Abstract: Disclosed are method and systems to program a server to identify the value of a fund comprising shares of multiple private entities. The server receives transaction data associated with a fund where the transaction data identifies a proportion of shares within the fund associated with each private entity, price per share of each private entity, and other relevant data. The server then executes multiple artificial intelligence models to identify comparable public entities to each private entity. The server then retrieves stock price data for each public entity and calculates a value for each private entity in real time. The server also displays a value of the fund in real time where identification of each private entity is anonymized.

Abstract: Methods and systems disclosed herein describe a server that generates an artificial intelligence model comprising a neural network corresponding to at least two sets of data points corresponding to a first independent variable and each data point within a second set of data points corresponding to a second variable dependent upon a corresponding first variable; executes a clustering algorithm to generate a plurality of clusters corresponding to at least one data point within the set of data points; generates a training dataset comprising a third set of data points corresponding to a pairwise distance between each two data points within at least one cluster; and trains the artificial intelligence model based on the training dataset, wherein when the trained artificial intelligence model is executed, the artificial intelligence model identifies a distance between the new data point and at least one data point within at least one cluster.

Abstract: Disclosed are method and systems to program a server to identify the value of a fund comprising shares of multiple private entities. The server receives transaction data associated with a fund where the transaction data identifies a proportion of shares within the fund associated with each private entity, price per share of each private entity, and other relevant data. The server then executes multiple artificial intelligence models to identify comparable public entities to each private entity. The server then retrieves stock price data for each public entity and calculates a value for each private entity in real time. The server also displays a value of the fund in real time where identification of each private entity is anonymized.

Abstract: Disclosed are method and systems to program a server to identify the value of a fund comprising shares of multiple private entities. The server receives transaction data associated with a fund where the transaction data identifies a proportion of shares within the fund associated with each private entity, price per share of each private entity, and other relevant data. The server then executes multiple artificial intelligence models to identify comparable public entities to each private entity. The server then retrieves stock price data for each public entity and calculates a value for each private entity in real time. The server also displays a value of the fund in real time where identification of each private entity is anonymized.