Scale creative asset discovery with Amazon Nova Multimodal Embeddings unified vector search

Gaming companies face an unprecedented challenge in managing their advertising creative assets. Modern gaming companies produce thousands of video advertisements for A/B testing campaigns, with some organizations maintaining libraries with more than 100,000 video assets that grow by thousands of assets monthly. These assets are critical for user acquisition campaigns, where finding the right creative asset can make the difference between a successful launch and a costly failure.

In this post, we describe how you can use Amazon Nova Multimodal Embeddings to retrieve specific video segments. We also review a real-world use case in which Nova Multimodal Embeddings achieved a recall success rate of 96.7% and a high-precision recall of 73.3% (returning the target content in the top two results) when tested against a library of 170 gaming creative assets. The model also demonstrates strong cross-language capabilities with minimal performance degradation across multiple languages.

Traditional methods ...