Abstract: Systems and methods for batch multiplexing a plurality of transactions are provided. A system may include a machine-learning (“ML”) based engine configured to receive instructions to execute a first transaction, derive a plurality of sets of delay parameters for the first transaction, and display the sets of delay parameters on a graphical user interface (“GUI”) associated with a sender of the instructions. The engine may be configured to receive a selection of a set of delay parameters, and, based on the selection, append the first transaction to one of a plurality of pending transaction queues. The engine may be further configured to, within a maximum time window, combine the transactions in the pending transaction queue to create a single multiplexed transaction, and execute the multiplexed transaction. The engine may also be configured to demultiplex the multiplexed transaction after it is executed.

Abstract: Aspects of the present disclosure are directed to electronic computer implemented methods of data communication. The method includes receiving a plurality of virtual nodes with EDI data payload including a node attribute, a GPS location attribute and a biometric ID attribute and at least one data element associated with the GPS location attribute. In further aspect, the method includes electronically via a data communications network, processing the EDI data payloads including the node attribute, the GPS location attribute and the biometric ID attribute and the at least one data element associated with the GPS location attribute. Then, electronically processing the EDI data payloads in a network with machine learning and providing an electronic message responsive thereto. In yet a further aspect, the data communications method includes a step of processing the smart data set in the network with machine learning and providing an electronic message responsive thereto.

Abstract: Aspects of the disclosure relate to utilizing smart data tags to track and control secure enterprise data. A computing platform may receive, from an enterprise user computing device, enterprise data. Subsequently, the computing platform may determine one or more tags to be applied to the enterprise data. Then, the computing platform may generate a smart data object based on the enterprise data received from the enterprise user computing device and the one or more tags determined to be applied to the enterprise data received from the enterprise user computing device. Next, the computing platform may send, to an enterprise data storage platform, the smart data object, and sending the smart data object to the enterprise data storage platform may cause the enterprise data storage platform to store the smart data object in a repository comprising a plurality of smart data objects maintained by the enterprise data storage platform.

Abstract: An apparatus that matches one or more affiliates to a user includes a memory, a geofencing engine, an artificial intelligence engine, and processing circuitry communicatively coupled to each. The geofencing engine determines a current geofenced area of a mobile device of the user. The artificial intelligence engine determines anticipated needs of the user. The processing circuitry determines, using the affiliate database, a list of candidate affiliates for the current geofenced area, and transmits a query to an affiliate feed for the list of candidate affiliates, where the query is based at least in part on the anticipated need of the user. The processing circuitry determines a first affiliate and a second affiliate based on the query and receives query results for the first affiliate and the second affiliate from the affiliate feed. The results are transmitted to the mobile device for presentation in a user interface.

Abstract: An intelligent hub for protocol-agnostic file transfer. The hub may include a transceiver, an interrogator processor, an intelligence engine processor, a data translation processor and a hashing processor. The hub may utilize artificial intelligence processes to perform real-time networking or file transfer protocol conversion.

Abstract: Aspects of the disclosure relate to transforming event data associated with an entity using a multicomputer platform and directing a client computing device to perform a determined action based on a detected event characteristic of the event data and a detected current event. With some embodiments, an event tracking server detects the current event from sensed data provided by a sensed data server and identifies a correlation measure between the detected event characteristic and the detected current event. The event tracking server may direct one or more client computing devices to perform one or more actions related to an entity based on the correlation measure.

Abstract: An apparatus that matches one or more affiliates to a user includes a memory, a geofencing engine, an artificial intelligence engine, and processing circuitry communicatively coupled to each. The geofencing engine determines a current geofenced area of a mobile device of the user. The artificial intelligence engine determines anticipated needs of the user. The processing circuitry determines, using the affiliate database, a list of candidate affiliates for the current geofenced area, and transmits a query to an affiliate feed for the list of candidate affiliates, where the query is based at least in part on the anticipated need of the user. The processing circuitry determines a first affiliate and a second affiliate based on the query and receives query results for the first affiliate and the second affiliate from the affiliate feed. The results are transmitted to the mobile device for presentation in a user interface.

Abstract: Aspects of the disclosure relate to utilizing smart data tags to track and control secure enterprise data. A computing platform may receive, from an enterprise user computing device, enterprise data. Subsequently, the computing platform may determine one or more tags to be applied to the enterprise data. Then, the computing platform may generate a smart data object based on the enterprise data received from the enterprise user computing device and the one or more tags determined to be applied to the enterprise data received from the enterprise user computing device. Next, the computing platform may send, to an enterprise data storage platform, the smart data object, and sending the smart data object to the enterprise data storage platform may cause the enterprise data storage platform to store the smart data object in a repository comprising a plurality of smart data objects maintained by the enterprise data storage platform.

Abstract: A method for throttling an allocation of resources for processing digital transmissions is provided. The method may include receiving initial digital transmissions from a plurality of client systems and analyzing the initial digital transmissions. The analyzing may determine a cluster of digital transmissions, an amount of resources for processing the cluster and a time-window for processing the cluster. The method may further include allocating the determined amount of resources to each of the clusters. The method may also include processing recurrently, for each of the systems, digital transmissions received after the initial digital transmissions. Concurrently with the periodic processing, the method may include, for each client system, monitoring digital transmissions including recording a transmission log, identifying changes in the log, assigning a credibility score and throttling, dynamically, the amount of resources allocated, based on the credibility score and the identified change.

Abstract: Aspects of the disclosure relate to transforming event data associated with an entity using a multicomputer platform and directing a client computing device to perform a determined action based on a detected event characteristic of the event data and a detected current event. With some embodiments, an event tracking server detects the current event from sensed data provided by a sensed data server and identifies a correlation measure between the detected event characteristic and the detected current event. The event tracking server may direct one or more client computing devices to perform one or more actions related to an entity based on the correlation measure.

Abstract: Systems for dynamic authentication are provided. In some examples, a system may receive a request to process an event. In some examples, the request to process the event may include additional details associated with the event. The system may initiate dynamic authentication functions and may retrieve data from a plurality of sources. In some examples, the data from the plurality of sources may be analyzed using machine learning to dynamically generate authentication data, such as one or more authentication questions. The system may also generate one or more corresponding responses or answers to the one or more authentication questions. In some examples, the one or more authentication questions may be transmitted to a user device or other device and may be displayed to the user. The user may provide authentication response data that may be analyzed by the system to determine whether it matches the generated response or answer. If so, the user may be authenticated and/or the event may be processed.

Abstract: Aspects of the present disclosure are directed to electronic computer implemented methods of data communication. The method includes receiving a plurality of virtual nodes with EDI data payload including a node attribute, a GPS location attribute and a biometric ID attribute and at least one data element associated with the GPS location attribute. In further aspect, the method includes electronically via a data communications network, processing the EDI data payloads including the node attribute, the GPS location attribute and the biometric ID attribute and the at least one data element associated with the GPS location attribute. Then, electronically processing the EDI data payloads in a network with machine learning and providing an electronic message responsive thereto. In yet a further aspect, the data communications method includes a step of processing the smart data set in the network with machine learning and providing an electronic message responsive thereto.

Abstract: Aspects of the disclosure relate to providing cloud computing resources from one or more cloud service providers for a client computing device through a computing platform. The client computing device may benefit from an economy of scale while being able to obtain different types of cloud services over a plurality of cloud providers. The client computing device may request an initial amount of cloud services and subsequently may request cloud services that utilize a requested amount of cloud resources. The requested amount of cloud resources may be apportioned among the plurality of cloud service providers, to provide the requested cloud service. The computing platform may also support a cloud abstraction layer interacting between client computing device and one or more cloud providers so that the client computing device can obtain cloud service in a transparent manner.

Abstract: Aspects of the present disclosure are directed to electronic computer implemented methods of data communication. The method includes receiving a plurality of virtual nodes with EDI data payload including a node attribute, a GPS location attribute and a biometric ID attribute and at least one data element associated with the GPS location attribute. In further aspect, the method includes electronically via a data communications network, processing the EDI data payloads including the node attribute, the GPS location attribute and the biometric ID attribute and the at least one data element associated with the GPS location attribute. Then, electronically processing the EDI data payloads in a network with machine learning and providing an electronic message responsive thereto. In yet a further aspect, the data communications method includes a step of processing the smart data set in the network with machine learning and providing an electronic message responsive thereto.

Abstract: Aspects of the present disclosure are directed to electronic computer implemented methods of data communication. The method includes receiving a plurality of virtual nodes with EDI data payload including a node attribute, a GPS location attribute and a biometric ID attribute and at least one data element associated with the GPS location attribute. In further aspect, the method includes electronically via a data communications network, processing the EDI data payloads including the node attribute, the GPS location attribute and the biometric ID attribute and the at least one data element associated with the GPS location attribute. Then, electronically processing the EDI data payloads in a network with machine learning and providing an electronic message responsive thereto. In yet a further aspect, the data communications method includes a step of processing the smart data set in the network with machine learning and providing an electronic message responsive thereto.

Abstract: Aspects of the disclosure relate to transforming event data associated with an entity using a multicomputer platform and directing a client computing device to perform a determined action based on a detected event characteristic of the event data and a detected current event. With some embodiments, an event tracking server detects the current event from sensed data provided by a sensed data server and identifies a correlation measure between the detected event characteristic and the detected current event. The event tracking server may direct one or more client computing devices to perform one or more actions related to an entity based on the correlation measure.