Introducing multimodal retrieval for Amazon Bedrock Knowledge Bases
Amazon Bedrock Knowledge Bases now supports multimodal retrieval, enabling search and retrieval across text, images, audio, and video content.Summary
Amazon Web Services (AWS) announced the general availability of multimodal retrieval for Amazon Bedrock Knowledge Bases, expanding its capabilities to natively support video and audio alongside text and images. This new feature simplifies building Retrieval Augmented Generation (RAG) applications by allowing searches across multiple content types within a fully managed service. Previously, handling diverse content required complex custom infrastructure; now, users can ingest, index, and retrieve information from various media using a unified workflow.
Two processing approaches are available: Amazon Nova Multimodal Embeddings, which encodes content into a shared vector space for cross-modal retrieval, and Bedrock Data Automation, which converts multimedia into text for high-accuracy speech retrieval. Nova is ideal for visually-driven use cases like product catalogs, while Data Automation excels in scenarios requiring precise transcriptions, such as meetings and podcasts. The choice depends on whether visual context or speech precision is more critical.
The article details a walkthrough of setting up and testing a multimodal knowledge base for e-commerce product search, demonstrating how customers can search using text, images, or video references. It also provides instructions for cleaning up resources and links to documentation, code examples, and further information about Amazon Nova.
(Source：Plato Data Intelligence)
