeting these requirements is extremely challenging with black-box models, it becomes straightforward with white-box models. In addition, white-box models offer clear, broadly beneficial properties due to their interpretability and transparency.
During the project, the commercialization potential and benefits of the white-box solution will be validated in collaboration with data analytics companies and end-user organizations. This validation will help identify the most suitable go-to-market strategy and productization path for the solution. The project team consists of both commercialization professionals and experts in AI and software development with strong scientific backgrounds. The team is supported by an advisory board with experience in data analytics and business development. The goal is to bring to market a solution that combines scientific excellence with practical applicability and meets both market needs and regulatory demands.
