NEWS · COMPANIES · #1204
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.
KEY POINTS
- 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.
- This demonstrates a practical multimodal production deployment that uses speciality embeddings and managed model serving to unlock large archived video libraries and cut editorial discovery time dramatically.
WHY IT MATTERS
This demonstrates a practical multimodal production deployment that uses speciality embeddings and managed model serving to unlock large archived video libraries and cut editorial discovery time dramatically.