Utilizing machine learning models to generate interactive digital text threads with personalized digital text reply options

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a computer system to:

• extract client features corresponding to a client device participating in an automated interactive digital text thread;
• identify a hierarchical intent architecture comprising a plurality of intent classifications organized in a plurality of hierarchical layers;
• generate, from the hierarchical intent architecture utilizing a machine learning model, a plurality of predicted client intent classifications and a plurality of intent classification probabilities from the client features;
• apply a bonus weight to a first intent classification probability of the plurality of intent classification probabilities associated with a first predicted client intent classification from a first hierarchical layer of the plurality of hierarchical layers, the bonus weight based on the first hierarchical layer;
• select the first predicted client intent classification and at least one additional predicted client intent classification from the plurality of predicted client intent classifications utilizing the plurality of intent classification probabilities;
• and
• provide, for display via the client device, at least two personalized digital text reply options corresponding to the first predicted client intent classification and the at least one additional predicted client intent classification via the automated interactive digital text thread.

A system comprising:

• at least one processor;
• and
• at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
• extract client features corresponding to a client device participating in an automated interactive digital text thread;
• identify a hierarchical intent architecture comprising a plurality of intent classifications organized in a plurality of hierarchical layers;
• generate, from the hierarchical intent architecture utilizing a machine learning model, a plurality of predicted client intent classifications and a plurality of intent classification probabilities from the client features;
• apply a bonus weight to a first intent classification probability of the plurality of intent classification probabilities associated with a first predicted client intent classification from a first hierarchical layer of the plurality of hierarchical layers, the bonus weight based on the first hierarchical layer;
• select the first predicted client intent classification and at least one additional predicted client intent classification from the plurality of predicted client intent classifications utilizing the plurality of intent classification probabilities;
• and
• provide, for display via the client device, at least two personalized digital text reply options corresponding to the first predicted client intent classification and the at least one additional predicted client intent classification via the automated interactive digital text thread.