Paris, France (February 27, 2019)—Israeli national radio network Galei Tsahal (Galatz) is also known for its news and thematic programs featuring politicians, military leaders, and influential citizens. With that in mind, it recently updated its production workflows and asset management across its digital channels and social networks.
That meant upgrading to the Dalet Galaxy five Media Asset Management (MAM) and Workflow Orchestration platform to affect production and delivery of its music and news-related content through social media networks, reporters’ abilities to file stories from the field, and use AI-powered speech-to-text algorithms to enable wider accessibility to its historical archives, which date back to its founding in 1950.
“The upgrade to Dalet Galaxy five is enabling us to build a new content value chain, better integrating our social media channels across our operations, and leveraging AI services to make our entire inventory more discoverable and better monetized,” states Izak Pasternak, head of the technical department, Galatz.
With Dalet Galaxy five, Galatz will be able to make all content that is produced in the production system available to social media publishing with a click of a button. Social media content performance (views, likes, shares) will be analyzed by the broadcaster; that data will be used to make better-informed decisions as to what to provide audiences next, helping to deliver a more enjoyable experience to listeners.
Connecting in-the-field reporters directly to the newsroom, Dalet On-the-Go lets journalists organize and submit comprehensive news packages from their mobile device. Users can record interviews, write stories, and assemble and upload packages to the Dalet Galaxy five content catalog for sharing across the station or sending direct to air.
With historic information under its care, Galatz wanted to make its archives open to the public for the first time online. Leveraging Dalet Media Cortex, the new AI cloud service of Dalet Galaxy five, the network applied AI-driven, speech-to-text algorithms to all archived content, turning it into text that is both searchable and accessible via an online portal.
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