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.

Abstract: Systems and methods for real-time account access, allowing access to accounts (such as deposit, credit, or debit accounts) through network processing infrastructures such as Electronic Funds Transfer (EFT). In some embodiments, consumers and/or merchants are able to effect transaction requests against accounts, using a pseudo-identifier or other identifier, and without the need to provide an account number or card number. In other embodiments, payment networks are able to route and process transaction requests against accounts, without having a card number or account number. In other embodiments, account processing systems are able to determine an appropriate account based on transaction requests that do not contain card numbers or account numbers.

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: A method for finding historically similar incidents is disclosed.

Abstract: A computer-implemented method for determining a signature embedding vector for information technology events. The method including: receiving a current data object representing an occurrence of an information technology event associated with a configurable item; obtaining a graph database of logical associations of the configurable item; applying a clustering algorithm to the graph database to determine a subset of graphs; extracting associated data of the subset of graphs; applying an embedding model to the extracted associated data to determine an embedding vector for each subset of graphs; aggregating the embedding vector for each subset of graphs to determine a signature embedding vector; and utilizing the signature embedding vector to perform further analysis of the current data object.

Abstract: A method for loop escape analysis includes receiving a set of executable computer instructions stored on a storage medium, and determining a number of inputs to a loop associated with a data structure, storage space that would be saved by compressing the data structure, and a size of new elements required to compress the data structure. Upon reaching an end of the loop, the method determines whether to compress the data structure based on a comparison between the size of the new elements and the saved storage space. In response to determining to compress the data structure, the method compresses the data structure.

Abstract: Systems and methods for application management are disclosed. The system may include a probe system and one or more director systems, each comprising at least one memory and one or more processors configured to execute instructions. The instructions may include monitoring an availability of an application; updating a status associated with the availability of the application in a first data store; polling the first data store in intervals to retrieve the status associated with the availability of the application; upon retrieving at least a consecutive predetermined number of statuses associated with the application being unavailable, determining the application is unavailable; determining whether at least one other director system of the one or more director systems has determined the application is unavailable; and upon determining the at least one other director system of the one or more director systems has determined the application is unavailable, triggering a failover process.

Abstract: The present disclosure relates to methods and systems for natural language processing (NLP). An example method includes techniques enabling a chatbot to join a group conversation, receive a request from a user in the group conversation, and analyze and confirm the authorization level of each member in the group. If each member of the group is authorized, then the chatbot can process the request, including categorizing, selecting a processing approach, and applying the processing approach.

Abstract: A method and system for generating predictive data related to institutional risks. An application programming interface (API) request for data includes multiple fields indicating a data type parameter, a dataset to be accessed, and operations to be performed on the dataset to generate first model output data. The first model output data is generated using a trained document data machine learning model. The operations indicated in the fields of the API request are performed. A data format associated with the requestor device is determined. A data stream usable by the requestor device is generated by formatting the data stream into a particular structure usable by the requesting device, the generated data stream based on the first model output data and at least one criterion of the API request. The formatted data stream is sent to a trained statistical data machine learning model to generate predictive data related to institutional risks.

Abstract: A data analytics system including an append-only first data store accessible to multiple clients and a second data store is disclosed. The data analytics system can be configurable to, in response to receiving first instructions from a first target system of a first client, the first target system separate from the data analytics system, create a first pipeline between the append-only first data store and the second data store. The first pipeline can be configured according to the first instructions to generate a client-specific data object and store the client-specific data object in the second data store. The data analytics system can be configurable to tear down the first pipeline upon completion of storing the client-specific data object in the second data store.

Abstract: A system for scoring user conversation satisfaction. The system comprises one or more memory devices storing instructions, and one or more processors configured to execute instructions to perform operations. The operations comprising receiving data corresponding to a conversation between the user and a third-party service provider. The operations further comprising parsing the data into conversation subsets, and analyzing each respective subset with a first model. The operations further comprising determining a user conversation satisfaction score based on the first model analyzed subset; storing, in a database, the parsed data subsets, and the determined conversation satisfaction score; and training a second model with the data stored in the database.