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TwelveLabs

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EVENT TIMELINE

3

MODELS · 1 SOURCE · AWS Machine Learning

TwelveLabs' Pegasus 1.5 is now available on Amazon Bedrock

TwelveLabs has made Pegasus 1.5 — a video language model that converts long-form video into structured, timestamped JSON metadata — available on Amazon Bedrock. New features include full-video segmentation, multimodal prompting with reference images, on-the-fly processing with no pre-indexing, and extended single-request analysis up to two hours; calls are made via the bedrock-runtime InvokeModel or InvokeModelWithResponseStream APIs and can process video from an S3 URI or a base64 string while keeping data within the AWS boundary.

6.0

COMPANIES · 1 SOURCE · AWS Machine Learning

Condé Nast builds multimodal video discovery with Amazon Bedrock and TwelveLabs Marengo

Condé Nast partnered with the AWS Generative AI Innovation Center to build a multimodal video discovery system using TwelveLabs' Marengo embeddings via Amazon Bedrock and indexed in Amazon OpenSearch Service. The decoupled architecture — embedding generation on Bedrock and low-latency k-NN search on OpenSearch — enables intent-based, image-driven, and timestamped searches across transcripts, audio, and visuals, reducing average discovery time from ~250 minutes to under 2 minutes per task.

6.0

MODELS · 1 SOURCE · AWS Machine Learning

TwelveLabs' Marengo Embed 3.0 added to Amazon Bedrock Knowledge Bases for video, image and audio search

TwelveLabs' Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, enabling fully managed natural-language semantic search over video, image and audio content. AWS Machine Learning published a walkthrough showing how to build a Bedrock knowledge base powered by Marengo 3.0 and run semantic queries against media.

6.0