CogniK has built state-of-the-art profiling and recommending technologies in order to propose relevant content or products to selected audiences with learning, entertaining or shopping objectives.

The algorithm developed for edutainment focuses on young children (preschool to elementary school) while the algorithms for personalized VOD or home shopping are suited for a large audience.

CogniK algorithms are based on explicit and implicit profiling. The core of the matching technology is a combination of the a multi-dimensional K-neighbours algorithm and statistical, Bayesian, approach.

Truly Multi-Platform & Multi-Screen technology

With CogniK API, your media portal, VOD store or home shopping services combines smart recommendation with dynamic personalization to offer your audience a unique experience across all connected screens, including PCs, tablets and TVs.

Easy & Flexible Setup, Deployment & Operation

CogniK API is an easy-to-use programming interface allowing any kind of online applications to take full advantage of CogniK’s powerful profiling and recommendation engine, without the need for any specific and costly on-site implementation:
► Simple & user-friendly interface
► Cost-effective integration
► Multiple application support
► Customizable per partner

For more information about CogniK API, please read our white paper.

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Implementing Researcher’s Expertise into Machine Learning Algorithms

The technologies developed by CogniK have been conceived by our internal R&D team in cooperation with the ICAR research lab. ICAR is a team of multi-disciplinary researchers focusing on cognitive sciences: language, interactions, learning. It depends on French National Research Centre CNRS and is located at the heart of prestigious Ecole Normale Supérieure. Kristine Lund, vice-director of ICAR lab, is co-founder and Chief Science Officer for CogniK.