Machine learning-based evaluation of recorded interactions

A system, comprising:

• one or more processors configured to:
• obtain an evaluation plan to correspond to a new question, wherein to obtain the evaluation plan further comprises to:
• analyze the new question using a large language model (LLM) to determine key characteristics;
• compare the key characteristics against predefined criteria associated with a library of predetermined evaluation plans to determine a set of candidate evaluation plans;
• determine a set of accuracies corresponding to respective ones of the set of candidate evaluation plans;
• and
• select the evaluation plan from the set of candidate evaluation plans based at least in part on the set of accuracies;
• retrieve a representative interaction based at least in part on the new question;
• use 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;
• output, at a user interface, the new question and the preview evaluation result of the representative interaction;
• receive, via the user interface, user feedback to the preview evaluation result;
• and
• update the reasoning and answer language model based at least in part on the user feedback to the preview evaluation result;
• and
• a storage device configured to store a feedback data set including the user feedback.