Build an AI-powered product tagging system with Amazon SageMaker serverless model customization
Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) on Amazon SageMaker serverless model customization, then deploy it for asynchronous inference to build a cost-efficient product tagging system.
We haven't written up this one. AWS Machine Learning has the full story — the link below goes straight to it.
