Abstract: Systems, devices, and methods to automate communications via an operator portal are disclosed. A system may obtain session data generated during a communications session involving a device and a programmatic agent, the session data characterizing a query associated with a first party. The system may generate output data characterizing one or more allowable actions and determine that at least one of the one or more allowable actions is consistent with one or more constraints imposed on the trained artificial intelligence process. The system may, based on a determination that the at least one of the one or more allowable actions is insufficient to respond to the query, transmit notification data characterizing the allowable action and the query to a computing system associated with a second party. The system may receive response data characterizing a response to the query from the computing system associated with the second party.

Abstract: Improved systems and methods for automatically discovering and filtering electronic messages. These systems and methods improve the operation of computer apparatus to achieve dramatic reductions in processing resources, data storage resources, network resources, and filter production times compared to conventional approaches. In some examples, improvements result from configuring computer apparatus to perform a unique sequence of specific electronic message processing rules in a network communications environment. In this regard, these examples are able to automatically learn the structures and semantics of machine generated electronic message headers, accelerating the ability to support new message sources and new markets. These examples provide a purchase related electronic message discovery and filtering service that is able to identify and filter purchase related electronic messages with high accuracy across a wide variety of electronic message formats.

Abstract: Improved systems and methods for automatically discovering and filtering electronic messages. These systems and methods improve the operation of computer apparatus to achieve dramatic reductions in processing resources, data storage resources, network resources, and filter production times compared to conventional approaches. In some examples, improvements result from configuring computer apparatus to perform a unique sequence of specific electronic message processing rules in a network communications environment. In this regard, these examples are able to automatically learn the structures and semantics of machine generated electronic message headers, accelerating the ability to support new message sources and new markets. These examples provide a purchase related electronic message discovery and filtering service that is able to identify and filter purchase related electronic messages with high accuracy across a wide variety of electronic message formats.

Abstract: Improved systems and methods for automatically discovering and filtering electronic messages. These systems and methods improve the operation of computer apparatus to achieve dramatic reductions in processing resources, data storage resources, network resources, and filter production times compared to conventional approaches. In some examples, improvements result from configuring computer apparatus to perform a unique sequence of specific electronic message processing rules in a network communications environment. In this regard, these examples are able to automatically learn the structures and semantics of machine generated electronic message headers, accelerating the ability to support new message sources and new markets. These examples provide a purchase related electronic message discovery and filtering service that is able to identify and filter purchase related electronic messages with high accuracy across a wide variety of electronic message formats.

Abstract: Improved systems and methods for automatically discovering and filtering electronic messages. These systems and methods improve the operation of computer apparatus to achieve dramatic reductions in processing resources, data storage resources, network resources, and filter production times compared to conventional approaches. In some examples, improvements result from configuring computer apparatus to perform a unique sequence of specific electronic message processing rules in a network communications environment. In this regard, these examples are able to automatically learn the structures and semantics of machine generated electronic message headers, accelerating the ability to support new message sources and new markets. These examples provide a purchase related electronic message discovery and filtering service that is able to identify and filter purchase related electronic messages with high accuracy across a wide variety of electronic message formats.

Abstract: Improved systems and methods for extracting product purchase information from electronic messages transmitted between physical network nodes to convey product purchase information to designated recipients. These examples provide a product purchase information extraction service that is able to extract product purchase information from electronic messages with high precision across a wide variety of electronic message formats and thereby solve the practical problems that have arisen as a result of the proliferation of different electronic message formats used by individual merchants and across different merchants and different languages. In this regard, these examples are able to automatically learn the structures and semantics of different message formats, which accelerates the ability to support new message sources, new markets, and different languages.

Abstract: Improved systems and methods for extracting product purchase information from electronic messages transmitted between physical network nodes to convey product purchase information to designated recipients. These examples provide a product purchase information extraction service that is able to extract product purchase information from electronic messages with high precision across a wide variety of electronic message formats and thereby solve the practical problems that have arisen as a result of the proliferation of different electronic message formats used by individual merchants and across different merchants and different languages. In this regard, these examples are able to automatically learn the structures and semantics of different message formats, which accelerates the ability to support new message sources, new markets, and different languages.

Abstract: Improved systems and methods for extracting product purchase information from electronic messages transmitted between physical network nodes to convey product purchase information to designated recipients. These examples provide a product purchase information extraction service that is able to extract product purchase information from electronic messages with high precision across a wide variety of electronic message formats and thereby solve the practical problems that have arisen as a result of the proliferation of different electronic message formats used by individual merchants and across different merchants and different languages. In this regard, these examples are able to automatically learn the structures and semantics of different message formats, which accelerates the ability to support new message sources, new markets, and different languages.

Abstract: Improved systems and methods for extracting product purchase information from electronic messages transmitted between physical network nodes to convey product purchase information to designated recipients. These examples provide a product purchase information extraction service that is able to extract product purchase information from electronic messages with high precision across a wide variety of electronic message formats and thereby solve the practical problems that have arisen as a result of the proliferation of different electronic message formats used by individual merchants and across different merchants and different languages. In this regard, these examples are able to automatically learn the structures and semantics of different message formats, which accelerates the ability to support new message sources, new markets, and different languages.

Abstract: Improved systems and methods for extracting product purchase information from electronic messages transmitted between physical network nodes to convey product purchase information to designated recipients. These examples provide a product purchase information extraction service that is able to extract product purchase information from electronic messages with high precision across a wide variety of electronic message formats and thereby solve the practical problems that have arisen as a result of the proliferation of different electronic message formats used by individual merchants and across different merchants and different languages. In this regard, these examples are able to automatically learn the structures and semantics of different message formats, which accelerates the ability to support new message sources, new markets, and different languages.

Abstract: Improved systems and methods for extracting product purchase information from electronic messages transmitted between physical network nodes to convey product purchase information to designated recipients. These examples provide a product purchase information extraction service that is able to extract product purchase information from electronic messages with high precision across a wide variety of electronic message formats and thereby solve the practical problems that have arisen as a result of the proliferation of different electronic message formats used by individual merchants and across different merchants and different languages. In this regard, these examples are able to automatically learn the structures and semantics of different message formats, which accelerates the ability to support new message sources, new markets, and different languages.