Technologies for Dynamically Generating Personalized Support Recommendations During a Live Call
AssigneeThe PNC Financial Services Group, Inc.
InventorTouseef Habib
Life of this patent
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Abstract
Technologies for dynamically generating personalized support recommendations during a live call include a compute device. The compute device includes circuitry configured to receive, through a real-time communication channel, a call in which a customer poses a question to a live agent. The question is provided in real-time to a retrieval augmented generation artificial intelligence system (“RAG system”). The RAG system retrieves relevant context from a knowledge base related to the question and generates a predicted recommendation. The predicted recommendation is provided to the live agent during the call.
Claims20
A compute device comprising:
- circuitry configured to:
- receive, through a real-time communication channel, a call in which a customer poses a question to a live agent;
- provide the question in real-time to a retrieval augmented generation artificial intelligence system (“RAG system”);
- retrieve, with the RAG system, relevant context from a knowledge base related to the question;
- generate, by the RAG system, a predicted recommendation in response to the question based on the relevant context from the knowledge base;
- and
- provide, by the RAG system, the predicted recommendation to the live agent.
A method comprising:
- receiving, with a compute device, a call in which a customer poses a question to a live agent;
- providing, with a compute device, the question in real-time to a retrieval augmented generation artificial intelligence system (“RAG system”) by providing one or more of (i) a live audio stream, (ii) an audio clip, and/or (iii) a live multimedia stream of the call from the customer to the RAG system;
- retrieving, with the RAG system, relevant context from a knowledge base related to the question;
- determining whether there is sufficient relevant context for the RAG system to directly answer the customer’s question,
- in response to determining there is sufficient context for the RAG system to directly answer the customer’s question, providing a predicted recommendation generated by the RAG system directly to the customer using one or more large language models (LLMs) without any further involvement by the live agent;
- and
- in response to determining there is insufficient context for the RAG system to directly answer the customer’s question, providing the predicted recommendation to the live agent.
Dependencies are inferred from the claim text.