Project Design Phase
Proposed Solution Template
Date 15 February 2025
Team ID LTVIP2025TMID30127
Project Name Edu Tutor AI
Maximum Marks 2 Marks
Proposed Solution Template:
S.No. Parameter Description
1 Problem Statement (Problem Traditional education
to be solved) systems struggle to provide
personalized learning
experiences at scale.
Students often receive
generic content that doesn't
align with their individual
learning pace, style, or goals.
There's also a lack of
integration between AI tools
and classroom management
platforms.
2 Idea / Solution Description EduTutor AI is a personalized
education platform powered
by IBM Watsonx’s Granite-
13B model and integrated
with Google Classroom. It
enables customized tutoring
based on a student’s learning
profile, offering targeted
study material, topic-based
assistance, and intelligent
content generation. Built
using FastAPI, Streamlit,
Pinecone, and LangChain, the
system supports real-time AI
interaction, topic suggestion,
and performance tracking.
3 Novelty / Uniqueness - Uses IBM Granite LLMs for
deep contextual
understanding.
- Integrates LangChain for
contextual memory and
document handling.
- Personalized content
generation tailored to user
input and curriculum data.
- Combines AI foundation
models with real-world
education APIs (Google
Classroom).
4 Social Impact / Customer EduTutor AI democratizes
Satisfaction access to high-quality
education by offering
scalable, intelligent tutoring
to students regardless of
their location or background.
It promotes inclusive
education and reduces the
dependency on expensive
private coaching. Teachers
also benefit from automation
and better insights into
student progress.
5 Business Model (Revenue - Freemium model: Basic
Model) access for free; premium
features such as advanced
analytics, priority AI support,
and curriculum planning tools
for a fee.
- Subscription plans for
schools/institutions.
- Custom enterprise solutions
for educational platforms and
edtech companies.
6 Scalability of the Solution EduTutor AI is built using
scalable cloud-native
technologies (IBM Cloud,
FastAPI, Pinecone). The
modular architecture allows
easy integration with more
LLMs, learning platforms, and
languages. It can support
millions of users with
minimal latency and be
deployed globally with
regional language
customization.
