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

This article demonstrates how Amazon Nova Multimodal Embeddings enables semantic search for creative asset discovery in gaming, addressing the challenge of managing massive video libraries for advertising campaigns.

• Nova Multimodal Embeddings achieved 96.7% recall and 73.3% high-precision recall on 170 gaming assets
• Unified vector space supports text, images, video, and audio for cross-modal retrieval
• Automatic video segmentation breaks content into 1-30 second segments for precise retrieval
• Flexible embedding dimensions (256, 384, 1024, 3072) balance accuracy and cost
• Serverless architecture using Lambda, OpenSearch, S3, and API Gateway scales automatically
• Strong cross-language performance with minimal degradation across multiple languages
• Replaces manual tagging and keyword-based search with semantic understanding
• Asynchronous processing handles large files without API timeouts

Nova Multimodal Embeddings transforms creative asset management by enabling intuitive semantic search across diverse media types without manual tagging, significantly improving discovery efficiency for gaming studios managing thousands of video assets.