Abstract: Systems, computer program products, and methods are described herein for determining application degradation using advanced computational models for data analysis and automated decision-making. The present disclosure is configured to receive one or more applications, wherein the one or more applications comprise one or more access paths; update the one or more access paths, wherein updating the one or more access paths comprises reconfiguring details associated with the access paths; create, in response to updating the one or more access paths, updated access paths; determine that the one or more updated access paths experience one or more application degradations; and implement one or more degradation solutions for the one or more application degradations to an artificial intelligence model.

Abstract: Systems, computer program products, and methods are described herein for implementing a code debugger platform in a virtual environment. The system is configured to authenticate a plurality of users via an authentication portal and initialize an instance of a virtual environment for each of the plurality of users. The system is configured to extract a plurality of computer instructions, and display, in the virtual environment, a debugging platform of an integrated development environment, the debugging platform configured to receive the plurality of computer instructions and receive input from at least one of the plurality of users, and initiate a debugging protocol. The debugging protocol may include a breakpoint in at least one of the plurality of computer instructions, wherein the breakpoint is received as an input from the at least one of the plurality of users.

Abstract: A method includes receiving a data population and a plurality of constraints. The data population includes a plurality of units. Each unit includes a plurality of respective values. Each value corresponds to a respective parameter. Each constraint corresponds to a respective parameter. A holistic feature of the data population is determined. A volume is defined in the parameter space based on the plurality of constraints. For each unit of a current data population, a first vector representing a respective unit is subtracted from a second vector representing a current holistic feature to determine a third vector. For each third vector, a distance between a point defined by a respective third vector and the volume is determined. A minimum distance is determined from determined distances. The current data population is transformed into an updated data population by removing a unit that corresponds to the minimum distance from the current data population.

Abstract: Systems, computer program products, and methods are described herein for large scale data extraction and processing. The method includes receiving a transmission request. The transmission request indicates two or more accounts for which one or more account statements are to be retrieved. The method also includes selecting a first retrieval set of the two or more accounts. A first retrieval set size of the first retrieval set is based on a first expected network capacity. The method further includes causing a retrieval of one or more account statements associated with first retrieval set. The method still further includes selecting a second retrieval set of the two or more accounts. A second retrieval set size of the second retrieval set is based on a second expected network capacity. The method includes causing a retrieval of one or more account statements associated with the second retrieval set.

Abstract: A system is configured to determine multiple sub-requests from one of service requests received from a user device. The system associates each sub-request to at least one knowledge domain. The sub-requests are transmitted to a decentralized network. In turn, the decentralized network generates one or more responses associated with each knowledge domain in each sub-request. At this stage, the system relates multiple responses corresponding to the received service request to a same identifier (i.e., a common identifier) and provide the responses related to the identifier to the user device as a single service request response.

Abstract: An Augmented Reality (AR)-enabled Automated Teller Machine (ATM) receives a request to dispense cash equal to amount of an AR document. The AR document comprises an AR check. The AR-enabled ATM fetches a first AR check image from a memory. The AR-enabled ATM extracts a first set of features from the first AR check image. The AR-enabled ATM receives a second AR check image from a computing device associated with the receiver. The AR-enabled ATM extracts a second set of features from the second AR check image. The AR-enabled ATM compares the first AR check image with the second AR check image. The AR-enabled ATM determines whether the first AR check image corresponds to the second AR check image. In response to determining that the first AR check image corresponds to the second AR check image, the AR-enabled ATM dispenses cash equal to the amount.

Abstract: Various systems, methods, and computer program products are provided for dynamically generating an API. The method includes extracting metadata from a command recording of a system API. The command recording of the system includes a starting breakpoint and an ending breakpoint for one or more repetitive processes. The method also includes determining one or more API parameters for an API to be generated based on the extracted metadata. The method further includes dynamically generating the API based on the API parameters. The method still further includes causing an authentication of the credentials relating to the API via robotic process automation.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for utilizing machine learning to predict future deceitful domain names and determine preferred security responses. As such, the system allows for use of a machine learning engine to collect new domain name registration information from a plurality of sources and predict future name registrations associated with said sources. A single user may register deceitful domain names through a plurality of domain name registration systems. By collecting data from multiple servers, the system may identify data trends and generate predictions of future domain names independently of any individual server. Thus, the system may benefit a number of entities, by providing real-time data analysis that would not be obtainable by any one entity operating alone.

Abstract: A system for leveraging local/user-side resources (i.e., memory) to store Non-Fungible Tokens (NFTs) and conduct NFT-related computational processes required for generating/minting or exchanging an NFT. The local/user device is equipped with super Non-Volatile Random Access Memory (NVRAM), which operates in accordance with a resource-sharing protocol, such as Network Block Device (NBD) protocol or the like. The resource-sharing protocol is registered with the user's NFT digital wallet, which is in communication with the distributed trust computing networks and, thus links the local/user-side resources (i.e., NVRAM) with the distributed trust computing network for resource sharing capabilities.

Abstract: Systems, computer program products, and methods are described herein for secured data analysis and synthetic identity detection in a distributed ledger network. The present invention is configured to receive an event for a predetermined set of occurrences, generate a first hash packet and a second hash packet, wherein the first hash packet is generated by applying a hashing engine to a first identifier, and wherein the second hash packet is generated by applying the hashing engine to a second identifier, generate, by a distributed ledger server, a first key pair, generate, by the member of the distributed ledger network, a second key pair, encrypt a bundle using the first public key, wherein the bundle comprises the first and second hash packets, and appending the bundle to the transaction object, wherein the transaction object is distributed to the distributed ledger network.

Abstract: Artificial intelligence, in the form of machine-learning models, are implemented to dynamically detect when an online or mobile app application is being filled-out/submitted by an autonomous software program/bot (e.g., an invalid application submission), as opposed to a human (i.e., a valid application submission). Telemetry data is captured from the mobile application or web/online application that is indicative as to whether the application forms are being filled-out by a human or an autonomous software program. The telemetry data is applied to machine learning models to determine if the telemetry data results in a recognized pattern that indicates autonomous software program data entry or, conversely, human data entry. In the event that an application submission is determined to be filled-out by an autonomous software program/bot, subsequent submission and/or further processing of the application is denied.

Abstract: Systems, computer program products, and methods are described herein an automated system for restarting large scale cluster supercomputers. The present disclosure is configured to receive a request to reboot a supercomputer cluster, wherein the request comprises a sequence of reboot instructions; determine, using a data integrity engine, whether a current state of the supercomputer cluster meets reboot requirements, wherein the reboot requirements are associated with a core logic of the data integrity engine; and execute the sequence of reboot instructions in an instance where the current state of the supercomputer cluster meets the reboot requirements.

Abstract: The present invention is configured to track a resource input distribution to a first user account; receive a third party distribution request from the first user account, the third party distribution request comprising at least a portion of the resource input distribution; and authenticate a third party associated with the third party distribution request, the authentication of the third party comprising a comparison of the third party against a trusted third party distribution set, wherein, in an instance where the third party matches at least one trusted third party of the trusted third party distribution set, allow a third party distribution associated with the third party distribution request.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for convenient, secure digital data archiving and utilization across multiple communication channels. The method includes extracting one or more data input fields from a form and generating one or more user prompts to be presented to a user in order to complete at least one of the one or more entries of the one or more data input fields. The method further includes causing the transmission of at least one of the one or more user prompts to the user and receiving a prompt response from the user. The method further includes displaying to the user a completed generated form in an appropriate channel format, and provides a process for secure e-signature and cross-stream utilization of user input.

Abstract: Systems, computer program products, and methods are described herein for transformative data analysis and data modeling in a distributed network. The present invention is configured to receive sample data from a source system into a data ingestion engine, transmit, from the data ingestion engine to a data governance engine a request for metadata of the sample data, construct metadata of the sample data, determine a data transformation of the sample data based on the schema, transform the sample data via the data transformation, and store transformed sample data and corresponding metadata in a shared data store. First and second views may also be generated, where the first view is a raw data view, and the second view is a processed view of the transformed data.

Abstract: Systems, computer program products, and methods are described herein for a machine learning based system for optimized CPU utilization in data transformation. The present disclosure is configured to receive a new data segment; retrieve characteristics of the new data segment; determine, using a trained machine learning model, an encryption algorithm, and a compression algorithm for implementation on the new data segment based on at least the characteristics of the new data segment; determine, using the trained machine learning model, an order of implementation associated with the implementation of the encryption algorithm and the compression algorithm; and implement the encryption algorithm and the compression algorithm on the new data segment in the determined order of implementation.

Abstract: A system for leveraging local/user-side resources (i.e., memory) to store Non-Fungible Tokens (NFTs) and conduct NFT-related computational processes required for generating/minting or exchanging an NFT. The local/user device is equipped with super Non-Volatile Random Access Memory (NVRAM), which operates in accordance with a resource-sharing protocol, such as Network Block Device (NBD) protocol or the like. The resource-sharing protocol is registered with the user's NFT digital wallet, which is in communication with the distributed trust computing networks and, thus links the local/user-side resources (i.e., NVRAM) with the distributed trust computing network for resource sharing capabilities.

Abstract: Systems, computer program products, and methods are described herein for determining data transmission destinations across an electronic network. The method includes receiving a resource data packet to be transmitted to one of a plurality of data centers across a network. The resource data packet is associated with a user identifier that corresponds to one of one or more users. The method also includes determining a target data center for the resource data packet based on the user identifier associated with the resource data packet. One or more character of the user identifier associated with the resource data packet designates the target data center for the user associated with the user identifier of the resource data packet. The method further includes causing a transmission of the resource data packet to the target data center based on the user identifier associated with the resource data packet.

Abstract: Aspects of the disclosure relate to verifying external accounts in real-time using dynamic smart contracts. A computing platform may receive a consumer request to initiate a transaction, at an enterprise organization, with an entity associated with an account. The computing platform may use the received consumer request to generate a smart contract profile associated with the entity. The computing platform may use the smart contract profile associated with the entity to determine a trust score associated with the entity. The computing platform may gather data indicating external accounts associated with the entity. The computing platform may use the data indicating the external accounts associated with the entity to determine a confidence threshold value. The computing platform may compare the trust score associated with the entity to the confidence threshold value to verify the legitimacy of the account associated with the entity.

Abstract: Systems, computer program products, and methods are described herein for generating, extracting, classifying, and formatting object metadata using natural language processing in an electronic network. The present disclosure is configured to identify at least one input source, comprising at least one input data; parse the at least one input data; output, by an extraction layer, at least one product metadata and a term importance score associated with the input data to a metadata storage, the extraction layer comprising an NLP attribute extraction model; assemble, by an assignment layer, a corpus of text data and key phrases based on the product metadata from the extraction layer, the assignment layer comprising an NLP classification model; classify and verify, by the assignment layer, the product metadata; and output, by a generative layer, at least one generative metadata to the metadata storage, the generative layer comprising a pretrained generative NLP model.