A data-centric network and non-Real-Time (RT) RAN Intelligence Controller (RIC) architecture are described. The data-centric network architecture provides data plane functions (DPFs) that serve as a shared database for control functions, user functions and management functions for data plane resources in a network. The DPFs interact with control plane functions, user plane functions, management plane functions, compute plane functions, network exposure functions, and application functions of the NR network via a service interface. The non-RT RIC provides functions via rApps, manages the rApps, performs conflict mitigation and security functions, monitors machine learning (ML) performance, provides a ML model catalog that contains ML model information, provides interface terminations and stores ML data and Near-RT RIC related information in a database. An ML training host trains and evaluates ML models in the catalog, obtains training and testing data from the database, and retrains and updates the ML models.