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Amagi Debuts Machine Learning Powered Content Preparation Suite, TORNADO

MediaInfoline April 10, 2018
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Amagi, a global leader in cloud-based technology for media processing, 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. Compared to traditional manual content preparation, Amagi TORNADO is nearly six times more efficient, allowing broadcasters free up capital and streamline workflows.

Over the last three years, the broadcast industry has had to evolve significantly due to a rise in multi-screen content consumption, demands for “here and now” content and a shift in how consumers are viewing content as more consumers move from cable to OTT services.

In such an evolving scenario, TV networks, content owners, and digital-first networks are creatively trying to grab a piece of the action by trying new mediums and delivery methods to provide better experiences to consumers while streamlining costs and operations. However, despite these efforts, content preparation continues to require pain-staking hours of manual work and massive overhead costs. Enter Amagi’s TORNADO.

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 conceptualized as a suite of machine learning-based content preparation services that dynamically evolve 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 optimize 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 optimize 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.
  • Near real-time live to VOD conversion: Amagi TORNADO will soon allow broadcasters to create near real-time creation of VOD content from live broadcasts. Meaning, for example, broadcasters can create sports highlights packages automatically with little to no human effort required from “fresh off-the-air” sports contests and more.

“Given how competitive broadcasting has gotten today, it has never been more important for broadcasters to be able to optimize their operations and spends,” said Deepakjit Singh, CEO at Amagi. “TORNADO is game-changing for broadcasters and their teams today, allowing them to spend more time on creating better experiences for consumers and less time on mundane tasks.”

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