Abstract: The present disclosure describes an artificial intelligence (AI)/machine learning (ML) based distributed, hybrid, and multi-cloud software fabric-based system that unifies the communication infrastructure across hybrid and multi clouds. This mobile connectivity software fabric allows operators to modernize their networks to bring significant operational savings while rolling out new mobile services. This fabric can enable small independent networks and allow them to seamlessly connect with public networks, and it can enable network of networks while keeping the underlying compute and heterogeneity unified.

Abstract: A system and method for dynamically creating distributed, self-adjusting and optimizing core network with machine learning is disclosed. The method includes receiving a request to access one or more services and establishing a secure real time communication session with one or more client devices and a set of service layers based on the received request. The method further includes determining one or more service parameters based on the received request and sending one or more handshake messages to each of the set of service layers. Further, the method includes determining one or more environmental parameters and determining best possible service layer capable of processing the received request by using a trained service based ML model. The method includes processing the request at the determined best possible service layer and terminating or transferring the secure real time communication session after the request is processed.