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.

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: An AI chatbot responds to the intent of a customer question by triggering an automatic workflow appropriate for the intention of the question. An information retrieval pipeline may be initiated to response to question corresponding to an information request. A Large Language Model may be initiated to generate a workflow to respond to other types of questions. The Large Language Model is provided with policies, tools and prompts to implement workflows. An evaluation engine evaluates factualness and helpfulness of responses to information questions and workflow intent accuracy and workflow appropriateness. Overall conversation resolution verification ay also be performed.

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 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.