Discover how to revolutionize AI storage economics through this AWS re:Invent 2025 conference session exploring Amazon S3 Vectors' native support for storing, retrieving, and querying vectors directly in S3. Learn how this innovative feature complements high-performance vector databases while dramatically reducing storage and querying costs by up to 90%. Explore integration strategies with Amazon Bedrock Knowledge Bases and OpenSearch Service to enable cost-effective retrieval-augmented generation (RAG) and semantic search capabilities with reduced complexity. Examine architecture design principles, performance considerations, and implementation approaches for scalable AI agent memory and search functionality. Gain insights from March Networks, a real-world customer case study, demonstrating how S3 Vectors transforms operations and powers intelligent video search capabilities. Master the technical aspects of leveraging S3 Vectors to optimize AI workloads while maintaining performance and scalability requirements in enterprise environments.