Adnane Errazine

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Motivaty: Making Math Matter

/ Hackathon recap / 3 min
Motivaty preview image

Motivaty came out of a question that felt personally familiar: what if abstract math concepts always came with the real-world examples that make them feel alive instead of distant?

Good educational products often reduce abstraction friction before they add new complexity.

The Core Idea

Instead of presenting formulas as isolated objects, the project tried to connect them to practical domains, memorable examples, and a more motivating learning path. The goal was to make the value of the concept visible immediately.

Fourier transform illustration Motivaty why illustration

How It Worked

  1. Users entered a concept, theorem, or formula.
  2. The app surfaced practical applications and relatable examples.
  3. It generated a personalized roadmap tied to user interests.

Why I Like It

It sits at a nice intersection of education, product thinking, and AI-assisted retrieval. It also reflects a broader theme I care about: systems become more useful when they reduce abstraction friction for real people.

Tech Stack

  • Frontend: React + Vite
  • API layer: FastAPI
  • AI/ML: Mistral Small, Mistral OCR, LangGraph
  • Future direction: richer retrieval, public datasets, vision-language parsing

What Stays With Me

Hackathons are great pressure tests. They expose what matters, what can be cut, and which ideas still feel compelling once time gets brutally short.

Acknowledgments

Huge thanks to the Tech: Europe organizers and sponsors, especially Knowunity for powering the Education track and Mistral AI for model access.

Project repository