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AI-Powered Sports Advisor

Screenshot of AI advisor


A sports app aimed to integrate an innovative AI-powered advisory feature to leverage underutilized data, but faced significant internal constraints. The core engineering team was focused on their existing development roadmap and was unsure of the feasibility or the methodology required to build such a feature. This uncertainty necessitated an external solution that would not disrupt the team’s primary projects and could explore uncharted technical possibilities.


RTB-AI developed a robust solution by creating an external application that interfaces seamlessly with the client’s app through a webview, maintaining the appearance and functionality of a native feature. This approach involved transferring not only data but also images from the client’s app to the external application, utilizing computer vision techniques to analyze and make sense of the imagery. The AI utilized Retriever-Augmented Generation (RAG) to process and interpret extensive datasets, enriching the advisory capabilities of the tool.

Strict adherence to the client-provided UI specifications ensured a seamless user experience. Moreover, RTB-AI implemented a dual-tier access system where paid users enjoyed unlimited access to the AI’s full capabilities, whereas free users were allowed the full experience three times before transitioning to a basic version. This strategic access model was designed to optimize user engagement and manage operational costs efficiently for the client.


The deployment of the AI-powered sports advisor profoundly enhanced the app’s functionality and business model:

  • Enhanced Data Insights: By integrating computer vision and AI, the tool provided personalized advice based on individual user data and broader aggregated insights, significantly tapping into previously unused data.

  • Freemium Model Enhancement: The new feature bolstered the client’s freemium model by encouraging free users to upgrade for continued access to valuable personalized insights, thus driving incremental paid subscriptions.

This project not only fulfilled the client’s immediate need for an innovative feature without straining their core engineering resources but also set a precedent for integrating advanced AI functionalities in a user-centric and commercially viable manner.

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