Abstract: A method for enabling continuity of access to a primary dataset stored in a computer network is provided. The method utilizes a node, a computer processor, and non-transitory computer-readable media storing computer-executable instructions. The node is connected to the computer network. The method includes configuring the mobile device for wireless connection to the computer network. The method includes configuring the mobile device to receive indication that the node is disconnected from the computer network and transmit a copy of the primary dataset or a portion thereof from the computer network to the node. The method includes configuring the node to enable operations on the dataset copy and keep a record of them. The method includes configuring the node to receive indication that the node is connected to the computer network and transmit the record to the computer network.

Abstract: Apparatus, methods and systems for securely trade data from one node by another node is provided. Methods may include receiving raw data at a node. Methods may include categorizing the data. Methods may include classifying the data. Methods may include assigning data grades to the data. Methods may include assigning security levels to the data. Methods may include storing the data at a data mesh. Methods may include determining a resource consumption metric (“RCM”) for the data. Methods may include transmitting the data. The dataset may be acquired for a value specified by the RCM. Methods may include improving the data. Methods may include recategorizing, reclassifying and reassigning a security level to the data. Methods may include storing the improved data in the data mesh. Methods may include determining a new RCM for the improved data. Methods may include transmitting the improved data. Methods may include managing the transmission of the data with a third node.

Abstract: Provided herein is a method for enabling continuity of access to a primary dataset stored in a computer network, the method utilizing a node, a computer processor, and non-transitory computer-readable media storing computer-executable instructions, the node being connected to the computer network; the method including the steps of: configuring the mobile device for wireless connection to the computer network; configuring the mobile device to receive indication that the node is disconnected from the computer network, and transmit a copy of the primary dataset or a portion thereof from the computer network to the node; configuring the node to enable operations on the dataset copy and keep a record of them; and configuring the node to receive indication that the node is connected to the computer network and transmit the record to the computer network.

Abstract: Apparatus, methods and systems for securely trade data from one node by another node is provided. Methods may include receiving raw data at a node. Methods may include categorizing the data. Methods may include classifying the data. Methods may include assigning data grades to the data. Methods may include assigning security levels to the data. Methods may include storing the data at a data mesh. Methods may include determining a resource consumption metric (“RCM”) for the data. Methods may include transmitting the data. The dataset may be acquired for a value specified by the RCM. Methods may include improving the data. Methods may include recategorizing, reclassifying and reassigning a security level to the data. Methods may include storing the improved data in the data mesh. Methods may include determining a new RCM for the improved data. Methods may include transmitting the improved data. Methods may include managing the transmission of the data with a third node.

Abstract: A method for determining whether an existing customer is eligible for a zero-knowledge proof (“ZKP”) application is provided. The method may include determining that the existing customer possesses a private key linked to an account profile associated with the existing customer absent provision of the private key. The determining may also include executing a behavior-scan on the account profile to confirm that a score of the behavior-scan is equal to or greater than a pre-determined score. In response to the determining that the existing customer is eligible for the ZKP application, the method may include generating the ZKP application by executing an encryption algorithm on the sensitive data of the account profile to output a digital zero-knowledge token for each of the sensitive data and auto-filling each input field in the ZKP application that is associated with sensitive data with the digital zero-knowledge token.

Abstract: Systems, computer program products, and methods are described herein for determining probability of misappropriation of a resource based on geolocation tracking over an electronic network. The method includes receiving a resource processing request. The resource processing request includes a request geolocation and is associated with a user. The method also includes receiving a device geolocation of a user device associated with the user. The method further includes comparing the request geolocation and the device geolocation. Based on the comparison of the request geolocation and the device geolocation, the method still further includes causing an execution of the resource processing request in an instance in which the request geolocation and the device geolocation match.

Abstract: A system is provided for resource sharing over a secure wireless network communication channel. In particular, the system may include an endpoint device equipped with wireless communication capabilities. An application installed on the endpoint device may cause the endpoint device to perform a wireless scan of a network for nearby devices that are configured to send, receive, and/or exchange resources. Each device may be associated with a unique identifier, where the unique identifier may be associated with one or more resource accounts. Upon receiving a selection of a unique identifier, the endpoint device may initiate a resource transfer to the device associated with the selected identifier. In this way, the system may provide a secure and efficient way to exchange resources over a wireless communication channel.

Abstract: A system is provided for implementing predictive configuration changes based on tracking application usage patterns. In particular, the system may track usage patterns associated with a user and predict the intention of the user based on the usage patterns. For instance, the system may track resource transfers executed by the user within the application and generate one or more configuration changes for user account linkages with external entity computing systems or servers. Once the configuration changes have been generated, the system may prompt the user with a notification to accept the changes. Upon receiving an acceptance from the user, the system may dynamically and automatically implement the configuration changes. In this way, the system may provide an efficient way to generate and implement configuration changes based on tracking application usage.

Abstract: Systems, computer program products, and methods are described herein for an intelligent processing engine for acquisition, storage, and subsequent refresh of data from a distributed network. The present invention is configured to receive, from one or more distributed computing systems, an enterprise dataset; convert the enterprise dataset to a standardized format; store the enterprise dataset in one or more storage locations based on a characteristic of the enterprise dataset; provide the one or more distributed computing systems with remote access to the one or more storage locations; monitor, via an artificial intelligence engine, usage data from the one or more distributed computing systems, wherein the usage data is associated with remote access of the one or more storage locations; generate, via the artificial intelligence engine, a use score associated with the one or more storage locations; and automatically refresh the one or more storage locations based on the use score.

Abstract: An apparatus for sorting and ordering data based on filtering parameters comprises a memory operable to store a digital folder and a processor operably coupled to the memory. The processor is configured to receive a transmission comprising verification of an interaction session established between a first user and an entity and to receive file information corresponding to one or more files stored in the digital folder from an external exchange. The processor is further configured to generate a file vector comprising the one or more files of the digital folder that is sorted based on applying a selection factor to the received file information for each of the one or more files. The processor is further configured to send a transmission to a user device comprising the file vector and an indication to utilize a first file of the file vector during the interaction session.

Abstract: An entity data record includes, for each of a plurality of entities, a plurality of attribute data entries. Each attribute data entry indicates a characteristic of the entity. For each entity of the plurality of entities, an authentication score is determined indicating an extent to which the characteristics indicated by the attribute data entries for the entity are authenticated. The authentication score is stored in memory for each entity in the entity data record. A device provides a request for information about a first entity of the plurality of entities. After receiving the request, one or more attribute entries associated with the first entity and a first authentication score of the first entity are provided to the device.

Abstract: A system comprises a processor configured to receive user criteria associated with an operation and to obtain a plurality of segment candidates from a plurality of sources, each source configured to provide a segment of the operation that corresponds to a respective segment candidate obtained from said source. The processor is configured to determine a plurality of operation structure candidates for the operation. Each operation structure candidate is determined based on aggregating a respective subset of the plurality of segment candidates. The processor is configured to determine a priority for each operation structure candidate based on prioritization rules stored in memory of the system and based on the user criteria. The processor is configured to communicate an output indicating one or more of the operation structure candidates for the operation. The output is based on the priority.

Abstract: An apparatus for sorting and ordering data based on filtering parameters comprises a memory operable to store a digital folder and a processor operably coupled to the memory. The processor is configured to receive a transmission comprising verification of an interaction session established between a first user and an entity and to receive file information corresponding to one or more files stored in the digital folder from an external exchange. The processor is further configured to generate a file vector comprising the one or more files of the digital folder that is sorted based on applying a selection factor to the received file information for each of the one or more files. The processor is further configured to send a transmission to a user device comprising the file vector and an indication to utilize a first file of the file vector during the interaction session.

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: Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. Input data for a machine learning system may be analyzed to determine one or more potential biases in the input data. Based on the one or more potential biases, the input data may be grouped, and/or weights may be applied to one or more portions of the input data. The input data may be input into a machine learning algorithm, which may generate output data. Based on an evaluation of the output data, the input data may be grouped, and/or second weights may be applied to one or more portions of the input data.

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 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: Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. Input data for a machine learning system may be analyzed to determine one or more potential biases in the input data. Based on the one or more potential biases, the input data may be grouped, and/or weights may be applied to one or more portions of the input data. The input data may be input into a machine learning algorithm, which may generate output data. Based on an evaluation of the output data, the input data may be grouped, and/or second weights may be applied to one or more portions of the input data.

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.