Systems and methods for processing message exchanges using artificial intelligence

Abstract

Systems and methods for processing automated message exchanges using artificial intelligence are providing. In some embodiments, a message is generated by populating variable fields within a message template with corresponding data from a knowledge set and/or a lead data set. Lead data is the data known about the intended recipient of the message, whereas the knowledge set is contextual knowledge useful for the artificial intelligence. Once the message has been generated, the system waits for a response from the lead. Once the response is received, the AI algorithms may categorize the response and generate a corresponding confidence value for the categorization. The categorization and confidence level are utilized to determine which subsequent action the system takes. The actions consist of sending a follow-up message, a subsequent message in the series, requesting user input, or discontinuing messaging.

What is claimed is: 
     
         1 . In a computerized messaging system, a method for processing message exchanges, useful in association with an artificial intelligence system, the method comprising:
 generating a first message by populating variable fields within a first message template with corresponding data from at least one of a knowledge set and a lead data set;   receiving a response from the lead to the first message;   categorizing the response using at least one artificial intelligence algorithm;   generating a confidence value for the categorization; and   determining an action based upon the categorization and the confidence value.   
     
     
         2 . The method of  claim 1 , wherein the first message is a textual message. 
     
     
         3 . The method of  claim 1 , wherein the first message is a message within a series of messages. 
     
     
         4 . The method of  claim 3 , wherein the action includes at least one of seeking user input, proceeding to a second message within the series of messages, discontinuing messaging, and generating a follow-up message. 
     
     
         5 . The method of  claim 4 , wherein the each message within the series of messages has an objective. 
     
     
         6 . The method of  claim 5 , wherein if the response satisfies the objective for the first message, then the action is proceeding to the second message. 
     
     
         7 . The method of  claim 4 , wherein if the confidence value is less than a threshold, then the action is seeking user input. 
     
     
         8 . The method of  claim 5 , wherein if no response is received or if the objective of the first message is not met, then the action is generating a follow-up message. 
     
     
         9 . The method of  claim 1 , wherein the at least one artificial intelligence algorithm compares n-grams within the response to the knowledge set, wherein each n-gram is associated with at least one category with a confidence level, and wherein presence of sufficient n-grams related to a category strongly results in a categorization, and wherein the degree of how strongly the n-grams correspond to the category determined the confidence value. 
     
     
         10 . The method of  claim 1 , wherein the at least one artificial intelligence algorithm compares n-grams within the response to a listing of terms that overwhelmingly are associated with a particular category, and if such a term exists in the n-grams, categorizing the response to the category associated with the term. 
     
     
         11 . An automated messaging system for processing message exchanges, comprising:
 a message builder configured to generate a first message by populating variable fields within a first message template with corresponding data from at least one of a knowledge set and a lead data set;   a message receiver configured to receive a response from the lead to the first message; and   an artificial intelligence configured to categorize the response using at least one artificial intelligence algorithm, generate a confidence value for the categorization, and determine an action based upon the categorization and the confidence value.   
     
     
         12 . The method of  claim 11 , wherein the message builder is configured to generate textual messages. 
     
     
         13 . The system of  claim 11 , wherein the message builder is configured to generate a series of messages, and wherein the first message is a message within the series of messages. 
     
     
         14 . The system of  claim 13 , wherein the action determined by the artificial intelligence includes at least one of seeking user input, proceeding to a second message within the series of messages, discontinuing messaging, and generating a follow-up message. 
     
     
         15 . The system of  claim 14 , wherein the each message within the series of messages has an objective. 
     
     
         16 . The system of  claim 15 , wherein if the response satisfies the objective for the first message, then the action is proceeding to the second message. 
     
     
         17 . The system of  claim 14 , wherein if the confidence value is less than a threshold, then the action is seeking user input. 
     
     
         18 . The system of  claim 15 , wherein if no response is received or if the objective of the first message is not met, then the action is generating a follow-up message. 
     
     
         19 . The system of  claim 11 , wherein the artificial intelligence compares n-grams within the response to the knowledge set, wherein each n-gram is associated with at least one category with a confidence level, and wherein presence of sufficient n-grams related to a category strongly results in a categorization, and wherein the degree of how strongly the n-grams correspond to the category determined the confidence value. 
     
     
         20 . The system of  claim 11 , wherein the artificial intelligence compares n-grams within the response to a listing of terms that overwhelmingly are associated with a particular category, and if such a term exists in the n-grams, categorizing the response to the category associated with the term.