Jinni solves an interesting problem. PPV, VOD and online video platforms lack a recommendation service. Think about it – every time you buy a movie on demand, you need to sift through all the new releases and try to remember feedback you’ve heard elsewhere. Jinni wants this problem algorithmically by bringing into account viewers’ moods and tastes using content analysis and user psychographics. The result is better user experience and increased use of the video inventory (users can access long-tail content rather than box office hits only).
According to the site:
Jinni’s innovative content discovery solution for professional and semi-professional videos organizes metadata across multidimensional parameters of plot and experience, reflecting how people really think about entertainment. Our video data brain gives precise, succinct, and highly personalized search-and-recommendation results.
Jinni’s business model is based on advanced advertising matching, fitting the user’s taste with high accuracy. Today’s categorization in VOD systems is based on the genre – Comedies, Thirllers, Horror movies etc. Jinni’s engine is propelled by sentiments, so users will be able to describe parameters that fit their mood, for example – one could search for movies that are: ‘appropiate for kids’, ‘cinical’, or ‘relaxing’ .
Jinni is still in stealth, but it is actively looking for partnerships with TV Operators and Internet Content Providers who are looking to improve their user experience. Jinni’s value proposition is:
- search and browse intuitively and enjoyably using natural metaphors
- get fast, precise and user-friendly single-page search results
- develop a profile based on viewing behavior
- get highly personalized recommendations
- meet other users with shared tastes
- link to information about where to purchase or view videos
- …and much more.
Source: The Marker
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