Abstract: Machine learning-based evaluation of recorded interactions is disclosed, including: obtaining an evaluation plan to correspond to a new question; retrieving a representative interaction based at least in part on the new question; using a reasoning and answer language model to evaluate the representative interaction against the new question based at least in part on the evaluation plan and to provide a preview evaluation result; outputting, at a user interface, the new question and the preview evaluation result of the representative interaction; receiving, via the user interface, user feedback to the preview evaluation result; updating the reasoning and answer language model based at least in part on the user feedback to the preview evaluation result; and storing a feedback data set including the user feedback.

Abstract: Machine learning-based evaluation of recorded interactions is disclosed, including: obtaining an evaluation plan to correspond to a new question; retrieving a representative interaction based at least in part on the new question; using a reasoning and answer language model to evaluate the representative interaction against the new question based at least in part on the evaluation plan and to provide a preview evaluation result; outputting, at a user interface, the new question and the preview evaluation result of the representative interaction; receiving, via the user interface, user feedback to the preview evaluation result; updating the reasoning and answer language model based at least in part on the user feedback to the preview evaluation result; and storing a feedback data set including the user feedback.

Abstract: Analysis is performed on a collection of data that is recorded for the storage system during a first time frame. The recorded collection of data includes a plurality of performance parameters that are determined from, for example, diagnostic tools that continually operate on the storage system. A set of baseline values are determined for each of the plurality of performance parameters by analyzing the recorded collection of data from an older portion of the time frame. For each parameter, a set of performance parameter values obtained from a recent portion of the time frame is compared to a corresponding baseline value of that performance parameter. From performing the comparison, one or more anomalies that are indicative of a particular problem on the storage system are determined for one or more of the plurality of performance parameters.