EduAid — Your AI Study Companion

Inspiration

We wanted to make studying smarter, not harder. As students, we often struggle to condense massive notes into something meaningful and memorable. Tools like ChatGPT or Notion AI help, but they often feel detached from the learning process itself.

We asked ourselves:

“What if studying felt like talking to an AI tutor that remembers what you’ve learned?”

What it does

EduAid helps students learn faster by turning their study materials into:

Concise AI-generated summaries

Spoken recaps (via ElevenLabs voice synthesis)

Automatically generated flashcards for review

A session-based memory of past summaries

Users can paste text into the web app, get a summary instantly, and review it later through history or flashcards. The goal is to make study sessions interactive, efficient, and accessible.

How we built it

We built EduAid using a React / Next.js frontend and a FastAPI backend.

The frontend (deployed on Vercel) handles user input and displays summaries, history, and flashcards.

The backend (local MVP) provides two working endpoints:

POST /summarize — returns an AI-style summary

GET /history — returns recent summaries in memory

The full backend (in progress) integrates:

Gemini API for summarization

ElevenLabs for voice synthesis

Snowflake for persistent memory and analytics

This modular setup allows quick iteration — our MVP runs fully offline while the full stack evolves toward cloud deployment.

Challenges we ran into

Backend Deployment: Vercel and Render both struggled to package FastAPI correctly (Python 3.12 build plan issues).

Integration Limits: Limited access tokens and rate limits made testing Gemini and ElevenLabs slower.

Coordination: Syncing React and FastAPI updates across multiple contributors during a 48-hour sprint required constant debugging.

Persistence: Implementing temporary, in-memory data handling to simulate a database on the fly.

Despite these hurdles, we produced a working, connected MVP and a live web interface.

Accomplishments that we're proud of

Built and deployed a polished Next.js frontend during the hackathon

Delivered a working local FastAPI MVP backend

Designed architecture for Gemini + ElevenLabs + Snowflake integration

Created an intuitive, minimalist UI/UX for stress-free studying

Demonstrated real-time text summarization and history tracking

What we learned

How to integrate multiple APIs into a modular backend architecture

The challenges of serverless Python deployment with FastAPI

How to maintain team momentum and version control under hackathon pressure

The importance of balancing technical ambition with deliverable scope

What's next for EduAid — Your AI Study Companion

Fully deploy the backend using Render or Railway

Add Gemini-powered summarization and question generation

Integrate ElevenLabs for natural voice recaps

Connect to Snowflake for long-term study history and analytics

Improve the flashcard system with adaptive spaced repetition

Launch a public beta for students to test and provide feedback

EduAid aims to evolve into a truly personal AI tutor — one that not only summarizes but helps you master what you study.

Built With

• elevenlabs
• fastapi
• gemini
• git
• javascript
• nextjs
• python
• react
• render
• snowflake
• typescript
• uvicorn
• vercel
• vscode