Real time model cascades and derived feature hierarchy

Abstract

Certain aspects of the present disclosure provide techniques for a feature management platform to asynchronously implement an ensemble of machine learning models (or AI/ML models). The feature management platform can transmit feature data presently available on the feature queue (e.g., published on the feature queue or retrieved from a persistent data layer). The feature management platform can transmit the feature data to a first group of the machine learning models, capable of inputting the presently available feature data to generate predictions. The predictions can be transmitted back to the feature queue to consume—as well as store in the persistent data layer. The predictions, as well as any newly generated feature data, can be provided to the remaining machine learning models in the ensemble. The prediction of the ensemble can then provided to a consumer (e.g., an organization).

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