News Releases

VUniverse Named One of Five Finalists for SXSW Innovation Awards: AI & Machine Learning Category
Company to Demonstrate Live at Finalists Showcase in Austin, TX on Saturday, March 14

NEW YORK, Feb. 5, 2020 /PRNewswire/ -- VUniverse, a personalized movie and show recommendation platform that enables users to browse their streaming services in one app—a channel guide for the streaming universe, announced today its been named one of five finalists in the AI & Machine Learning category for the 23rd annual SXSW Innovation Awards.

The SXSW Innovation Awards recognizes the most exciting tech developments in the connected world. During the showcase on Saturday, March 14, 2020, VUniverse will offer first-look demos of its platform as attendees explore this year's most transformative and forward-thinking digital projects. They'll be invited to experience how VUniverse utilizes AI to cross-reference all streaming services a user subscribes to and then delivers personalized suggestions of what to watch.

"We're honored to be recognized as a finalist for the prestigious SXSW Innovation Awards and look forward to showcasing our technology that helps users navigate the increasingly ever-changing streaming service landscape," said VUniverse co-founder Evelyn Watters-Brady. "With VUniverse, viewers will spend less time searching and more time watching their favorite movies and shows, whether it be a box office hit or an obscure indie gem."

About VUniverse
VUniverse is a personalized movie and show recommendation platform that enables users to browse their streaming services in one app—a channel guide for the streaming universe. Using artificial intelligence, VUniverse creates a unique taste profile for every user and serves smart lists of curated titles using mood, genre, and user-generated tags, all based on content from the user's existing subscription services. Users can also create custom watchlists and share them with friends and family.

Media Contact
Jessica Cheng
jessica@relativity.ventures

SOURCE VUniverse