Advertisers and publishers want to use machine learning (ML) to improve addressability and audience experience by placing ads near contextually-relevant content. For data scientists, this often requires spending significant time on data engineering, data pre-processing, and training in order to extract metadata from petabytes of media content, or score billions of ad events per day with ML models. Contextual Analysis solutions on AWS help customers spend less time on data engineering and more time on data science to accelerate product development and launch for ML-based contextual advertising workloads such as content metadata extraction, brand safety analysis, and fraud prevention.
Partner Solutions
Software, SaaS, or managed services from AWS Partners
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Total results: 4
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Nomad Media AWS Migration and Modernization Competency…
Nomad Media Platform Nomad Media is an intuitive cloud-based content and asset management platform powered by Amazon Web Services AI technology that transforms the way you manage your ever-growing content libraries. The Nomad Media Platform seamlessly merges the world of our cloud-based content and asset management with AI, allowing you to generate more value from your content, unlock new opportunities, drive new growth, and deliver new efficiencies. Our intuitive user interface makes storing, searching, managing and distributing your content quick and easy. -
Veritone Digital Media Hub
Veritone Digital Media Hub is an AI-powered, white-label asset management and monetization solution. It gives content owners the opportunity to generate more revenue from their assets by setting up their own digital storefront and makes content easily discoverable with AI-powered metadata tagging and content management.
Guidance
Prescriptive architectural diagrams, sample code, and technical content
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Total results: 4
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Contextual Intelligence Advertising Using Generative AI…
This Guidance shows how to use generative AI to derive contextual insights from multimedia assets and identify relevant audience segments for targeted advertising placements. By analyzing video, audio, and text, you can identify the most relevant audience segments and deliver personalized advertising experiences. Moreover, the use of multimodal large language models (LLMs) facilitates the extraction of insights from both visual and transcript components so you can align your media with the right advertising opportunities and monetize content more effectively.