Dynamic product design via generative architectures

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:

• generating, via one or more machine learning models based at least on information associated with a user, candidate product data comprising (i) one or more candidate customized product suggestions, (ii) one or more product images corresponding to the one or more candidate customized product suggestions, and (iii) one or more product descriptions for the one or more candidate customized product suggestions;
• determining, via one or more additional machine learning models based on the candidate product data, at least a subset of the one or more candidate customized product suggestions that meets a set of evaluation criteria;
• and
• outputting the at least the subset of the one or more candidate customized product suggestions to the user.

A system comprising:

• one or more memories storing instructions;
• and
• one or more processors for executing the instructions to:
• generate, via one or more machine learning models based at least on information associated with a user, candidate product data comprising (i) one or more candidate customized product suggestions, (ii) one or more product images corresponding to the one or more candidate customized product suggestions, and (iii) one or more product descriptions for the one or more candidate customized product suggestions;
• determine, via one or more additional machine learning models based on the candidate product data, at least a subset of the one or more candidate customized product suggestions that meets a set of evaluation criteria;
• and
• output the at least the subset of the one or more candidate customized product suggestions to the user.