There is great news for book lovers! Seoul-based tech startup Braincolla, made up of ‘Brain’ plus ‘Collaboration’, has a mobile app ‘iink’ that helps book lovers pick the book that is perfect for them! Established in 2015, Braincolla carries out the innovation of the content business model through data distribution. The company specializes in machine learning and deep learning in the text-content field by developing algorithms that provide personalized book recommendations and predict the next bestseller. The algorithm matches readers with books based on their taste. So you don’t have to waste time scrolling through titles and reading blurbs to pick the book you want to enjoy reading. Simply let Braincolla do the job for you!
Discovering a best seller just for you
With the dual focus on churning out bestsellers but also meeting the reader’s taste, Briancolla researches a best- seller prediction model. The platform matches users and the content precisely out of hundreds of genres and titles. There are personal book recommendations to the reader that is dependent upon the individual’s taste.
The app has engines such as the Contents Context Analysis engine, User Reading Insight Analysis engine, Contents Recommendation Engine, Bestseller and Target User Prediction Engine. The app also offers authoring tools for writers. Authors can write a catchy storyline with tools analyzing the writings and readers’ feedback.
The company has collaborated with Yes24, the national no.1 online bookstore, and will promote the app through them. The company has acquired a technology partnership with GCP (Google Cloud Platform) this year in March and is expanding the business field.
Braincolla won the ‘Smart App Award’ in 2017 and the ‘Library Big Data Best Use Case Competition’ in 2018. It is being financed by Joara Corp. The startup’s app was selected as 2015 Naver App Store startup best app 20. It has also now started another app ‘myfan.ai‘ which keeps the author or writer updated about the readers’ reviews and feedbacks on their work.
