Abstract: Methods, apparatuses, system, devices, and computer program products for automating asset trading based on composite AI-generated data is disclosed that includes a controller receiving from a user, investor-specified risk parameters and portfolio criteria for a portfolio; retrieving from an entity database, composite AI-generated data; based on scoring preferences of the user, utilizing, the scoring data to select from the plurality of entity profiles, a first set of entity profiles corresponding to candidate assets that satisfy the investor-specified risk parameters and the portfolio criteria; for each asset associated with an entity profile in the first set of entity profiles, determining based on the investor-specified risk parameters and the portfolio criteria, an asset allocation for the portfolio; and transmitting instructions to one or more trade fulfillment backends to perform one or more trades in accordance with the determined asset allocations.

Abstract: Methods, apparatuses, system, devices, and computer program products for user interaction within a data analysis system are disclosed that include a controller receiving user queries via a user interface; in response to receiving the user queries, performing data operations on the entity profiles in the database, wherein the data operations include at least one of: sorting the entity profiles based on composite scores associated with the entity profiles; searching the entity profiles based on the specified one or more parameters in the user queries; or combining the entity profiles by correlating data from multiple profiles based on the composite scores of the entity profiles, to generate an aggregated result set; generating a response to the user queries; and outputting, by the controller, the response to the user interface for display to the user.

Abstract: Methods, apparatuses, system, devices, and computer program products for evaluating tokenized entities using an AI model are disclosed. In a particular embodiment, a controller generates a profile for a digitally traded asset and generates, using an AI model, one or more entity profiles corresponding respectively to one or more entities that back the digitally traded asset. The controller stores the profile for a digitally traded asset and the one or more entity profiles in a database comprising a plurality of entity profiles corresponding to different entities. The controller augments the AI model based on the plurality of entity profiles. The controller generates using the augmented AI model, a rating for the digitally traded asset based on an AI-driven analysis of the plurality of entity profiles.

Abstract: Methods, apparatuses, system, devices, and computer program products for providing access to composite AI-generated data is disclosed that includes a controller of an API server, receiving from a user system, an API call that specifies a request to perform a data operation on an entity database; interpreting the API call to identify the data operation and parameters related to the scoring data; executing the data operation on the entity database according to the specified parameters; generating a response to the API call; and transmitting the response to the user system.

Abstract: Methods, apparatuses, system, devices, and computer program products for customized integrated entity analysis using an AI model are disclosed. In a particular embodiment, customized AI-powered analysis of an entity includes a controller creating a custom attribute for a user to analyze an entity and processing a first set of external data related to the created custom attribute and the entity including structured data and unstructured data retrieved from a first set of structured data sources and unstructured data sources. In this embodiment, the controller augments an AI model using the processed first set of external data and generates using the augmented AI model, one or more metrics for assessing the custom attribute in relation to the entity. The controller also presents to the user the generated one or more metrics for assessing the custom attribute in relation to the entity.