Building bots from raw logs and computing coverage of business logic graph

Abstract

A method for dynamically generating training data for a model includes receiving a transcript corresponding to a conversation between a customer and an agent, the transcript comprising a customer input and an agent input. The method includes receiving a logic model including a plurality of responses, each response of the plurality of responses representing a potential reply to the customer input. The method further includes selecting, based on the agent input, a response from the plurality of responses of the logic model. The method includes determining that a similarity score between the selected response and the agent input satisfies a similarity threshold, and, based on determining that the similarity score between the selected response and the agent input satisfies the similarity threshold, training a machine learning model using the customer input and the selected response.