Connect: Modernize media workflows and unlock more value

Media organizations spend significant resources creating engaging trailers and recaps from extensive content libraries. This demo showcases techniques that can accelerate creating tailored trailers for multiple platforms while maintaining creative control. The Guidance for a Media Lake on AWS, enhanced with intelligent AI agents, transforms this process through advanced scene analysis, sentiment detection, and automated segmentation. Using the Automate-IT solution from AWS Partner Embrace, this workflow automatically assembles clips in order, illustrating how a combination of AI and automation can streamline and simplify content creation workflows.

Media organizations struggle with optimizing storage costs, content silos, and the inability to unlock the value of their vast archives through modern media workflows. Traditional on-premises storage systems create barriers to innovation, preventing organizations from leveraging cloud-native AI services that could transform their content into strategic business assets. In this demonstration, we showcase how AWS services and AWS Partner solutions from Cloudfirst.io for archive migration and Dalet for asset management help customers seamlessly transition their content ecosystem to the cloud. We demonstrate how migrated archives are automatically indexed using the orchestration capabilities of the Guidance for a Media Lake on AWS to enable semantic search, while live content flows through Time-Addressable Media Store (TAMS) workflows. Attendees see the strategic cost benefits driving enterprise cloud migration decisions, including reduced infrastructure overhead and enhanced AI-driven content discovery.

Media companies face significant challenges in managing vast collections of digital media files scattered across multiple storage locations, which makes content discovery and understanding time-consuming and inefficient. The Guidance for a Media Lake on AWS addresses this challenge by providing a unified, intelligently searchable catalog of media assets with advanced video understanding capabilities. This demonstration showcases the use of AWS Partner TwelveLabs' foundation models and Amazon Bedrock Agents to enable bi-directional conversational video understanding, allowing users to engage in both single-turn queries and multi-turn conversations about video content. Through natural language interactions, users ask complex questions about scenes, objects, actions, and context within videos, while the system maintains conversation history to enable follow-up questions and deeper exploration of content. Integrations with upstream metadata providers, such as the Guidance for Media2Cloud on AWS, enrich the foundational metadata, while the core focus remains on the intelligent video understanding capabilities that allow content creators and media professionals to discover, analyze, and extract insights from their video libraries through intuitive conversational interfaces. See how this comprehensive video understanding system transforms media workflows by enabling users to search not just for specific content, but to engage in meaningful dialogue about what's happening within their media assets.

Automated sports highlights are a crucial tool for rights holders to enable their marketing, creative, and distribution teams to reach and engage fans. However, tailoring videos and images to the myriad aspect ratios required for each delivery destination and social media platform is traditionally a labor-intensive and time-consuming process. By building a serverless, event-driven architecture on AWS, customers harness the power of AWS native services and AWS Partner solutions to accelerate and automate the highlight creation and packaging process. This automation enables broadcasters to deliver highlights to fans faster than ever by using AI to automatically detect key moments, generate localized narration, and enable context-aware reframing for multiple aspect ratios. In this demonstration, we showcase how AWS services, including Amazon Bedrock running Amazon Nova foundation models, combined with AWS Partner solutions from Prime Focus Technologies, TwelveLabs, Deepdub, Cloudinary, Odub, and Scoreplay, help customers reduce time and effort needed to create compelling highlight reels. We also demonstrate how AI-powered search capabilities make highlight discovery more intuitive and engaging for distributors and fans.

Media companies have extensive content libraries but struggle to maximize their commercial value. Traditional content management systems provide basic metadata but fail to connect content understanding with audience behavior and business performance, leaving monetization opportunities unexplored. A comprehensive media intelligence workflow powered by AWS transforms content into strategic business assets through semantic discovery and unified data insights. This demo showcases how to use AWS services to answer complex business questions about content investment decisions, subscription optimization strategies, and archive monetization opportunities. The solution combines semantic analysis, Amazon Q for QuickSight, and Amazon S3 Tables MCP Server to drive measurable revenue growth across content portfolios.