From Prompt to Production: Automating Brand-Safe Marketing Imagery with Text-to-Image Models

Text-to-image models have made significant strides, producing impressive results in generating images from textual descriptions. However, creating a scalable pipeline for deploying these models in production remains a challenge. Achieving the right balance between automation and human feedback is critical to maintain both scale and quality. While automation can handle large volumes, human oversight is still an essential component to ensure that the generated images meet the desired standards and are align with the creative vision. This paper presents a new agentic workflow that offers a fully automated, scalable solution for generating advertisement images using text-to-image models. The proposed system maintains the quality and fidelity of images, while also introducing sufficient creative variation to adhere to marketing guidelines. By streamlining this process, we ensure a seamless blend of efficiency and human oversight.On average models integrated in our workflow achieve an average of 30.77\% increase in attaining the marketing object fidelity using DINOV2 and an average of 52.00\% increase human preference over the generated outcome.