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Portfolio Details

HomeportfolioStudyable — AI-Powered Homework & Study Assistant
  • Category:
    Artificial Intelligence
  • Software:
    NLP, RAG, ML
  • Clients:
    Mr. Esther Howard
  • Locations:
    6391 Elgin St. Celina, UK
  • Date:
    23/03/2024
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Studyable — AI-Powered Homework & Study Assistant

Client Overview

Modern students face overwhelming academic pressure. Traditional study tools often lack personalization, context
understanding, and real-time support. To solve these problems, we developed Studyable — an AI-powered study assistant
built with NLP, Advanced RAG, and Machine Learning techniques.

Client Requirements

  • Understand student questions naturally
  • Provide accurate homework help
  • Generate explanations and study resources
  • Offer instant essay grading with feedback
  • Create flashcards and study sets automatically
  • Ensure safety, accuracy, and scalability

Solution Delivered

We developed Studyable with three core features:
1. Study Chat — Smart homework assistant
2. Essay Grader — Instant writing analysis
3. Flashcards Generator — AI-created study sets

How the System Works

Discovery & Planning

We analyzed student needs, academic subjects, safety requirements, and platform integration points.

Data Pipeline & RAG Knowledge Base

We built a structured knowledge system including:- Academic facts- Definitions- Writing rules- Subject-specific explanations- Rubrics

Model Engineering & NLP Pipeline

We implemented:- Embedding models for semantic search- Intent classification- Named Entity Recognition- Context-based generation with hallucination reduction

Feature Development

Study Chat:- Step-by-step explanations- Multi-subject support- Multi-turn reasoning

Essay Grader:- Grammar checking- Scoring via ML- Actionable writing feedback

Flashcards:- Concept extraction- Topic-based flashcard sets- Auto-generated Q/A pairs

Testing & Evaluation

We tested across:- 12 academic subjects- Accuracy and clarity testing- Load and latency optimization- Safety and bias checks

Recommendation Engine
Recommendation Engine

After classification, the system provides:- Treatment steps- Organic and chemical options- Preventive strategies- Soil/water adjustmentsData based on:- Rule-based engine- Expert-verified agricultural knowledge

Deployment & Integration
Deployment & Integration

Tools used:- FastAPI backend- TensorFlow Lite mobile models- Docker containers- AWS EC2 and Lambda- CDN acceleration

Testing & Evaluation

94% accuracy in factual answers

91% user satisfaction

70% faster homework completion

Outcome & Impact Of The Project

  • Personalized learning
  • Accurate homework assistance
  • Instant essay grading

Conclusion

Studyable demonstrates our ability to build robust, scalable, and intelligent AI learning tools using NLP, RAG, and ML.
It enhances productivity, supports students, and offers real academic value.