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StudyMate — AI Tutor & Learning Companion

StudyMate is an AI-powered learning platform that turns uploaded course materials into dynamic, personalized sessions—Quick Learn, In-depth Lessons, Mock Exams, and Quick Prep—guided by a lifelike AI avatar that speaks, teaches, and interacts in real time.

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Client

Portfolio / Product Build

Role

Full Stack & AI Developer

Year

2024

Timeline

End-to-end prototype

Industry

EdTech / AI Learning

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Challenge & solution

From static documents to a teacher-like experience students actually want to use.

The Challenge

Engagement without a human in the room

Traditional e-learning tools rarely feel personal. Students lose focus without real-time feedback, and most platforms cannot truly understand uploaded materials, auto-build study sessions, or evaluate learners through dynamic AI quizzes. The goal was a system that ingests documents, generates structured learning paths, and interacts naturally via speech and text—like studying with a real teacher.

The Solution

Conversational AI that actually teaches

StudyMate combines conversational AI, retrieval-augmented generation, and expressive UI. Uploaded PDFs and notes are chunked, embedded, and structured into modules. Learners move through teaching, Q&A, and testing with an animated avatar powered by Azure Speech and OpenAI—raising a hand, reviewing transcripts, extending sessions, and building habits with Calm Study reminders.

Key features

AI tutoring, document intelligence, and tools that keep learners in flow.

AI teaching avatar

Lifelike character with voice and text; gestures and speech via Azure Speech and OpenAI GPT.

Document-to-lesson

Upload PDFs or notes → automatic courses with summaries, lessons, and quizzes via LangChain embeddings.

Learning modes

Quick Learn, In-depth Lesson, Mock Exam, and Quick Prep for every study goal.

Interactive session tools

Raise Hand, transcript & record playback, session timer, and extend time.

Productivity add-ons

Calm Study reminders for consistent habits and focused revision.

Intelligent retrieval (RAG)

Vector search over uploaded content so answers stay grounded in the learner’s materials.

System architecture

Five layers from document ingestion to the real-time learning UI.

01

Document ingestion

Prepares and normalizes uploaded PDFs and notes for processing.

02

RAG pipeline

Chunking, embeddings, vector storage, and contextual retrieval.

03

AI orchestration

GPT-driven dialogue, lesson generation, and dynamic quizzes.

04

Speech & interaction

Avatar animation, Azure Speech synthesis, voice and text I/O.

05

Frontend UI layer

React dashboard, session tools, timers, and learner progress.

Impact

Results & impact

70%

Less manual session setup

4+

Core learning modes shipped

1

End-to-end AI tutor flow

24/7

Avatar-guided study on demand

Tech stack

MERN, LangChain, OpenAI, Azure Speech, and tools chosen for real-time tutoring.

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React.js

· Frontend

Component-based UI for real-time session tools, dashboards, and avatar interactions.

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Node.js

· Backend

REST APIs, auth, file uploads, and orchestration between AI, speech, and the database.

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Express

· Backend

REST APIs, auth, file uploads, and orchestration between AI, speech, and the database.

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MongoDB

· Database

Flexible storage for users, documents, sessions, vectors metadata, and progress.

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OpenAI

· AI / RAG

Embeddings, retrieval, and GPT-driven lesson, quiz, and dialogue generation.

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LangChain

· AI / RAG

Embeddings, retrieval, and GPT-driven lesson, quiz, and dialogue generation.

Azure

Azure Speech API

· Speech & Avatar

Real-time speech synthesis and avatar voice pipeline for natural tutoring.

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NextAuth

· Authentication

Secure sign-in and session management across the MERN stack.

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Vercel

· Hosting

Deploy frontend and containerized services with reliable CI/CD.

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Docker

· Hosting

Deploy frontend and containerized services with reliable CI/CD.

Ready to build your next AI product?

From RAG and avatars to full MERN delivery—I help teams ship intelligent, human-centered learning experiences.