Systems and methods for deterministic ai/ml models

A non-transitory computer-readable medium, storing a plurality of processor-executable instructions to:

• maintain a first set of artificial intelligence/machine learning ("AI/ML") models, wherein a particular AI/ML model of the first set of AI/ML models includes:
• an association between a particular set of attributes and a particular input type, and
• an association between the particular input type and a particular set of output tuning parameters;
• generate a set of outputs using a second set of AI/ML models;
• select a subset of outputs, from the set of outputs, based on the particular set of output tuning parameters;
• associate the selected subset of outputs with the particular AI/ML model;
• compare a set of attributes, associated with a received input, with the particular set of attributes included in the particular AI/ML model;
• determine, based on the set of attributes, that the received input is associated with the particular input type with which the particular AI/ML model is associated;
• identify the subset of outputs with which the particular AI/ML model is associated;
• and
• provide a response to the received input, wherein the response is based on the identified subset of outputs with which the particular AI/ML model is associated.

A method, comprising:

• maintaining a first set of artificial intelligence/machine learning ("AI/ML") models, wherein a particular AI/ML model of the first set of AI/ML models includes:
• an association between a particular set of attributes and a particular input type, and
• an association between the particular input type and a particular set of output tuning parameters;
• generating a set of outputs using a second set of AI/ML models;
• selecting a subset of outputs, from the set of outputs, based on the particular set of output tuning parameters;
• associating the selected subset of outputs with the particular AI/ML model;
• comparing a set of attributes, associated with a received input, with the particular set of attributes included in the particular AI/ML model;
• determining, based on the set of attributes, that the received input is associated with the particular input type with which the particular AI/ML model is associated;
• identifying the subset of outputs with which the particular AI/ML model is associated;
• and
• providing a response to the received input, wherein the response is based on the identified subset of outputs with which the particular AI/ML model is associated.