Real Clients. Real Success.

We use natural language processing and machine learning to understand item details and user behavior. This combination allows us to create personalized product recommendations in real-time.

An A/B test, also known as a split test, is a method used to compare two versions of a webpage, app feature, or product recommendations to determine which one performs better. Essentially, we divide your audience into two groups: Group A sees the original version (the control), and Group B experiences the new version (the variation). By analyzing how each group interacts with the version they see, we can measure changes in behavior, such as increases in purchases, engagement, or any other key metric of interest. This approach allows us to make data-driven decisions and continuously improve the personalization and effectiveness of our recommendations on your site. Jewel ML facilitates this process seamlessly, providing you with clear insights into the impact of our AI-driven recommendations without requiring any separate A/B testing software.

Our solution is fully no-code. Your team won't need to do any engineering work, from the initial setup to ongoing maintenance and customizations.

Our solution can increase your website's revenue by 5-15% in just 30 days. It's a no-code solution, requiring minimal initial setup and no ongoing effort from your team.

Yes, we can integrate seamlessly with your current systems through APIs or tags, without requiring any changes to your site code.