This post is co-written by Jake Friedman, President + Co-founder of Wildlife.
Amazon Nova is enhancing sports fan engagement through an immersive Formula 1 (F1)-inspired experience that turns traditional spectators into active participants. This post explores the Real-Time Race Track (RTRT), an interactive experience built using Amazon Nova in Amazon Bedrock, that lets fans design, customize, and share their own racing circuits. We highlight how generative AI capabilities come together to deliver strategic racing insights such as pit timing and tire choices, and interactive features like an AI voice assistant and a retro-style racing poster.
Evolving fan expectations and the technical barriers to real-time, multimodal engagement
Today’s sports audiences expect more than passive viewing—they want to participate, customize, and share. As fan expectations evolve, delivering engaging and interactive experiences has become essential to keeping audiences invested. Static digital content no longer holds attention; fans are drawn to immersive formats that make it possible to influence or co-create aspects of the event. For brands and rights holders, this shift presents both an opportunity and a challenge: how to deliver dynamic, meaningful engagement at scale. Delivering this level of interactivity comes with a unique set of technical challenges. It requires support for multiple modalities—text, speech, image, and data—working together in real time to create a seamless and immersive experience. Because fan-facing experiences are often offered for free, cost-efficiency becomes critical to sustain engagement at scale. And with users expecting instant responses, maintaining low-latency performance across interactions is essential to avoid disrupting the experience.
Creating immersive fan engagement with the RTRT using Amazon Nova
To foster an engaging and immersive experience, we developed the Real-Time Race Track, allowing F1 fans to design their own custom racing circuit using Amazon Nova. You can draw your track in different lengths and shapes while receiving real-time AI recommendations to modify your racing conditions. You can choose any location around the world for your race track and Amazon Nova Pro will use it to generate your track’s name and simulate realistic track conditions using that region’s weather and climate data. When your track is complete, Amazon Nova Pro analyzes the track to produce metrics like top speed and projected lap time, and offers two viable race strategies focused on tire management. You can also consult with Amazon Nova Sonic, a speech-to-speech model, for strategic track design recommendations. The experience culminates with Amazon Nova Canvas generating a retro-inspired racing poster of your custom track design that you can share or download. The following screenshots show some examples of the RTRT interface.
 |
 |
Amazon Nova models are cost-effective and deliver among the best price-performance in their respective class, helping enterprises create scalable fan experiences while managing costs effectively. With fast speech processing and high efficiency, Amazon Nova provides seamless, real-time, multimodal interactions that meet the demands of interactive fan engagement. Additionally, Amazon Nova comes with built-in controls to maintain the safe and responsible use of AI. Combining comprehensive capabilities, cost-effectiveness, low latency, and trusted reliability, Amazon Nova is the ideal solution for applications requiring real-time, dynamic engagement.
Prompts, inputs, and system design behind the RTRT experience
The RTRT uses the multimodal capabilities of Amazon Nova Pro to effectively lead users from a single line path drawing to a fully viable race track design, including strategic racing recommendations and a bold visual representation of their circuit in the style of a retro racing poster.
The following diagram gives an overview of the system architecture.
Prompt engineering plays a crucial role in delivering structured output that can flow seamlessly into the UI, which has been optimized for at-a-glance takeaways that use Amazon Nova Pro to quickly analyze multiple data inputs to accelerate users’ decision making. In the RTRT, this extends to the input images provided to Amazon Nova Pro for vision analysis. Each time the user adds new segments to their racing circuit, a version of the path is relayed to Amazon Nova Pro with visible coordinate markers that produce accurate path analysis (see the following screenshot) and corresponding output data, which can be visually represented back to users with color-coded track sectors.
This is paired with multiple system prompts to define the role of Amazon Nova Pro at each stage of the app, as well as to return responses that are ready to be consumed by the front end.
The following is a prompt example:
The prompts also use sets of examples to produce consistent results across a diverse range of possible track designs and locations:
This is also a key stage in which to employ responsible use of AI, instructing the model not to generate content that might infringe on existing race tracks or other copyrighted material.
These considerations are essential when working with creative models like Amazon Nova Canvas. Race cars commonly feature liveries that contain a dozen or more sponsor logos. To avoid concern, and to provide the cleanest, most aesthetically appealing retro racing poster designs, Amazon Nova Canvas was given a range of conditioning images that facilitate vehicle accuracy and consistency. The images work in tandem with our prompt for a bold illustration style featuring cinematic angles.
The following is a prompt example:
The following images show the output.
 |
 |
Conclusion
The Real-Time Race Track showcases how generative AI can deliver personalized, interactive moments that resonate with modern sports audiences. Amazon Nova models power each layer of the experience, from speech and image generation to strategy and analysis, delivering rich, low-latency interactions at scale. This collaboration highlights how brands can use Amazon Nova to build tailored and engaging experiences.
About the authors
Raechel Frick is a Sr. Product Marketing Manager at AWS. With over 20 years of experience in the tech industry, she brings a customer-first approach and growth mindset to building integrated marketing programs.
Anuj Jauhari is a Sr. Product Marketing Manager at AWS, enabling customers to innovate and achieve business impact with generative AI solutions built on Amazon Nova models.
Jake Friedman is the President and Co-founder at Wildlife, where he leads a team launching interactive experiences and content campaigns for global brands. His work has been recognized with the Titanium Grand Prix at the Cannes Lions International Festival of Creativity for “boundary-busting, envy-inspiring work that marks a new direction for the industry and moves it forward.”
