Systems and methods for performance modeling

A system, comprising:

• a data processing system comprising one or more processing circuits configured to:
• receive an input corresponding to an entity to model;
• responsive to the input, access, via one or more data channels, one or more data sources corresponding to the entity;
• identify, based on the accessing of the one or more data sources via one or more data channels, a modeling dataset;
• generate, for one or more artificial intelligence (AI) models, a prompt based on (i) the modeling dataset, (ii) entity data of the entity, and (iii) one or more performance benchmarks, wherein generating the prompt comprises mapping one or more associations corresponding to the modeling dataset and one or more performance parameters of one or more performance indicators;
• apply the modeling dataset and the prompt as input to the one or more AI models to cause the one or more AI models to generate an output regarding one or more performance metrics of the entity to correspond to the one or more performance parameters, the output comprising one or more performance product recommendations based on the one or more performance metrics;
• generate, using a performance indicator framework, the one or more performance indicators of the entity based on the one or more performance metrics;
• and
• transmit, to a user computing system, the one or more performance indicators and the one or more performance product recommendations, the one or more performance indicators comprises one or more AI responses annotating the one or more performance indicators for review.

A method for modeling performance of entities using one or more artificial intelligence (AI) models, comprising:

• receiving, by one or more processing circuits, an input corresponding to an entity to model;
• responsive to the input, accessing, by the one or more processing circuits via one or more data channels, one or more data sources corresponding to the entity;
• identifying, by the one or more processing circuits based on the accessing of the one or more data sources via the one or more data channels, a modeling dataset;
• applying, by the one or more processing circuits, the (i) the modeling dataset, (ii) entity data of the entity, and (iii) one or more performance benchmarks as input to one or more AI models to cause one or more AI models to generate an output regarding one or more performance metrics of the entity to correspond to one or more performance parameters;
• generating, by the one or more processing circuits using a performance indicator framework, one or more performance indicators of the entity based on the one or more performance metrics;
• and
• transmitting, by the one or more processing circuits to a user computing system, the one or more performance indicators comprising one or more AI responses annotating the one or more performance indicators for review.