Artificial intelligence agent for personalized communication with users of an online system

A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising:

• receiving, via a network and from an online platform, information about a set of candidate items;
• accessing a conversion prediction model of a computer system, wherein the conversion prediction model is a machine-learning model trained to predict a likelihood of a user of the computer system converting on each candidate item from the set of candidate items;
• receiving, at an agent management module and via the network, images of a set of items from a device associated with the user in real time;
• identifying, by the agent management module and using the images of the set of items, information about expiration dates of the set of items;
• retrieving. from a database of the computer system and using an identifier of the user, information about the user including information about past conversions conducted by the user and information about one or more features for the user, each of the one or more features related to a preference of the user for a type of items;
• retrieving, from the database and using an identifier of each candidate item from the set of candidate items, information about each candidate item including information about a type of each candidate item;
• applying the conversion prediction model to the information about the user, the information about expiration dates of the set of items, and the information about each candidate item from the set of candidate items to generate a score that is indicative of the likelihood of the user converting on each candidate item from the set of candidate items;
• selecting, using the score for each candidate item, an item from the set of candidate items;
• generating a prompt for input into a generative model of the computer system, the prompt including information about the item, one or more features of the user including the information about expiration dates of the set of items, content of a current order placed by the user, and one or more inputs from the online platform;
• requesting the generative model to generate, based on the prompt input into the generative model, an output including a pitch for the item;
• generating, using the output, a user interface signal;
• and
• sending, via the network, the user interface signal to a device associated with the user, wherein sending the user interface signal causes the device associated with the user to display a user interface with a description of the item, provide the pitch for the item, and display a user interface element for use by the user to add the item to the current order.

A computer system comprising:

• a processor;
• and
• a non-transitory computer-readable storage medium having instructions that, when executed by the processor, cause the computer system to perform steps comprising:
• receiving, via a network and from an online platform, information about a set of candidate items;
• accessing a conversion prediction model of the computer system, wherein the conversion prediction model is a machine-learning model trained to predict a likelihood of a user of the computer system converting on each candidate item from the set of candidate items;
• receiving, at an agent management module and via the network, images of a set of items from a device associated with the user in real time;
• identifying, by the agent management module and using the images of the set of items, information about expiration dates of the set of items;
• retrieving, from a database of the computer system and using an identifier of the user, information about the user including information about past conversions conducted by the user and information about one or more features for the user, each of the one or more features related to a preference of the user for a type of items;
• retrieving, from the database and using an identifier of each candidate item from the set of candidate items, information about each candidate item including information about a type of each candidate item;
• applying the conversion prediction model to the information about the user, the information about expiration dates of the set of items, and the information about each candidate item from the set of candidate items to generate a score that is indicative of the likelihood of the user converting on each candidate item from the set of candidate items;
• selecting, using the score for each candidate item, an item from the set of candidate items;
• generating a prompt for input into a generative model of the computer system, the prompt including information about the item, one or more features of the user including the information about expiration dates of the set of items, content of a current order placed by the user, and one or more inputs from the online platform;
• requesting the generative model to generate, based on the prompt input into the generative model, an output including a pitch for the item;
• generating, using the output, a user interface signal;
• and
• sending, via the network, the user interface signal to a device associated with the user, wherein sending the user interface signal causes the device associated with the user to display a user interface with a description of the item, provide the pitch for the item, and display a user interface element for use by the user to add the item to the current order.