2025 Sneak Peek

Violeta Milarova

Mar 19

This year is already off to an exciting start, and we’re rolling out new tools to improve efficiency and optimize recommendations.

Here’s what’s available and what’s coming next.

Copy Settings Between Recombee Databases - (Now Available!)

Managing multiple Recombee databases is now more efficient than ever. With this newly released feature, you can effortlessly copy settings such as defined properties, business rules, scenarios, and widgets between databases.

Configure and fine-tune your setup in a development environment, test it thoroughly, and then easily transfer everything to your production database. Say goodbye to manual duplication and hello to streamlined workflows, improved consistency, and reduced errors.

This feature empowers you to focus on innovation while ensuring a smooth transition from testing to production.

Optimize with A/B Testing for Scenarios

Coming in 2025, Recombee will introduce built-in A/B Testing for Scenarios, giving you the power to fine-tune your recommendations like never before.

This feature will allow you to test different configurations such as varying Boosters or Logics within the same Scenario. By running controlled experiments and evaluating performance metrics, you can determine which settings deliver the best results for your users.

Whether you're optimizing for engagement, conversions, or other KPIs, A/B Testing will provide valuable insights to help you make data-driven decisions and maximize the impact of recommendations.

Recombee Widget SDK

In 2025, Recombee will launch the Widget SDK, a powerful new tool designed to make creating customized recommendation widgets a whole lot easier.

While our JavaScript SDK offers full flexibility to build visualizations from scratch, and the HTML Widget Editor in our Admin UI enables widget creation without any programming, the Widget SDK strikes the perfect balance.

It empowers developers to create highly customized widgets without starting from scratch, simplifying the process while retaining creative control.

Algorithmic Improvements

This year, we will continue improving our LLM-based semantic search, making it available to more customers.

To further enhance the performance of our recommender system, we are developing advanced collaborative filtering algorithms using sparse autoencoders, along with multimodal transformer-based models that process both images and text.

The deployment of the multimodal beeFormer will significantly improve the accuracy of our recommendations, particularly in cold-start scenarios and beyond.

We’re excited for what this year holds and can’t wait to bring you even more tools to drive your success! 🤝