This invention describes a system that intelligently routes customer interactions, like calls or messages, to the most suitable agent in a contact center. When a customer initiates contact, the system first determines their intent and then accesses their historical data, including past interactions across various companies. Based on this information, it generates a personalized profile outlining the ideal characteristics for an agent to handle that specific interaction, which is then used by a routing engine to find the best match. The claims narrow this to an intermediary platform that operates separately and can gather customer interaction data from multiple contact centers.
Why it matters: Filed before widespread adoption of advanced AI for intent recognition and preference inference. Large Language Models can now analyze interaction data to determine intent and infer preferred agent characteristics with greater accuracy and flexibility than was feasible in 2019, making the core process more robust.
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