As TV’s gradually get connected to the Internet, there is an increasing appetite for smart content recommendation. Personalized recommendations are not an easy problem to tackle – Netflix went as far as offering $1 million prize for the top algorithm for scientists and researchers who were up for the Netflix challenge in 2009. Jinni, an Israeli startup offering a taste-and-mood based guide for movies and TV shows, announced yesterday the closing of its $5 million series B funding. The round was led by Belgacom and an undisclosed connected-TV manufacturer. Previous backer DFJ Tamir Fishman (led the previous $1.6 million round a year ago) also participated.
Yosi Glick, Jinni’s CEO and Co-founder said:
“Completing the Series B funding round allows us to focus on what we do best: Developing an innovative product that is designed to fundamentally improve the entertainment experience. We’re very happy to collaborate with Belgacom to bring Jinni’s intuitive video guide features to an international, multilingual audience. The round B investors are leading innovators in creating the next-generation entertainment experience, across platforms and devices. We firmly believe that superior discovery features and personalization are key to creating this experience, and we’re fortunate to have strategic investors who share our vision”
The company’s press release did not specify the identity of the consumer electronics partner, but hinted at the potential expansion plan of Jinni from your computer screen to your living room. The TV recommendation market is getting crowded with very talented companies ranging from Jim Lanzone’s Clicker, backed by Red Point as well as Boxee, the Israeli startup that needs no introduction, who also recently launched its own set up box, competing with Apple TV and Google T. Jinni’s potential edge may be on its direct TV integration, removing the need for a separate device.
Jinni enables users to search for TV shows and movies based on its ‘Movie Genome‘ technology. Users can search for story plots (e.g “race against time”), moods (upbeat, silly) title, genre, time periods and more. Think of it as a search engine for video content that understands the semantic meaning behind the query. Some of the featured searches include: “award winner secret agent comedy”, or “love story in New York”. What I particularly miss in Jinni’s product is the lack of social interaction (which Boxee has done so well).
Latest posts by Eze Vidra (see all)
- Emerging Machine Intelligence Clusters - March 2, 2017
- 30 Machine Intelligence Startups to Watch in Israel - February 15, 2017
- Five Books I Want to Read in 2017 - January 16, 2017