Recommender Service

Overview

Our Recommender service simplifies the development of recommendation systems for a variety of use cases. It offers a fully managed, low-code interface that enables real-time recommendations that adapt dynamically to user events. Additionally, it offers users configurable endpoints for custom item-to-item, item-to-user, and user-to-user recommendation scenarios. Teams with limited machine-learning expertise can build highly personalised, scalable recommenders for AI-driven customer experiences.

• Simple client interface for managing and creating custom recommendations
• Multi-modal representations of item-level data objects.
• Personalized user recommendation and search based on past events and interactions
• Configurable endpoints for different recommendation scenarios

We’re actively looking for customers to join our private beta. If you’re interested, please let us know.