---
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id: "d156b04030788015826ace913ad1483d9aa45f712531d8aa484fff919d113135"
canonical_url: "https://aidr.today/d156b040?lang=en"
title: "How Condé Nast built multimodal video discovery with Amazon Bedrock"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-09-29T15:55:17.000Z"
category: "Products"
topics: ["amazon","llm"]
source_urls: ["https://aws.amazon.com/blogs/machine-learning/how-conde-nast-built-multimodal-video-discovery-with-amazon-bedrock/"]
summary: "Condé Nast's editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions. Working with the AWS Generative AI Innovation Center, they built a multimodal video discovery solution on Amazon Bedrock and Amazon OpenSearch Service that cut discovery time to under 2 minutes."
---

# How Condé Nast built multimodal video discovery with Amazon Bedrock

> [Open the canonical story](<https://aidr.today/d156b040?lang=en>)

**Published:** 2026-09-29T15:55:17.000Z
**Category:** Products
**Topics:** amazon, llm

## Summary

Condé Nast's editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions\. Working with the AWS Generative AI Innovation Center, they built a multimodal video discovery solution on Amazon Bedrock and Amazon OpenSearch Service that cut discovery time to under 2 minutes\.

## Sources

- [Story source](<https://aws.amazon.com/blogs/machine-learning/how-conde-nast-built-multimodal-video-discovery-with-amazon-bedrock/>)