Patents by Inventor Macgregor S. Gainor
Macgregor S. Gainor has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11551188Abstract: Systems and methods for scheduling appointments are provided. This scheduling process includes generating an introductory message proposing an appointment with the target with a request for timing. The target responds, and this response is processed for a positive interest and the presence of a proposed time. If there is an absence of positive interest then the messaging may be discontinued. However, in the presence of a positive interest, and a proposed time from the target, the system may access an external scheduling system when a proposed time is present. This includes determining availability of at least one resource at the proposed time. The system then iteratively provides suggested times close to the proposed time when the resource is not available for the proposed time. The system then confirms the appointment when the resource is available for either the proposed time or any of the suggested times.Type: GrantFiled: August 8, 2019Date of Patent: January 10, 2023Assignee: CONVERSICA, INC.Inventors: Siddhartha Reddy Jonnalagadda, George Alexis Terry, James D. Harriger, Werner Koepf, William Dominic Webb-Purkis, Macgregor S. Gainor, Patrick D. Griffin
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Patent number: 11301632Abstract: Systems and methods for natural language processing and classification are provided. In some embodiments, the systems and methods include a communication editor dashboard which receives the message, performs natural language processing to divide the message into component parts. The system displays the message in a first pane with each of the component parts overlaid with a different color, and displaying in a second pane the insights, the confidence scores associated with each insight, the sentiment and the actions. In another embodiment, the systems and methods include combining outputs from multiple machine learned AI models into a unified output. In another embodiment, the systems and methods include responding to simple question using natural language processing.Type: GrantFiled: June 26, 2018Date of Patent: April 12, 2022Assignee: CONVERSICA, INC.Inventors: Alex Terry, Werner Koepf, James Harriger, Will Webb-Purkis, Joseph M. Silverbears, Macgregor S. Gainor, Ryan Ginstrom, Siddhartha Reddy Jonnalagadda
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Patent number: 11106871Abstract: Systems and methods for a configurable response-action engine are provided. Actions are generated for a conversation when an insight is received from a natural language processing system. Industry, segment, client specific instructions, third party data, a state for the lead and lead historical patterns are also received. A decision making action model is tuned using this information. An objective for the conversation may be extracted from the state information for the lead. The tuned model is then applied to the insight and objective to output an action. A response message may be generated for the action. The action is directed to cause a state transition of the lead to a preferred state. In another embodiment, systems and methods are presented for feature extraction from one or more messages. In yet other embodiments, systems and methods for message cadence optimization are provided.Type: GrantFiled: October 23, 2018Date of Patent: August 31, 2021Assignee: CONVERSICA, INC.Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, Joseph M. Silverbears, William Dominic Webb-Purkis, Macgregor S. Gainor, Ryan Francis Ginstrom, Siddhartha Reddy Jonnalagadda
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Patent number: 11100285Abstract: Systems and methods for a configurable response-action engine are provided. Actions are generated for a conversation when an insight is received from a natural language processing system. Industry, segment, client specific instructions, third party data, a state for the lead and lead historical patterns are also received. A decision making action model is tuned using this information. An objective for the conversation may be extracted from the state information for the lead. The tuned model is then applied to the insight and objective to output an action. A response message may be generated for the action. The action is directed to cause a state transition of the lead to a preferred state. In another embodiment, systems and methods are presented for feature extraction from one or more messages. In yet other embodiments, systems and methods for message cadence optimization are provided.Type: GrantFiled: October 23, 2018Date of Patent: August 24, 2021Assignee: CONVERSICA, INC.Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, Joseph M. Silverbears, William Dominic Webb-Purkis, Macgregor S. Gainor, Ryan Francis Ginstrom, Siddhartha Reddy Jonnalagadda
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Patent number: 11010555Abstract: Systems and methods for natural language processing and classification are provided. In some embodiments, the systems and methods include a communication editor dashboard which receives the message, performs natural language processing to divide the message into component parts. The system displays the message in a first pane with each of the component parts overlaid with a different color, and displaying in a second pane the insights, the confidence scores associated with each insight, the sentiment and the actions. In another embodiment, the systems and methods include combining outputs from multiple machine learned AI models into a unified output. In another embodiment, the systems and methods include responding to simple question using natural language processing.Type: GrantFiled: September 12, 2018Date of Patent: May 18, 2021Assignee: CONVERSICA, INC.Inventors: Alex Terry, Werner Koepf, James Harriger, Will Webb-Purkis, Joseph M. Silverbears, Macgregor S. Gainor, Ryan Ginstrom, Siddhartha Reddy Jonnalagadda
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Patent number: 10803479Abstract: Systems and methods for management of automated dynamic messages are providing. In some embodiments, a data store is populated with one or more knowledge sets and one or more lead datasets in response to a user's input. A campaign builder may be provided to the user for generating and initiating campaigns. A campaign is a series of messages designed to satisfy one or more objectives. The campaign builder allows the creation of a campaign by allowing the composition of a series of message templates with variable fields. The variable fields correspond to classes of data from the knowledge sets and/or the lead data. Once the campaign has been initiated, the system categorizes the responses using algorithms. These categorizations have corresponding confidence levels. If the confidence level is too low, manual user intervention may be required in order to determine which subsequent action the system should perform.Type: GrantFiled: January 23, 2015Date of Patent: October 13, 2020Assignee: CONVERSICA, INC.Inventors: Benjamin P. Brigham, Macgregor S. Gainor, Joseph M. Silverbears, Patrick D. Griffin, Jared Keller
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Publication number: 20200272791Abstract: Systems and methods for an automated conversation with a transactional assistant are provided. This conversation relies upon initially a set of exchanges being defined. Each exchange connected to every other exchange by bidirectional edge transitions. A response from the conversation target is received, and is processed for natural language understanding (NLU) generate intents and entities. After the NLU, a determination is made which bidirectional edge transition applies, as a function of the intent and the source exchange. Subsequently, the exchange may be transitioned to a new exchange based upon the determined bidirectional edge transition, and a response is formulated using natural language generation (NLG) for the new exchange.Type: ApplicationFiled: February 24, 2020Publication date: August 27, 2020Inventors: Siddhartha Reddy Jonnalagadda, Macgregor S. Gainor, Connor Mack Gouge, Patrick D. Griffin, Alexander Eliseev, Kerri Louise Rapes, Ivania Donoso Guzman, Andres Collao, Emmanuel Faddoul, Ernesto Trujillo, Oscar Oteiza, David Manriquez, Heilein Izaguirre, Will Kempff Beeler
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Publication number: 20200143247Abstract: Systems and methods for generating intents for a response is provided. The tokens of the response is encoded into a dense vector space as a plurality of vectors. Name entities are extracted, and individual sentences and paragraphs are both classified in response to the vectors. In addition to the tokens being represented in the vector space, the sentences and paragraphs may be represented in the vector space. The entities and intents are then used to determine an action for the system according to a policy that is optimized for. Annotations may be requested when the classifications are below thresholds, and these annotations may be employed in the action determination process. Annotation includes receiving an annotation work in an annotation queue, prioritizing the annotations, and sending the highest priority annotations to the annotator in order. This is used to update the production annotation database.Type: ApplicationFiled: December 25, 2019Publication date: May 7, 2020Inventors: Siddhartha Reddy Jonnalagadda, Connor Mack Gouge, Macgregor S. Gainor, Ryan Francis Ginstrom
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Publication number: 20200034797Abstract: Systems and methods for scheduling appointments are provided. This scheduling process includes generating an introductory message proposing an appointment with the target with a request for timing. The target responds, and this response is processed for a positive interest and the presence of a proposed time. If there is an absence of positive interest then the messaging may be discontinued. However, in the presence of a positive interest, and a proposed time from the target, the system may access an external scheduling system when a proposed time is present. This includes determining availability of at least one resource at the proposed time. The system then iteratively provides suggested times close to the proposed time when the resource is not available for the proposed time. The system then confirms the appointment when the resource is available for either the proposed time or any of the suggested times.Type: ApplicationFiled: August 8, 2019Publication date: January 30, 2020Inventors: Siddhartha Reddy Jonnalagadda, George Alexis Terry, James D. Harriger, Werner Koepf, William Dominic Webb-Purkis, Macgregor S. Gainor, Patrick D. Griffin
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Publication number: 20190286713Abstract: Systems and methods for variable field replacement are provided. Message templates include variable fields that can be populated with industry and client specific information through entity replacement, lexical replacement and phrase package selection. In addition to the generation of messages, the system may also be able to perform other actions that leverage external third-party systems. The templates may be drawn from a conversation library with hierarchical inheritance. Likewise, actions may leverage an action response library that links triggers in the response to required actions. Packet selection is based upon how closely the phrase fits a personality for the AI identity, and how well historically the phrase has performed. Lastly, while the AI systems disclosed herein have the ability to understand and respond to conversations in natural language format, this is computationally expensive. These AI systems may use an objective and intent based communication protocol when communicating with one another.Type: ApplicationFiled: March 26, 2019Publication date: September 19, 2019Inventors: George Alexis Terry, James D. Harriger, Werner Koepf, Siddhartha Reddy Jonnalagadda, William Dominic Webb-Purkis, Macgregor S. Gainor, Patrick D. Griffin
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Publication number: 20190286712Abstract: Systems and methods for variable field replacement are provided. Message templates include variable fields that can be populated with industry and client specific information through entity replacement, lexical replacement and phrase package selection. In addition to the generation of messages, the system may also be able to perform other actions that leverage external third-party systems. The templates may be drawn from a conversation library with hierarchical inheritance. Likewise, actions may leverage an action response library that links triggers in the response to required actions. Packet selection is based upon how closely the phrase fits a personality for the AI identity, and how well historically the phrase has performed. Lastly, while the AI systems disclosed herein have the ability to understand and respond to conversations in natural language format, this is computationally expensive. These AI systems may use an objective and intent based communication protocol when communicating with one another.Type: ApplicationFiled: March 26, 2019Publication date: September 19, 2019Inventors: George Alexis Terry, James D. Harriger, Werner Koepf, Siddhartha Reddy Jonnalagadda, William Dominic Webb-Purkis, Macgregor S. Gainor, Patrick D. Griffin
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Publication number: 20190286711Abstract: Systems and methods for variable field replacement are provided. Message templates include variable fields that can be populated with industry and client specific information through entity replacement, lexical replacement and phrase package selection. In addition to the generation of messages, the system may also be able to perform other actions that leverage external third-party systems. The templates may be drawn from a conversation library with hierarchical inheritance. Likewise, actions may leverage an action response library that links triggers in the response to required actions. Packet selection is based upon how closely the phrase fits a personality for the AI identity, and how well historically the phrase has performed. Lastly, while the AI systems disclosed herein have the ability to understand and respond to conversations in natural language format, this is computationally expensive. These AI systems may use an objective and intent based communication protocol when communicating with one another.Type: ApplicationFiled: March 26, 2019Publication date: September 19, 2019Inventors: George Alexis Terry, James D. Harriger, Werner Koepf, Siddhartha Reddy Jonnalagadda, William Dominic Webb-Purkis, Macgregor S. Gainor, Patrick D. Griffin
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Publication number: 20190220773Abstract: Systems and methods for more effective AI operations, improvements to the experience of a conversation target, and increased productivity through AI assistance are provided. In some embodiments, the systems use machine learning models to classify a number of message responses with a confidence. If these classifications are below a threshold the messages are sent to a user for analysis, after prioritization, along with guidance data. Feedback from the user modified the models. In another embodiment, a system and method for an AI assistant is also provided which receives messages and determines instructions using keywords and/or classifications. The AI assistant then executes upon these instructions. In another embodiment, a conversation editor interface is provided. The conversation editor includes one or more displays that illustrate an overview flow diagram for the conversation, specific node analysis, libraries of conversations and potentially metrics that can help inform conversation flow.Type: ApplicationFiled: December 20, 2018Publication date: July 18, 2019Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, William Dominic Webb-Purkis, Siddhartha Reddy Jonnalagadda, Macgregor S. Gainor, Colin C. Ferguson
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Publication number: 20190220774Abstract: Systems and methods for more effective AI operations, improvements to the experience of a conversation target, and increased productivity through AI assistance are provided. In some embodiments, the systems use machine learning models to classify a number of message responses with a confidence. If these classifications are below a threshold the messages are sent to a user for analysis, after prioritization, along with guidance data. Feedback from the user modified the models. In another embodiment, a system and method for an AI assistant is also provided which receives messages and determines instructions using keywords and/or classifications. The AI assistant then executes upon these instructions. In another embodiment, a conversation editor interface is provided. The conversation editor includes one or more displays that illustrate an overview flow diagram for the conversation, specific node analysis, libraries of conversations and potentially metrics that can help inform conversation flow.Type: ApplicationFiled: December 20, 2018Publication date: July 18, 2019Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, William Dominic Webb-Purkis, Siddhartha Reddy Jonnalagadda, Macgregor S. Gainor
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Publication number: 20190179903Abstract: Systems and methods for improvements in AI model learning and updating are provided. The model updating may reuse existing business conversations as the training data set. Features within the dataset may be defined and extracted. Models may be selected and parameters for the models defined. Within a distributed computing setting the parameters may be optimized, and the models deployed. The training data may be augmented over time to improve the models. Deep learning models may be employed to improve system accuracy, as can active learning techniques. The models developed and updated may be employed by a response system generally, or may function to enable specific types of AI systems. One such a system may be an AI assistant that is designed to take use cases and objectives, and execute tasks until the objectives are met. Another system capable of leveraging the models includes an automated question answering system utilizing approved answers.Type: ApplicationFiled: December 3, 2018Publication date: June 13, 2019Inventors: George Alexis Terry, Werner Koepf, Siddhartha Reddy Jonnalagadda, James D. Harriger, William Dominic Webb-Purkis, Macgregor S. Gainor, Ryan Francis Ginstrom, Caleb Andrew Bredlow, Kyle Sargent, Alexander Carmelo Reid Fordyce, Ian McCann
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Publication number: 20190180196Abstract: Systems and methods for improvements in AI model learning and updating are provided. The model updating may reuse existing business conversations as the training data set. Features within the dataset may be defined and extracted. Models may be selected and parameters for the models defined. Within a distributed computing setting the parameters may be optimized, and the models deployed. The training data may be augmented over time to improve the models. Deep learning models may be employed to improve system accuracy, as can active learning techniques. The models developed and updated may be employed by a response system generally, or may function to enable specific types of AI systems. One such a system may be an AI assistant that is designed to take use cases and objectives, and execute tasks until the objectives are met. Another system capable of leveraging the models includes an automated question answering system utilizing approved answers.Type: ApplicationFiled: December 3, 2018Publication date: June 13, 2019Inventors: George Alexis Terry, Werner Koepf, Siddhartha Reddy Jonnalagadda, James D. Harriger, William Dominic Webb-Purkis, Macgregor S. Gainor, Colin C. Ferguson, Ravi Shankar, Shashi Shankar, Ian McCann
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Publication number: 20190129933Abstract: Systems and methods for a configurable response-action engine are provided. Actions are generated for a conversation when an insight is received from a natural language processing system. Industry, segment, client specific instructions, third party data, a state for the lead and lead historical patterns are also received. A decision making action model is tuned using this information. An objective for the conversation may be extracted from the state information for the lead. The tuned model is then applied to the insight and objective to output an action. A response message may be generated for the action. The action is directed to cause a state transition of the lead to a preferred state. In another embodiment, systems and methods are presented for feature extraction from one or more messages. In yet other embodiments, systems and methods for message cadence optimization are provided.Type: ApplicationFiled: October 23, 2018Publication date: May 2, 2019Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, Joseph M. Silverbears, William Dominic Webb-Purkis, Macgregor S. Gainor, Ryan Francis Ginstrom, Siddhartha Reddy Jonnalagadda
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Publication number: 20190122236Abstract: Systems and methods for a configurable response-action engine are provided. Actions are generated for a conversation when an insight is received from a natural language processing system. Industry, segment, client specific instructions, third party data, a state for the lead and lead historical patterns are also received. A decision making action model is tuned using this information. An objective for the conversation may be extracted from the state information for the lead. The tuned model is then applied to the insight and objective to output an action. A response message may be generated for the action. The action is directed to cause a state transition of the lead to a preferred state. In another embodiment, systems and methods are presented for feature extraction from one or more messages. In yet other embodiments, systems and methods for message cadence optimization are provided.Type: ApplicationFiled: October 23, 2018Publication date: April 25, 2019Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, Joseph M. Silverbears, William Dominic Webb-Purkis, Macgregor S. Gainor, Ryan Francis Ginstrom, Siddhartha Reddy Jonnalagadda
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Publication number: 20190121856Abstract: Systems and methods for a configurable response-action engine are provided. Actions are generated for a conversation when an insight is received from a natural language processing system. Industry, segment, client specific instructions, third party data, a state for the lead and lead historical patterns are also received. A decision making action model is tuned using this information. An objective for the conversation may be extracted from the state information for the lead. The tuned model is then applied to the insight and objective to output an action. A response message may be generated for the action. The action is directed to cause a state transition of the lead to a preferred state. In another embodiment, systems and methods are presented for feature extraction from one or more messages. In yet other embodiments, systems and methods for message cadence optimization are provided.Type: ApplicationFiled: October 23, 2018Publication date: April 25, 2019Inventors: George Alexis Terry, Werner Koepf, James D. Harriger, Joseph M. Silverbears, William Dominic Webb-Purkis, Macgregor S. Gainor, Ryan Francis Ginstrom, Siddhartha Reddy Jonnalagadda
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Publication number: 20190079921Abstract: Systems and methods for natural language processing and classification are provided. In some embodiments, the systems and methods include a communication editor dashboard which receives the message, performs natural language processing to divide the message into component parts. The system displays the message in a first pane with each of the component parts overlaid with a different color, and displaying in a second pane the insights, the confidence scores associated with each insight, the sentiment and the actions. In another embodiment, the systems and methods include combining outputs from multiple machine learned AI models into a unified output. In another embodiment, the systems and methods include responding to simple question using natural language processing.Type: ApplicationFiled: September 12, 2018Publication date: March 14, 2019Inventors: Alex Terry, Werner Koepf, James Harriger, Will Webb-Purkis, Joseph M. Silverbears, Macgregor S. Gainor, Ryan Ginstrom, Siddhartha Reddy Jonnalagadda