Abstract: A method and system for using machine learning techniques and artificial intelligence algorithms for evaluating quality levels of client services and interactions are provided. The method includes receiving an email communication from a user; parsing the email communication to determine component portions of the email communication; analyzing respective qualities of each component portion; assigning a respective numerical score to each component portion based on the analysis; and generating a graph that depicts a quality level of the email communication based on the assigned scores. The component portions may include clarity, empathy, response, resolution, opening, sentiment, tone, grammar, closing, and/or signature. The analysis may be performed by executing one or more AI algorithms that implement a Natural Language Processing (NLP) technique and/or a Deep Neural Network (DNN) technique.

Abstract: A system and method for performing a projected graph based prediction is provided. The method includes obtaining data from a plurality of servers, determining data entities and dataflows between the data entities based on the obtained data, and generating a first graph including the data entities as nodes and the dataflows between the nodes. The method further includes identifying data concepts based on the obtained data and modifying the first graph by inserting the identified data concepts to provide a second graph. The second graph is further projected to generate a sub-graph, which is then utilized for a prediction algorithm to determine a predicted dataflow between at least two nodes connected to a data concept in the sub-graph.