Game recommendations

We have developed Kinrate AI to provide personalized game recommendations to target audiences. Kinrate AI is a hybrid model, which combines both collaborative filtering and content-based approach to generate stellar results.

Kinrate AI has learned to predict both player profiles and latent qualities for digital games. To date, Kinrate AI has learned to portray a total of 12,000 games according to 61 latent gameplay characteristics, which measure six main factors of players’ gameplay preferences: aggression, management, exploration, care-taking, coordination, and problem-solving. We have validated the model in USA, Japan, Korea, Canada, UK, Denmark, and Finland.

Excellent instant recommendations! I went through the first 30 games in my list, and those games which I haven’t played yet, I’d really like to try”

Solution to the cold-start problem

By teaching AI with player data of more than 48 Million game players worldwide, we have been able to develop a great cross-platform game recommendation engine.

In contrast to established products, our recommender is a plug-and-play model, tailored for game business purposes. Our model can be integrated directly to your tech with our API.

Kinrate search engine finds similar games based on the unique AI-generated latent data. The search engine can be integrated to e.g., your marketplace. By finding the searched title and games similar to it, your customers are likely to spend more time and money on your platform. Try our intelligent similar games search engine.