Amagi launches Tornado, a machine learning augmented content preparation suite

Amagi, which deals in cloud-based technology for media processing, has announced the launch of Tornado, a machine learning-based content preparation service that enables TV networks and content owners to scale their operations, accelerate broadcast workflows, generate new revenues and reduce operational costs.

Tornado is a first-of-its-kind, cloud-based machine learning-augmented content preparation suite that tackles content preparation challenges head-on. Amagi Tornado is conceptualised as a suite of machine learning-based content preparation services that dynamically evolves as machines learn more about each segment of a video asset as they process higher volumes of content. Tornado can cater to the unique preparation needs of TV networks, content owners, vMVPD platforms, and digital-first networks with the company planning to continually expand the suite functionality and capabilities to optimise the entire broadcast workflow.

Through Tornado, broadcasters can:

Factory-scale VOD segment creation: Linear broadcast model is highly reliant on sophisticated processing of video for ad break points identification, credits, color bars and blacks. Using Amagi Tornado, this process can be completely automated, allowing broadcasters to simply upload video assets to Tornado, and then prepare breakpoints based on pre-loaded inputs from human content preparation specialists.

Auto ad detection of mid-roll ads: Using machine learning techniques, Tornado can automatically detect ads in linear broadcast streams without any ad markers by comparing video segments with an active ad library. This allows broadcasters to better optimise their mid-roll ads allowing them to insert the most appropriate, localized ads within their feeds, which is challenging for OTT advertisers and broadcasters today.

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