A recommendation engine may generate a recommendation in response to user interactions and executed operations in a system. The recommendation may be determined according to a number of factors including, but not limited to, an object affinity and a user affinity. The recommendation may include one or more of a recommendation to use an object and a recommendation for taking one or more actions. The recommendation may be provided to a user if the recommendation satisfies a confidence threshold. Recommendations provided by the recommendation engine are tracked to determine if the user accepted or rejected the recommendations. User history of accepting or rejecting recommendations may be utilized to train the recommendation engine for future recommendations and to build a user profile in a user database.