RaceMind.ai

Inspiration

I grew up racing competitively, starting in karts at age 12 and moving through Formula BMW, Formula Renault, and Formula Dodge. My dream was to reach Formula 1, but that journey ended after a serious crash at 22. Since then, I’ve built a career in AI research focused on safety and social impact. Still, F1 has always been part of me. Watching Lewis Hamilton lose races because of strategy errors lit a fire again. I began wondering: what if I could still make it to F1, not as a driver, but by helping someone else win?

That idea became RaceMind.ai, an AI strategist that sees the entire race, thinks faster than a human, and gives drivers the edge they need to win.

What it does

RaceMind is an AI-powered strategy assistant for Formula 1 teams. It ingests real-time telemetry, driver position, tire age and compound, weather conditions, and historical stint performance. Based on this, it calculates optimal pit stop strategies and race decisions. The system visualizes time deltas with precision, detects undercut opportunities, predicts traffic impact, and will soon allow drivers to interact with it through voice during races.

How we built it

This project was built entirely during the Bolt Hackathon. Using Bolt’s prompt-based flow, I created a delta graph engine that models time loss, pit stops, and stint degradation across race laps. The frontend is built in React, with data simulation modeled after actual F1 telemetry behavior.

Challenges we ran into

Understanding the exact structure behind Red Bull-style strategy graphs took deep research. Modeling realistic tire degradation, fuel loads, and timing loss accurately without real telemetry was also challenging. Balancing data density with clear UX took iteration.

Accomplishments that we're proud of

We built a working version of a strategist’s tool, including delta traces that reveal pace drop-off, pit stop loss, and undercut potential. It’s already capable of suggesting alternate strategy paths mid-race and visualizing performance impact clearly.

What we learned

Bolt made it possible to move fast with real complexity. I learned how to reduce F1's chaotic race dynamics into structured, real-time visual insights. I also confirmed that with the right modeling, AI can rival human strategists under pressure.

What's next for RaceMind.ai

Next, we plan to integrate live FIA telemetry and voice interaction, allowing the driver to speak directly with the AI during the race. The long-term vision is to turn RaceMind into a real-time AI co-strategist that helps win races at the highest level.

Built With

• bolt