Deep learning (DL) approaches are utilized across three distinct contexts to showcase their applicability in commercial environments with restricted data for training. This study showcases the application of unsupervised DL with autoencoders that vary and illustrates how federated learning serves as a successful collaboration approach for machine learning (ML) that safeguards confidentiality of data. © 2024 Elsevier B.V., All rights reserved.