Inspiration
We were inspired by the real-time challenges that F1 race engineers face, as described by the HMC^2 challenge, and sought to find a solution to one of the challenges faced by these engineers.
What it does
If an unexpected event occurs in the course of a race, we determine how that event could affect existing race strategy, and then propose those changes to the race engineers in real time and allow them to not skip a beat.
How we built it
We built the frontend using Tailwind CSS, React, TypeScript, and Next.js. The model was developed with LangGraph, LangChain, Groq, and Python, and we used PostgreSQL as our database.
Challenges
We found that it was difficult to connect the frontend and backend.
Accomplishments
We were proud of the workflow that our backend took in order to analyze the data.
What we learned
We learned that we would need to work faster to solidify our plans and flesh them out earlier in the process so we would have more time to catch potential pitfalls.
What’s next for it
We would love to continue working on it with NMC^2 as we believe that this project has the potential to positively impact race engineers.
Built With
- groq
- langchain
- langgraph
- llm
- nextjs
- openai
- postgresql
- python
- react
- tailwind
- typescript



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