Abstract: Systems and methods for automated reasoning and explanation of correlated factors in digital experience monitoring include collecting performance data from a plurality of sources, the performance metrics including network metrics, application performance metrics, device metrics, and user behavior metrics; identifying one or more anomalies and correlations between the collected performance data; processing the one or more anomalies and correlations with a Large Language Model (LLM) to generate one or more explanations for the identified anomalies and correlations; and presenting the generated explanations through a user interface.

Abstract: Systems and methods for handling customer support tickets are provided. A method, according to one implementation, includes a step of dynamically summarizing ticket content of a new ticket to obtain partial summaries and a final summary of the new ticket, wherein the new ticket is opened in order to resolve an incident in a domain. The method also includes a step of transforming the final summary into a numerical vector. Also, the method includes performing a similarity search to compare the numerical vector with pre-stored vectors in a vector database, wherein the pre-stored vectors are associated with previously resolved incidents in the domain. The method may further include triggering predefined actions based on the similarity search.

Abstract: Systems and methods include monitoring user experience of one or more users accessing any of the Internet, cloud applications, and private applications; determining a user experience score for the one or more users; responsive to detecting a low user experience score for a user, performing one or more analyses on the user experience of the user; and determining a root cause of the low user experience score based on the one or more analyses. The systems and methods can include determining a remedial action for the user based on the root cause.

Abstract: Systems and methods include monitoring user experience of one or more users accessing any of the Internet, cloud applications, and private applications; determining a user experience score for the one or more users; responsive to detecting a low user experience score for a user, performing one or more analyses on the user experience of the user; and determining a root cause of the low user experience score based on the one or more analyses. The systems and methods can include determining a remedial action for the user based on the root cause.