Entertainment Venue Case Study

Overview: Bringing a World-Class Media Library into the AI Era

When one of the world’s most prominent entertainment venues needed a smarter way to manage, search, and unlock value from its vast media asset library, they turned to Nomad Media, an AWS Partner with expertise in cloud-native media asset management platforms.

The Client is a major media and entertainment corporation operating one of the most iconic live event venues in New York City. Their portfolio spans professional sports teams, a flagship recurring live music event brand, and a range of other high-profile entertainment properties, each generating a continuous flow of valuable media content.

Having already modernized their legacy media workflow with the Nomad Media Platform and Amazon Web Services, the Client was ready to go further. The next step: harnessing generative AI and intelligent video search to surface the full value of their growing media archive.

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The Challenge: Managing a Growing Media Content Library at Scale

Like many entertainment organizations with a long, rich history, the Client had accumulated decades of event recordings. This was a treasure trove of historic broadcast content, much of it never re-released after its original air date. While the digitization of this library was already underway through their Nomad Media deployment, the challenge wasn’t storage. It was discoverability.

With metadata generation being rolled out in stages to manage budget, a significant portion of the asset library remained difficult to find by content. Editors, producers, and marketing teams faced a common pain point: how do you find the right clip in a vast media archive without watching hours of footage? And how do you do it quickly enough to support promo reels, advertising campaigns, performer awareness content, and live event marketing?

The Client needed a way to centralize media asset discovery, improve media discoverability across their library, and make intelligent video search a practical part of everyday production workflows, not a technical afterthought.

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Deploying an AI-Powered Media Asset Management Solution

Nomad Media approached this engagement with a flexible, phased deployment plan tailored to the Client’s environment. As an AWS Partner, Nomad Media brought both platform expertise and hands-on AWS integration experience to the table, helping the Client assess expected search improvements, plan a trial run on a test asset lot, and budget accurately for AWS service usage before any production rollout.

The Retrieval-Augmented Generation (RAG) feature was deployed via an upgrade to the Client’s existing Nomad Media installation. Activation is handled through a customer-accessible admin control, giving the Client full ownership over when the feature goes live and the system enters production mode. This made the transition smooth and low-risk.

Because the RAG feature operates under the hood, automatically enriching media with AI-generated metadata as content is ingested, end-user training was minimal. Nomad Media trained a designated Client admin in a train-the-trainer model, keeping disruption to existing workflows low while ensuring the team was fully equipped to take advantage of the platform’s new capabilities.

The deployment was completed on a short timeline. From that point forward, the Client’s editors, producers, and executives gained a meaningfully upgraded ability to search video content without the need to watch it, using natural language queries to find relevant assets across their entire media library.

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Technical Overview: Cloud-Native Media Asset Management on AWS

How the AI Metadata Generation System Works

At its core, Nomad Media’s Retrieval-Augmented Generation system is designed to make media discoverable, not just by filename or manually entered tags, but by what’s actually in the content. It achieves this by generating rich, embedding-based metadata that captures the meaning, context, and semantics of each asset.

The system uses a staged automated workflow. Once media is ingested and transcoded by the Nomad Platform, the following AI-powered operations run on each asset:

• Transcription and subtitling powered by Amazon Bedrock Data Automation

• Scene segmentation: breaking media into discrete video and text segments with AI-generated scene summaries, using Amazon Bedrock Data Automation

• Image-to-text summarization via Amazon Nova

• Vector and embedding generation from text and image content, using Amazon Nova

• Storage of all generated metadata and embedding matches in Amazon DynamoDB, indexed for use by Amazon OpenSearch

The workflow is orchestrated through custom AWS Lambda functions, with API calls triggering each processing stage and AWS SQS handling messaging between the Nomad Platform and AWS services. The result is a fully automated metadata generation pipeline that requires no manual intervention once activated.

Scalability is built in. Amazon’s Bedrock and Nova services scale up and down automatically based on processing demand, ensuring enterprise-grade performance without over-provisioning, keeping total cost of ownership (TCO) low.

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AWS Cloud Media Platform: Services & Integration

As an AWS Partner, Nomad Media builds upon a comprehensive set of AWS services to deliver a cloud-native media asset management platform. For this deployment, the core RAG components are Amazon Bedrock, Amazon Nova, and Amazon DynamoDB.

The broader Nomad Media Platform also integrates natively with Amazon Virtual Private Cloud, Amazon S3, Amazon Cognito, AWS Lambda, Amazon SQS, and AWS Storage Gateway. Amazon Glacier supports cost-effective long-term archiving of the Client’s asset library, an important consideration for managing the TCO of a large video archive.  

Live content delivery supporting the Client’s ongoing public events and community programming is handled by Amazon Elemental MediaLive, a broadcast-grade live video processing and packaging service, with Amazon CloudFront and Amazon CloudTrail providing world-class public distribution service. Amazon Bedrock Data Automation is also available to generate captions and enable per-user content localization for streaming and video-on-demand delivery.

Intelligent search across the archive is powered by Amazon OpenSearch, which indexes the AI-generated metadata from the RAG pipeline and makes every enriched asset immediately discoverable across the platform. Amazon QuickSight is also available within the platform as a choice for analytics and reporting.

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Platform Integrations

Nomad Media’s RAG functionality is built entirely on AWS services, with no third-party AI or metadata tools. For standard platform functionality, the Nomad Media Platform includes integrations with Google AdSense and the Bitmovin HTML5 Video Player.

The Client’s team accesses the platform via Nomad Media’s SSO integration with their authorization provider, streamlining user management and role assignment. The Bitmovin player is used internally to preview proxy copies of assets stored on AWS, keeping media review fast and accessible without requiring downloads.

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Deployment Timeline

The Client’s Retrieval-Augmented Generation system was launched in stages between January 15, 2025 and July 1, 2025.

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Results: Smarter Search, Stronger Media Workflows

With Nomad Media’s AI-powered media asset management in place, the Client’s media library went from a partially searchable archive to a fully discoverable, intelligence-enriched content repository. The combination of AI metadata generation and RAG-powered search made it meaningfully easier to find the right asset, whether for a marketing campaign, a promo reel, or a last-minute production request.

Because the Nomad Media Platform had already become the central hub for the Client’s media asset management operations, the impact of the RAG upgrade was felt across the entire organization. Editors, executives, and production teams all gained access to a more capable, more intuitive search experience, one that understands content, not just metadata labels.

The Client is now better positioned to unlock the commercial and creative potential of their media archive, with an AI-powered, cloud-native media asset management platform that can scale with their library and their ambitions.