This Guidance demonstrates how to design an intelligent brand system that is capable of evaluating social media posts, so you can measure brand performance, create dynamic content, and protect your brand. Amazon SageMaker provides a fully managed infrastructure and tools to build, train, and deploy machine learning (ML) models. Here, pretrained, open-source ML models are used to extract information from social media posts, including consumer sentiment and embeddings from text and images. Next, your team can create a prompt catalog with styles that adhere to your own brand guidelines. When your consumer submits a request for a social media post, the input is processed and a prompt is retrieved from the prompt catalog, with the conversation history securely stored. Finally, the custom prompt is used to generate a selection of personalized posts. Each post receives a predicted engagement rating, and your team can choose the post with the highest engagement rating to publish on social media.