Cresta Intelligence Inc.

Peter Elliot Schmidt-Nielsen

Tianlin Shi

Alexander Donald Roe

JungHa Lee

Navjot Matharu

Syed Zayd Enam

A conversation may be monitored in real time using a trained machine learning model. This real-time monitoring may detect attributes of a conversation, such as a conversation type, a state of a conversation, as well as other attributes that help specify a context of a conversation. Contextually appropriate behavioral targets may be provided by machine learning model to an agent participating in a conversation. In some embodiments, these 'behavioral targets' are identified by applying a set of rules to the contemporaneously identified conversation attributes. The behavioral targets may be defined in advance prior to the start of a conversation. In this way, the machine learning model may be trained to associate particular behavioral target(s) with one or more conversation attributes (or collections of attributes). This facilitates the real-time monitoring of a conversation and contemporaneous guidance of an agent with machine-identified behavioral targets.

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Menlo Park, CA, United States of America

Peter Elliot Schmidt-Nielsen