AI for E-commerce

Real-time Recommendation

Thanks to the proprietary Radicalbit platform – an Agentic AI Infrastructure that accelerates the development of ML and LLM-based applications – Bitrock supports online retailers with dedicated AI-driven real-time recommendation systems. These systems analyze customer data, such as purchase history, interests, and behaviors, to generate highly personalized purchase suggestions. Real-time data processing enables relevant and timely recommendations by instantaneously adapting to shifts in shopping behaviors and customer journeys. This level of personalization improves customer experience, supporting upselling and cross-selling efforts. Finally, Radicalbit’s monitoring capabilities ensure the correct behavior of the-time recommendation model, allowing for corrective interventions in case of degradation.

Thanks to the modular nature of the system, it is also possible to configure access to the portal for different customers, guaranteeing access to specific modules or customizing the style and appearance of the application.

The solution is therefore able to support the user throughout the life cycle of the product by standardizing access and the style of the various applications, providing the information necessary to manage investments.

The platform allows real-time data to be processed for the various markets, providing users with the tools and information necessary to select the investment strategies best suited to their needs and respond quickly to market changes. The system has been optimized to minimize latency during data transmission and processing and to guarantee robustness and consistency during tradable price calculation operations, a critical element in the financial sector.

This architectural approach not only allows for efficient management of daily operations, but also offers the flexibility needed to implement targeted updates and customizations specific to different customers, without compromising the stability and performance of the entire system.