Abstract: Techniques are provided for monitoring the integrity of a table in a dataset. The table may include one or more columns and one or more rows, in which data elements in the table are associated with a specific row and a specific column. A coverage rule set may be generated based on metadata of the table, which describes attributes of the table and the columns associated with the table. The coverage rule set includes table rules and column rules. A table fault value is generated for each table rule in the coverage rule set and a column fault value is generated for each column rule in the coverage rule set. An error is detected when a table fault value or a column fault value exceeds at least one of a corresponding table rule threshold or a corresponding column rule threshold. A notification is transmitted for error detected.

Abstract: A computer-implemented method for adaptively discretizing a position of a textual object in a document includes receiving, by a computer system, an image of the document and determining, by the computer system, an absolute position of the textual object in the image of the document. The method further includes normalizing, by the computer system, the absolute position to determine a relative position of the textual object. The method also includes calculating, by the computer system, a bin size such that at least one axis of the image is divided into a plurality of separate bins, wherein a distance between each bin along the at least one axis and its adjacent bin equals the bin size. The method includes discretizing, by the computer system, the relative position based on the bin size to determine a discretized position of the textual object; and providing, by the computer system, the discretized position and a textual content of the textual object as an input to a machine learning model.

Abstract: The Thematic Protocol and Circle Datastructure Apparatuses, Processes and Systems (“TPCD”) transforms TOP-RC search request, TOP-RC selection request inputs via TPCD components into TOP-RC search response, TOP-RC selection response, pool distribution notification request outputs. A thematic circle join request datastructure that includes a user object identifier, a portfolio object identifier associated with the user object identifier, and a thematic circle template identifier is obtained. A thematic circle object instantiated based on a thematic circle template corresponding to the thematic circle template identifier is determined. The user object identifier is added to participants datastructure. A portfolio object corresponding to the portfolio object identifier is marked as locked. A set of creation criteria associated with the thematic circle object is evaluated. The thematic circle object is activated based on a determination that the set of creation criteria has been met.

Abstract: A computerized method is provided for digitally signing a digital document related to a transaction request from a customer. The method includes receiving, by a computing device, data related to the transaction request from the customer via a web-based interface. Receipt of the transaction data initiates a request session. The method also includes recording during the request session a voice signature sample from the customer via the web-based user interface and verifying the customer for the transaction request by comparing the voice signature sample with a stored voice print of the customer. Further, a consolidated record for the transaction request is generated that includes the transaction data and the transaction result. The digital document is populated with the transaction data if the customer is verified, where the digital document is treated as being digitally signed by the customer.

Abstract: Methods and apparatuses are described for predicting user attributes using uncertainty estimate modeling. A server trains a plurality of machine learning (ML) models to predict a distribution of values for a plurality of user attributes. The server determines an uncertainty measure of the ML models for each user attribute based upon the predicted distribution of values. The server receives a request for prediction of user attributes from a client device and generates for each user attribute a first predicted distribution using one or more of the trained models. The server classifies, for each user attribute, an accuracy of the first predicted distribution based upon the uncertainty measure and provides the first predicted distribution and the accuracy for each user attribute to the client device for presentation. The server updates the first predicted value for the user attributes based upon input received from the client computing device.

Abstract: Methods and apparatuses are described for a dual screen extended reality (XR) headset device, including a first display screen viewable by a wearer of the headset device and a second display screen on an external surface of the headset device and viewable by other persons in proximity to the wearer. The headset device generates a virtual environment for display to the wearer via the first display screen. The headset device captures data associated with execution of the software application, data associated with the virtual environment being displayed to the wearer, and data associated with the wearer. The headset device displays a user interface based upon at least a portion of the captured data on the second display screen, and detects input associated with the user interface displayed on the second display screen. The headset device updates the virtual environment and access to software features based upon the detected input.

Abstract: Methods and apparatuses for optimizing performance of conversational interface applications using example forgetting include a server that retrieves training data comprising utterances each mapped to one or more known intents. The server determines a forgetting count for each utterance and selects utterances from the training data that have a forgetting count above a predetermined threshold. The server identifies whether the predicted intent associated with each utterance is accurate. The server generates updated training data comprising the selected utterances and corresponding predicted intents, and trains conversational interface applications using the updated training data. The server validates performance of the trained conversational interface applications and saves the updated training data.

Abstract: A computer implemented method is provided for assisting an agent in providing feedback to a customer during a chat session. The method includes receiving live feedback from the agent to the customer in response to an inquiry from the customer. The method also includes determining if at least one automated response is needed by comparing and matching the live feedback with at least one predefined trigger pattern. The method further includes identifying one or more trigger phrases in the live feedback if automated response is needed and determining from a conversation history database at least one automated response based on the one or more trigger phrases. The method additionally includes appending the at least one automated response to the live feedback for presentation to the customer during the chat session.

Abstract: The Blockchain Augmented Crypto Asset Valuation Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input, transfer transaction input, clawback transaction input, valuation access request datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output, transfer transaction output, clawback transaction output, valuation access response outputs. A crypto asset valuation request datastructure is obtained. A relevant crypto asset valuation transaction for a crypto asset is determined. Historical crypto asset valuation data is retrieved from a blockchain. A default valuation, a higher band valuation and a lower band valuation of the crypto asset are computed by AI crypto asset valuation engines. A valuation of the crypto asset computed by a best performing AI crypto asset valuation engine is selected.

Abstract: Techniques are provided for predicting data for precaching and/or recaching at a computer cache of a computer environment. Based on a detected login event of a user, a precache API request can be generated for a type of API data request most often utilized by the user over a predetermined time period. An API gateway may use the precache API request to obtain a corresponding precache API response from a microservice. The precache API response may be stored together at an API gateway cache. Subsequently, when information from an API call substantially matches a cache key corresponding to the precache API response, the precache API response can be provided to the user instead of obtaining the response from the microservice. Additionally, the precache API request may include a recache value that can be used to iteratively obtain up-to-date precache API responses from the microservice.

Abstract: Systems and methods are described for improving access control for a software application. A cloud platform may include a software application and an authorization sidecar. When a user attempts to access a resource, of the software application, that is associated with a first security level, the authorization sidecar performs authorization on the user based on a general authorization procedure and a specific authorization procedure. The user has access to the resource associated with the first security level after being authorized. When a user attempts to access a resource, of the software application, that is associated with a second security level, the authorization sidecar performs authorization on the user based on the general authorization procedure. The user has access to the resource associated with the second security level after being authorized.

Abstract: Methods and apparatuses are described in which unstructured computer text is analyzed for extraction of actionable insights in a computing environment. A server executes a machine learning classification model on text messages exchanged between users to classify each text message according to a disposition and a theme. The server analyzes the classified messages to generate candidate work items, each associated with software applications and skills requirements. The server filters the candidate items to remove extraneous items based upon a work item backlog or a prioritization. The server determines team members to assign to each remaining candidate item by comparing the software applications and the skills requirements for the work item to a profile for each team member. The server creates a task for each remaining candidate item, the task including the assigned team members. The server generates a notification for each task for transmission to the assigned team members.

Abstract: Automatic transaction processing failover and reconciliation in a cloud-based environment includes monitoring the processing of transaction messages to identify exception events and determining whether to initiate a failover switch based upon the identified exception events. When a failover switch is initiated, the system identifies a target cloud-based system instance for the failover switch, changes a state of the affected cloud-based system instance to prevent the affected instance from receiving transaction messages, changes a state of the target instance to receive transaction messages intended for the affected instance, and performs a replication check between databases. The system reconciles transaction messages stored in the database of the cloud-based system instance to identify anomalies.

Abstract: Methods and apparatuses are described for capturing and utilizing cross-channel context data in conversation service application communication sessions. A computing device establishes a first communication session between a first conversation service application and a first remote device. The orchestration utility detects an intent to transfer the first communication session to a second remote device. The orchestration utility captures context data generated during the first communication session. The computing device establishes a second communication session between a second conversation service application and the second remote computing device. The orchestration utility configures the second communication session based upon the context data, including synchronizing a state of the second communication session to a state of the first communication session.

Abstract: A computer-implemented method is provided for enforcing data access control policies in a hierarchical structure of a plurality of entities. The method includes receiving a data access request from a client in association with a target entity in the hierarchical structure and generating, by a security gateway, an internal access token comprising a business context that determines an identification of the target entity associated with the client and a data partition in the database corresponding to the target entity. The method also includes verifying, by a data access layer of a microservice module, the data access request against the data access control policies for the hierarchical structure using the internal access token to determine one or more permitted data partitions for access by the client. The method further includes granting the client access to the permitted data partitions if the verifying is successful.

Abstract: Methods and apparatuses are described for generating a domain-specific knowledge graph from unstructured computer text. A computing device extracts unstructured computer text associated with pairs of entities from domain-independent documents, and trains an entity relationship classification model using a domain-independent knowledge graph and the extracted text. The computing device extracts other unstructured text associated with a first domain from domain-specific documents. The computing device identifies pairs of entities contained within the text for the first domain, and executes the trained model to determine a relationship between the entities in each pair of entities identified from the text for the first domain. The computing device generates a domain-specific knowledge graph using (i) the pairs of entities identified from the text for the first domain and (ii) the relationships between the entities in each pair of entities identified from the text for the first domain.

Abstract: Methods and apparatuses are described for providing a centralized treatment selector for providing personalized cross-channel treatments for a given user. A computing device of a system establishes a first communication session with a user in a first channel. The system receives, at a treatment selector application, a user identifier and an experience context from the first channel. The system retrieves, from a treatment map store, one or more treatment maps compatible with the experience context, wherein the one or more treatment maps comprise an eligibility rule. The system obtains customer attributes for the user from an attribute store using the user identifier. One or more treatment maps and the customer attributes are provided to an eligibility rule engine that in turn identifies a set of eligible treatment maps based on the customer attributes and the eligibility rules for each of the one or more treatment maps.

Abstract: A computerized method is provided for evaluating performance of a virtual service agent. The method includes automatically generating at least one persona for impersonating a virtual customer by inputting a select demographic profile into a trained large language model (LLM). The method also includes generating (i) a list of questions for the virtual service agent for completing at least one task and (ii) a simulated context comprising at least one of mood or attitude of the virtual customer at beginning of the interaction. The method further includes enabling the virtual customer to interact with the virtual service agent to complete the task via multiple simulated dialogue turns involving the list of questions and the simulated context and evaluating the performance of the virtual service agent based on the dialogue turns.

Abstract: Techniques are provided for performing a failover for one or more streaming data applications executing in a cloud computing environment. An active application may actively communicate with a logical region of the cloud computing environment. A corresponding standby application may operate in standby mode with a different logical region. The active application and its standby application may each monitor the health of the logical region and the different logical region by polling respective health status applications. When it is determined that the logical region has failed and the different logical region is healthy, the active application may transition to standby mode and the standby application may transition to active mode to actively communicate with the different logical region. When it is determined that the logical region is healthy again, the applications may switch back to their initial modes.

Abstract: Methods and apparatuses are described for automatically provisioning and managing secure database resources in a cloud computing environment. A server provisions virtual computing resources in the cloud computing environment using resource templates and creates a database instance in each of the virtual computing resources. The server integrates the database instances and the virtual computing resources in the cloud computing environment with an identity authentication service. The server configures the database instances in two or more of the virtual computing resources to synchronize data. The server monitors each of the plurality of virtual computing resources using a monitoring service.