Jinni taps TMS Metadata for personalised TV and film guide

Editor | 05-12-2013

Semantic video discovery engine provider Jinni has made a strategic investment in the TMS On Entertainment metadata solution to provide availability information for linear TV and OTT content on its My TV & Movie Guide App.

Jinni claims to be the first and only taste-and-mood based semantic video search and recommendation engine delivering what it says is the most personalised and relevant TV and movie options to end users.

The company believes that use of industry standard On Entertainment data from TMS will allow its advanced search and discovery functionality to directly connect with viewing information for all linear TV and OTT content sources. TMS Unique IDs synchronise entertainment assets across multiple datasets which facilitates discoverability across linear TV, video-on-demand (VOD) and over-the-top (OTT) content.

"Jinni's goal is to set users free from the frustration of searching for something to watch. Our recommendations take them directly to the content they are most likely to enjoy," said Yosi Glick, co-founder & CEO of Jinni. "TMS metadata allows us to present users the very best recommendations from amongst all content available to them, and to directly connect to all viewing options for instant gratification."

"TMS is pleased to provide the enhanced entertainment data that helps Jinni facilitate consumers' viewing of TV shows and movies recommended by its taste and mood based discovery engine," added Rich Cusick, general manager of TMS. "Jinni users are sure to get hooked on the advanced search and discovery experience."