Abstract: A natural language workflow policy is generated for a workflow to solve customer support tickets is automatically generated from representative tickets. Tools, such as API calls, may also be automatically generated from representative tickets. In one implementation, a clustering technique may be used to identify representative answers for particular customer support topics. The generated workflows may be used by a large language model to generate answers for customer questions for an autonomous AI chatbot agent.

Abstract: An autonomous customer support Chatbot Agent utilizes a large language model to aid in implementing a workflow to solve a customer issue. A natural language workflow policy may be selected by an admin, along with tools such as API calls. The large language model determines the implementation details for the workflow based on the workflow policy and the selected tools.

Abstract: A system and method are disclosed for detecting the intent of a freeform customer support email question and performing a workflow to respond to the customer support email. In one implementation, a granular taxonomy of topics is generated and intent detection includes mapping a summary of the email to a topic in the taxonomy. An interactive workflow may be selected based on the topic of the email. The interactive workflow may include slot-filling using generative artificial intelligence. The interactive workflow may include API calls.

Abstract: A computer-implemented method is disclosed for using generative AI for customer support. An AI model may be fine-tuned on the task of generating a template workflow answer given a prompt of real answers. In some implementations, an AI empathy model is trained/fine-tuned to customize template answers to be more empathic. In some implementations, the template workflow answer may include an API call step.

Abstract: A computer-implemented method for augmenting customer support is disclosed in which a granular taxonomy is formed to classify tickets based on customer issue topic. A dashboard and user interface of performance metrics may be generated for the topics in the taxonomy. Recommendations may also be generated to aid servicing customer support issues for topics in the taxonomy. This may include generating information to aid in determining topics for generating automated responses or generating recommended answers for particular topics. In some implementations, an archive of historic tickets is used to generate training data for a machine learning model to classify tickets.