BetaSeries Match
The content description platform that transforms the TV series discovery and recommendation experience.
Developed in collaboration with CNRS scientists in artificial intelligence and the humanities and social sciences, BetaSeries Match uses revolutionary fingerprinting technology to analyze and understand TV series with an unprecedented level of depth and precision.
Unlike traditional recommendation systems, which rely on superficial metadata or user behavior to close off choices, BetaSeries Match examines the intrinsic qualities of content, from narrative and thematic elements to artistic, ethical and emotional characteristics.
These analyses performed by the latest AI technologies (LLM, Computer Vision) on the video (from which key frames, audio and text are extracted) produce a 64-dimensional description of the content. This method is fast and handles large volumes of content in all languages, ensuring very fine-grained content discoverability that truly resonates with the individual tastes of their viewers.
Applications: Audience recommendation (B2C)
- Clients: Content operators
- Using these content footprints to improve content recommendations and build audience loyalty
- The technology is offered via APIs to integrate with existing engines or can be offered in operated mode
- Totally RGPD-compliant, does not require transmission of users' personal information to operate
Applications : Content discoverability (B2B)
- Customers: Producers and distributors with catalogs for sale
- Presentation of catalogs with many more criteria and differentiations, analysis of catalog sales potential and buyer needs to be targeted, including in large volumes on old and/or little-known content
- The technology is offered via APIs to integrate with existing sales tools, or can be offered in operated mode. It is compatible with all scripted content (series, films, unitaries, documentaries)
- It is also possible to analyze and compare other content sources, such as a film script or an episode script