Carvana has been granted a patent for an artificial intelligence (AI) conversation system that can engage in automated conversations with users. The system uses trained models to analyze user messages, determine intent, extract entities, and construct appropriate responses based on the conversation context. GlobalData’s report on Carvana gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Carvana, Virtual try-ons was a key innovation area identified from patents. Carvana's grant share as of September 2023 was 59%. Grant share is based on the ratio of number of grants to total number of patents.
Automated ai conversation system for responding to user inquiries
A recently granted patent (Publication Number: US11777874B1) describes a method and system for automated conversations with users using an artificial intelligence (AI) conversation system. The method involves receiving multiple messages from a customer in a conversation and applying various models to analyze the message text.
The system uses a topic category model to compare the message text with a set of topic category reference feature vectors, determining the highest similarity topic category reference feature vector. This helps determine the topic category represented by the message. Additionally, an intent model compares the message text with a set of intent class reference feature vectors, determining the highest similarity intent class reference feature vector. This helps determine the intent class represented by the message. The method also involves using machine learning models to determine the requested intent based on the message text and storing it in a dataset associated with the customer.
After receiving the initial messages, the system can receive a new message from the customer. It then extracts entities from the new message text and determines the state of the conversation based on the new message. The system predicts information based on the extracted entities and the requested intents stored in the dataset, which is used to construct a response to the received message text. The response is based on the extracted entities, the determined state of the conversation, the topic category, the intent class, and the predicted information.
The conversation system described in the patent also includes the ability to determine state changes during the conversation based on predefined rules. If a state change occurs, the system changes the conversation to a second state and constructs another response based on the extracted entities and the new state of the conversation.
Overall, this patent presents a method and system for automated conversations with users using AI. It utilizes various models and machine learning techniques to analyze and understand user messages, determine intents, and generate appropriate responses based on the conversation context.
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