How uniopen customized Amazon Nova to their retail moderation policies for production deployment

What happened
uniopen is a digital communication and membership platform launched by Taiwan’s Uni-President Enterprises Group, connecting customers to ecommerce, membership benefits, and other retail experiences across web, tablet, and mobile channels. See how uniopen, a retail platform from Taiwan's Uni-President Enterprises Group, adapted Amazon Nova 2 Lite to its content-moderation policies using supervised fine-tuning (further training of an existing model for a narrower job) in Amazon SageMaker AI and prompt optimization.
Business-relevant evaluation and release gates kept quality in check. Across those channels, uniopen applies a moderation policy that classifies each interaction along two axes.
The first is what behavior occurred (nine categories), and the second is what subject the behavior refers to (brand, other, or forbidden). Both must be correct for a moderation decision to be useful, and both are specific to uniopen’s business rather than something a general-purpose model can be expected to learn out of the box.
Sources & evidence
- AWS Machine Learning Blog Primary / official
How uniopen customized Amazon Nova to their retail moderation policies for production deployment ↗
https://aws.amazon.com/blogs/machine-learning/how-uniopen-customized-amazon-nova-to-their-retail-moderation-policies-for-production-deployment/