Abstract: Systems and methods for monitoring a quality of interactions include: receiving one or more quality metrics relating to one or more quality targets; determining, on a periodic basis, a current quality value for each of the one or more quality targets; calculating a deviation of the current quality value from a desired value of the quality target; weighting the one or more quality targets according to the calculated deviation; and determining a set of one or more interactions for review based on one or more quality metric deviations and the weighted quality targets.

Abstract: A computerized-method for reducing time of evaluation of an interaction by annotating a media-file of the interaction based on an evaluation-measurement. The computerized-method includes: (i) receiving a request from a user to playback the media-file of the interaction by operating a media-playback service of a recording-player web-application; (ii) configuring the media-playback service to: a. operate an interaction-insights module to generate point-in-time annotations of the media-file, based on parameters of the evaluation-measurement; and b. send the point-in-time annotations and a location of the media-file to the recording-player web-application; and (iii) configuring the recording-player web-application to playback the media-file and upon user-selection to present each point-in-time annotation of the one or more point-in-time annotations, via a UI that is associated to the recording-player web-application, on a timeline-bar as an annotation-marker.

Abstract: A computerized-method for calculating a score of an outbound-marketing interaction. The computerized-method includes: (i) retrieving a transcription of the outbound-marketing interaction; (ii) identifying a product that is being marketed in the outbound-marketing interaction by executing an Artificial Intelligence (AI) Large Language Model (LLM) with a check-product-prompt having the transcription embedded therein; (iii) constructing a prompt based on: (a) the identified product; (b) one or more features of the identified product; (c) the transcription; and (d) one or more questions. Each question is related to a section in one or more preconfigured-sections; (iv) executing the AI LLM with the constructed prompt to yield an answer and a question-score to each question of the one or more questions; (v) calculating the score of the outbound-marketing interaction based on the question-score of each question; and (vi) sending the score to one or more applications for follow-on actions based on the score.

Abstract: A system and method are provided to predict media playback requests of media files to decrease response times to the media playback requests. The system includes a processor and a computer readable medium operably coupled thereto, to perform predictive caching operations which include receiving metadata from an interaction stream after recording a media file of an interaction, determining contacts corresponding to users identified in the metadata that are recorded in the media file from the metadata, accessing an ML model for predictive caching of media files, determining, using the ML model and a plurality of model features for the ML model, a first prediction for a first playback of the media file, predicting the first playback of the media file by at least one of the contacts based on the first prediction, caching the media file in the data cache for a time period based on the predicting.

Abstract: Systems and methods for monitoring a quality of interactions include: receiving one or more quality metrics relating to one or more quality targets; determining, on a periodic basis, a current quality value for each of the one or more quality targets; calculating a deviation of the current quality value from a desired value of the quality target; weighting the one or more quality targets according to the calculated deviation; and determining a set of one or more interactions for review based on one or more quality metric deviations and the weighted quality targets.

Abstract: Embodiments of the invention are directed to a computer-implemented system and method of performing quality assurance. The method may include receiving, by a processor, a quality plan comprising an expected number of evaluation tasks, wherein each evaluation task is distributed to an evaluator of a plurality of evaluators to be completed. For each evaluator, the processor computes an expected number of evaluation tasks to be completed per period, wherein the expected number of evaluation tasks completed per period is based on the expected number of evaluation tasks averaged over a set time period. The processor receives, for each evaluator, a number of actual evaluation tasks completed during the set time period and reassigns one or more evaluation tasks from the evaluator if the actual evaluation tasks completed during the set time period for said evaluator does not meet a predetermined threshold.