LivePerson had 18 patents in digitalization during Q2 2024. LivePerson Inc’s patents in Q2 2024 focus on artificial intelligence-based formatting of data for interface-specific representations, analyzing conversation data to identify intents and provide recommendations, implementing automated bots for opt-in offers during communications, and enabling rich messaging for obtaining payments via offline channels. These patents aim to enhance user interactions and streamline business transactions through innovative technology solutions. GlobalData’s report on LivePerson gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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LivePerson had no grants in digitalization as a theme in Q2 2024.
Recent Patents
Application: Methods and systems for implementing a unified data format for artificial intelligence systems (Patent ID: US20240211477A1)
LivePerson Inc. has developed a system and method for artificial intelligence-based formatting of data into interface-specific representations. The system involves receiving datasets structured for various interfaces, training a machine-learning model using feature vectors from the datasets to generate interface-specific representations, and executing the model to respond to queries through a specific interface. The response is tailored to the interface type and transmitted accordingly. The method includes training the model, receiving queries, and facilitating responses through the corresponding interface, enhancing user interaction and data presentation efficiency.
The patent claims detail the method and system's steps, including receiving datasets, defining feature vectors, training the machine-learning model, executing the model based on queries and interface types, and facilitating responses through the specific interface. Additional claims specify the inclusion of audio segments in datasets, different types of user interfaces like text messaging or webpages, and modifying the model based on input to improve response accuracy. The patent aims to optimize data presentation across various interfaces by utilizing machine learning to tailor responses, enhancing user experience and interaction efficiency.
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