Abstract: Various methods, apparatuses/systems, and media for automatic real-time identification of dissatisfaction data are disclosed. A receiver receives real-time stream of call transcript data generated during a call or a chat between a customer and an agent. A processor implements a machine learning model that includes predefined complaint data; applies the received call transcript data onto the machine learning model; compares, in response to applying, the call transcript data with predefined complaint data; generates a first similarity score, based on comparing, that identifies how similar the call transcript data is compared to the predefined complaint data; and automatically identifies the call transcript data as a first dissatisfaction data based on determining that the first similarity score is equal to or more than a predetermined threshold value.

Abstract: Systems and methods for locality testing federated microservice architectures are disclosed. In one embodiment, a computer-implemented method for testing federated architectures may include: (1) associating a microservice testing application program with a set of microservices to create a simulated federated microservice architecture environment; (2) detecting, by the microservice testing application program, relationships associated with the set of microservices generating; (3) generating, by the microservice testing application program, test cases for testing a target microservice in the set of microservices; and (4) evaluating, by the microservice testing application program, a performance of the target microservice in the simulated federated microservice architecture environment based on the test cases.

Abstract: Systems and methods for locality testing federated microservice architectures are disclosed. In one embodiment, a computer-implemented method for testing federated architectures may include: (1) associating a microservice testing application program with a set of microservices to create a simulated federated microservice architecture environment; (2) detecting, by the microservice testing application program, relationships associated with the set of microservices generating; (3) generating, by the microservice testing application program, test cases for testing a target microservice in the set of microservices; and (4) evaluating, by the microservice testing application program, a performance of the target microservice in the simulated federated microservice architecture environment based on the test cases.

Abstract: Various methods, apparatuses/systems, and media for automatic real-time identification of dissatisfaction data are disclosed. A receiver receives real-time stream of call transcript data generated during a call or a chat between a customer and an agent. A processor implements a machine learning model that includes predefined complaint data; applies the received call transcript data onto the machine learning model; compares, in response to applying, the call transcript data with predefined complaint data; generates a first similarity score, based on comparing, that identifies how similar the call transcript data is compared to the predefined complaint data; and automatically identifies the call transcript data as a first dissatisfaction data based on determining that the first similarity score is equal to or more than a predetermined threshold value.