The power of Contentigence™ comes from the use of Artificial Intelligence. We approached it with 3 vectors based on 3 solutions that we provide, i.e. Image Rating, Text Rating, and Video Rating.
For Image rating, we took the Google Vision API as the basis and used it to identify different elements and then using Contentigence™ to rate color combinations, white space, fonts, vectors, illustrations, and by connecting it with the ML model, we check the relevance of the image content.
Text rating is overall easier as the text content is rated in terms of grammar, plagiarism, and quality of content. The AI then drafts a text based on its understanding of the content by using ML data that it has collected from the World Wide Web (WWW) and then suggests improvements to the original content.
Video Content requires heavy lifting from the Contentigence™ where it converts the video into frames and then analyzes each frame content. After going through each frame, the Contentigence™ then runs a histogram analysis to find context and use ML data to compare content quality, and other factors.