Video and image search in Amazon Bedrock Knowledge Base using Marengo 3.0 | Amazon Web Services

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Today we’re announcing the general availability of TwelveLabs Marengo Embed 3.0 as an embedding model in Amazon Bedrock Knowledge Bases.

Video and media assets remain largely unsearchable by meaning. Teams in media, sports analytics, education, security, and retail need to find specific moments in hours of footage using natural language. An example query is “show me the penalty kick in the second half”. Building semantic search over video today requires stitching together a complex pipeline of transcription services, frame extraction pipelines, embedding models, vector databases, and synchronization logic.

Amazon Bedrock Knowledge Bases is a fully managed Retrieval Augmented Generation (RAG) service that handles storage, ingestion, embedding, re-ranking, and retrieval. It supports video files (MP4, MOV), images (JPEG, PNG), and audio tracks, with native connectors for Amazon Simple Storage Service (Amazon S3), SharePoint, Confluence, and more.

Marengo Embed 3.0 is a multimodal embedding model that jointly encodes video, audio, images, and...

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