TRETE Inc.

In certain aspects of the disclosure, a computer-implemented method includes creating a wallet for asset tokens and creating an account for a first user upon completion of user onboarding validation. The method includes associating the account with one of an individual and a business entity. The method includes initiating one of know-your-customer (KYC) for the individual and know-your-business (KYB) for the business entity. The method includes enabling the first user to access and make transactions using the wallet.

In certain aspects of the disclosure, a computer-implemented method includes associating a token with a token identification and associating the token identification with corresponding metadata of the token. The method includes updating and logging changes in the metadata as attributes evolve. The method includes updating token value based on the changes and publishing a real-time token value with selected information about the changes.

The present invention extends to methods, systems, and computer program products for data retrieval and validation for onboarding private credit assets and deriving private credit asset characteristics. A first set of data associated with a private credit asset is collected. Identifiers associated with the first set of data are created. A second set of data associated with the private credit asset is collected based on the identifiers. The first set of data set and the second set of data are compared based on the identifiers. The first set of data is validated based on the comparison. An artificial intelligence module is trained as part of a continuous training cycle in view of validation findings. Concurrently with artificial intelligence module training, one or more characteristics of the private credit asset are derived from the first set of data.

In certain aspects of the disclosure, a computer-implemented method includes receiving a selection of a model from a plurality of models running on an ecosystem. The method includes receiving annotated datasets with correct examples and incorrect examples. The method includes training, responsive to receiving the annotated datasets, the model based on the annotated datasets. The method includes running the model based on the training. The method includes receiving a feedback score of results from running the model based on the annotated datasets. The method includes iteratively running, until the feedback score is above a predetermined threshold, the model responsive to user evaluation of the results from running the model based on the annotated datasets. The method includes publishing the model responsive to the feedback score being above the predetermined threshold.

Aspects of the invention include ingesting capitalization data defining capitalization of a investment fund asset. A model determines a share price. The value of the investment fund asset is fractionalized into a plurality of digital shares, each digital share having a value of the share price and represented by a token. A capitalization table tracks relationships between the plurality of digital shares and the private credit asset using metadata incorporated in each digital share tying the digital share back to the private credit asset. A buy/sell transaction for a portion of the investment fund asset is performed based on the share price, including transferring at least one token to a digital wallet of a new investor in the investment fund asset.

The present invention extends to methods, systems, and computer program products for data retrieval and validation for asset onboarding and deriving asset characteristics. A first set of data associated with an asset is collected. Identifiers associated with the first set of data are created. A second set of data associated with the asset is collected based on the identifiers. The first set of data set and the second set of data are compared based on the identifiers. The first set of data is validated based on the comparison. An artificial intelligence module is trained as part of a continuous training cycle in view of validation findings. Concurrently with artificial intelligence module training, one or more characteristics of the asset are derived from the first set of data.

In certain aspects of the disclosure, a computer-implemented method includes creating a wallet for asset tokens and creating an account for a first user upon completion of user onboarding validation. The method includes associating the account with one of an individual and a business entity. The method includes initiating one of know-your-customer (KYC) for the individual and know-your-business (KYB) for the business entity. The method includes enabling the first user to access and make transactions using the wallet.

A system and method for determining whether to throttle or kill a sale of shares of an asset using a settlement approval service, including querying, by a settlement approval service, a transfer agent whether a buyer of shares of an asset is approved; querying, by the settlement approval service, a transfer agent whether a seller of shares of the asset is approved; based on the buyer and the seller being approved, querying, by the settlement approval service, the transfer agent as to whether the shares offered for sale are valid; and based on determining, by the settlement approval service, that the shares are valid, approving, by the settlement approval service, the sale of shares of the asset.

In certain aspects of the disclosure, a computer-implemented method includes creating a wallet for asset tokens and creating an account for a first user upon completion of user onboarding validation. The method includes associating the account with one of an individual and a business entity. The method includes initiating one of know-your-customer (KYC) for the individual and know-your-business (KYB) for the business entity. The method includes enabling the first user to access and make transactions using the wallet.

In certain aspects, a computer-implemented method includes monitoring data entries written on a database. The computer-implemented method includes recording at least part of the data entries written on the database to a blockchain.