Abstract: The disclosed embodiments include systems and methods for tracing data. A disclosed tracing system can receive a request to access original data. The request can be associated with access request metadata. The tracing system can generate a tracer based at least in part on the access request metadata and can generate an altered version of the first data by inserting the tracer into the original data. The tracing system can update a database or log file associated with the first data to include association information based on the access request metadata. The tracing system can then provide the altered version of the first data in response to the request.

Abstract: A computer implemented method for performing a facial biometric authentication is disclosed. The method includes: storing a validation image of a user; receiving a vector representation of a raw image of the user, wherein the raw image was processed and a machine learning model was applied to the processed raw image to determine the vector representation of features of the processed raw image; determining a distance between the vector representation of the raw image and a vector representation of the validation image, wherein the vector representation of the validation image was determined by a same type of machine learning model applied to processed raw images; and outputting an approval or rejection of a biometric authentication based on the determined distance.

Abstract: A data analytics system is configured to perform operations comprising creating at least one data storage, creating a metadata store separate from the at least one data storage, creating a flow storage, and configuring a flow service using first received instructions. The flow service is configured to obtain a first flow from the flow storage, obtain metadata from the metadata storage, and execute the flow. The flow execution can include obtaining input data from the at least one data storage, generating output data at least in part by validating, transforming, and serializing the input data using the metadata, and generating additional metadata describing the output data. The flow execution can further include providing the output data for storage in the at least one data storage and providing the additional metadata for storage in the metadata storage.

Abstract: A method for generating a user-designed image for applying to a payment card includes receiving at least one image criterion of a target image associated with a user associated with a payment card, receiving a plurality of preliminary images generated by an artificial intelligence engine based on the at least one image criterion, receiving an image selection by the user, the image selection including an image selected from the plurality of preliminary images, displaying on a user interface the selected image superimposed on a virtual representation of the payment card, and setting at least one dimensional parameter of the selected image to suit a size of the payment card.

Abstract: A data analytics system is disclosed that is configured to perform operations including receiving input data at a first storage location and configuring a flow service to execute a flow. The flow execution can include creating a pipeline using the flow and metadata associated with the flow, the pipeline configured to perform a data transformation specified in the flow. The flow execution can further include determining a tenancy associated with the input data using the flow. The flow execution can also include generating, using the pipeline, output data from the input data and storing, using the pipeline, the output data in a second storage location associated with the tenancy.

Abstract: Systems, devices, methods, and computer readable media for determining potential issues with a software upgrade are disclosed. In one implementation, the disclosed system includes at least one processor and at least one non-transitory memory storing instructions to perform operations when executed by the at least one processor. The operations include training a machine learning model on historic trouble ticket data; receiving data relating to a planned software upgrade; providing the received data to the trained machine learning model, wherein the trained machine learning model generates a tag value; calculating a risk score based on the tag value; and determining a client-specific action to be performed relating to the planned software upgrade and based on the risk score.

Abstract: A system for processing a transaction at a point of engagement comprising receiving an input interaction from a user, communicating with a plurality of identity providers to validate an identity of the user, communicating with a plurality of payment providers to collect available payment or funding options, mapping the input interaction to an output interaction, and performing a transaction that reflects the mapping of the input interaction to the output interaction.

Abstract: A computer-implemented method for tracking a data object in a data pipeline. The method may include receiving a data object from an data source; assigning a record number to the data object; determining a first tracking stamp for the data object; broadcasting the first tracking stamp to a channel of a record tracking queue; initiating a record in the record tracking queue for the data object, the record including the record number, a station array, a station code, and a timestamp array, wherein the first tracking stamp updates the station array, station code, and timestamp array; transferring the data object to a second component; determining a second tracking stamp for the data object, the second tracking stamp including the record number; broadcasting the second tracking stamp to the channel; and updating the record with the second tracking stamp to indicate that the data object was received by the second component.

Abstract: Systems and methods are disclosed for generating blockchain-based dynamic non-fungible tokens (NFTs) for user authentication. The method includes receiving a request from a mobile device associated with a user. Capturing, via one or more sensors, images and/or videos of the user and/or identification data associated with the user. Processing the images and/or the videos to detect biometric data unique to the user. Encoding the detected biometric data for generating the dynamic NFTs. Storing the dynamic NFTs on a transaction block of a distributed blockchain, wherein the dynamic NFTs are associated with a programmatically defined smart contract written to the distributed blockchain. Transmitting the dynamic NFTs to a plurality of service providers for authenticating the user.

Abstract: Systems and methods are disclosed for generating blockchain-based dynamic non-fungible tokens (NFTs) for user authentication. The method includes receiving a request from a mobile device associated with a user. Capturing, via one or more sensors, images and/or videos of the user and/or identification data associated with the user. Processing the images and/or the videos to detect biometric data unique to the user. Encoding the detected biometric data for generating the dynamic NFTs. Storing the dynamic NFTs on a transaction block of a distributed blockchain, wherein the dynamic NFTs are associated with a programmatically defined smart contract written to the distributed blockchain. Transmitting the dynamic NFTs to a plurality of service providers for authenticating the user.

Abstract: The disclosed embodiments include a method for providing cloud computing semantic layer. The method comprises receiving a description of a semantic layer operation performed by a semantic layer, the description including multiple implementations of the semantic layer operation, the multiple implementations differing in at least one of cloud operations used or cloud computing platforms used; receiving a request that indicates performance of the semantic layer operation; receiving first resource usage indications corresponding to the cloud operations, wherein the first resource usage indications comprise direct or indirect indications of least one of a storage amount, a compute amount, a number of transactions, a bandwidth, a number of application programming interface calls, or an application or database type associated with each of the cloud operations; selecting a first one of the multiple implementations; and communicating with the first one of the cloud providers to perform the semantic layer operation.

Abstract: Embodiments of the present disclosure relate to methods and systems for configuration management in the development and deployment of computer application products. A configuration copy tool (CCT) facilitates accurate, automated, and repeatable movement of definition-level configuration data across multiple environments, including development, testing, integration, and production. In several embodiments, a user searches for and selects a CCT instance for a corresponding tenant, selects a configuration component from a source system, retrieves or downloads details of a previous extraction, and extracts configuration data from a previously extracted time to a current execution time. The system may perform full extracts or delta extracts and may selectively include only approved, active, or passive configuration items while excluding cancelled or in-progress items.

Abstract: Systems and methods for troubleshooting issues based on historical resolution data. In one implementation, the disclosed system includes at least one processor and at least one non-transitory memory containing software code configured to cause the processor to: receive source data from a plurality of data sources; extract a plurality of keywords from the source data; store the plurality of keywords in a database; receive a natural-language user issue input from a chatbot; determine whether the received user input matches the keywords in the database, wherein a comparison result is inputted into a trained model; input the user issue input into the trained model; in response to the determining, transmit the resolution from the trained model to the chatbot.

Abstract: A system is disclosed for automatically estimating the time required to complete software development tasks using project and time data. The system extracts feature details from project management tools and retrieves corresponding time-tracking information. A large language model processes this information to generate machine-learning features, which are used to train a neural network that predicts development effort. The system may further fine-tune the language model using historical feature data and associated work items to improve accuracy. A user interface allows entry of a feature identifier, generation of predicted work items, and display of estimated hours, which may be updated based on team productivity or user input. The system also supports deploying the trained model across distributed computing nodes, integrating multiple estimation APIs, and retraining the model using recent sprint data or updated feature information.

Abstract: A system and method for version-controlled configurations promotion is disclosed. More particularly, a system to implement version control for configuration as code (CaC) for improved accuracy and speed, and reduction in human error in the creation of computer application products across multiple developers is disclosed. More particularly, a system to generate and use JavaScript object notation (JSON) for each of a plurality of entities in a product is disclosed. More particularly, a system for changing the JSON configurations and managing the changes as they are promoted up to the product through an improved version control workflow is disclosed.

Abstract: Systems and methods are disclosed for a pre-note process in an online communication. The method includes receiving a request from an access device. The request is processed to determine a request type and a request content. The pre-note process is initiated for the request based on the request type and the request content, wherein a pre-note includes access device information, a reference identification, and/or item details for categorization. The one or more items associated with the request are categorized into one or more categories based on the pre-note. The request is executed based on one or more categories.

Abstract: Methods and systems for regulating generation of units according to at least one encryption technique associated with a blockchain are disclosed. In some embodiments, a system includes a communication device configured to communicate with a computing device executing an application and a processor configured to execute instructions to perform operations. The operations include receiving transaction information describing a transaction; based on the transaction, determining product awards for at least one product awards program for the transaction; using the blockchain, determining a real-time conversion rate for the transaction, where the real-time conversion rate is regulated by the at least one encryption technique; based on the real-time conversion rate, converting the product awards to units; and entering into the blockchain encrypted data associated with the transaction, wherein the encrypted data is encrypted according to the at least one encryption technique.

Abstract: A method for implementing a multi-agent system to generate a response to a user query. The method may include receiving a query from a user; generating, by a response agent, an initial response to the query; evaluating, by a critic agent, a quality of the initial response, wherein evaluating the quality includes assigning, by the critic agent, a score to the initial response based on the quality; evaluating, by an ethical agent, ethical concerns in the initial response, wherein evaluating the ethical concerns includes determining, by the ethical agent, an evaluation report; determining, by a decision agent, that the initial response does not meet quality and ethical standards threshold values, instructing the response agent to improve the response.

Abstract: The present disclosure provides systems and methods for computerized methods and systems for processing transaction disputes and processing transactions associated with compromised accounts. According to one exemplary method, a server receives, from a user device, an instruction for disputing a transaction associated with a user account. The server can initiate, based on a record of the transaction, a dispute investigation, and issue provisional credit to the user account for the transaction. Based on a transaction history associated with the user account, the server can determine a plurality of expected transactions associated with the user account and cause the determined expected transactions to be displayed on the user device. After receiving a transaction authorization for at least one of the plurality of expected transactions, the server can process payments for the at least one of the plurality of expected transactions, and generate a notification indicating a status of the dispute investigation.

Abstract: Systems, devices, methods, and computer readable media for determining potential issues with a software upgrade are disclosed. In one implementation, the disclosed system includes at least one processor and at least one non-transitory memory storing instructions to perform operations when executed by the at least one processor. The operations include training a machine learning model on historic trouble ticket data; receiving data relating to a planned software upgrade; providing the received data to the trained machine learning model, wherein the trained machine learning model generates a tag value; calculating a risk score based on the tag value; and determining a client-specific action to be performed relating to the planned software upgrade and based on the risk score.