2026
CampusStudy AI
University-focused AI study platform with RAG, web, mobile, backend, workers, and study workflows.
CampusStudy AI is a university-focused AI study platform designed to help students organize learning, generate study support, and interact with AI-powered academic workflows. The project combines a modern frontend, FastAPI backend, worker-based processing, and retrieval-augmented generation concepts to support scalable study experiences.
Generated from project structure
AI Study Platform Concept
Study Planner
AI Assistant
RAG Search
Mobile App
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AI Study Workflows
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RAG Architecture
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Web + Mobile Platform
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FastAPI Backend
Executive Summary
CampusStudy AI is a university-focused AI study platform designed to help students organize learning, generate study support, and interact with AI-powered academic workflows. The project combines a modern frontend, FastAPI backend, worker-based processing, and retrieval-augmented generation concepts to support scalable study experiences.
Problem Statement
Students often use disconnected tools for notes, assignments, study planning, and AI assistance. CampusStudy AI aims to bring these workflows into a unified academic platform with structured study support and intelligent retrieval.
What I Built
AI study workflows
RAG-style learning assistance
Backend workers
Web and mobile platform planning
How It Works
A conceptual workflow showing how the project moves from input to processing and output.
Step 1
Student Uploads / Study Input
Step 2
RAG Retrieval
Step 3
AI Study Assistant
Step 4
Generated Study Output
Step 5
Saved Workflow
Architecture / System Design
A simplified system view of the major project components and how responsibilities connect.
Step 1
Web App / Mobile App
Step 2
FastAPI Backend
Step 3
RAG Layer
Step 4
Worker Queue
Step 5
Study Data / Documents
Technical Implementation
Frontend
- TypeScript interface planning
- Web and mobile study flows
- Minimal academic dashboard patterns
Backend
- FastAPI service layer
- Study workflow endpoints
- Structured backend responsibilities
AI Layer
- RAG-style retrieval
- Context-aware study assistance
- Academic content grounding
Workers
- Background processing
- Async study tasks
- Pipeline-ready architecture
Screenshots & Visuals
Real project screenshots and outputs appear first. Where a project has no existing screenshots, the visuals are grounded diagrams or output previews based on the actual project structure.
Study Dashboard Preview
Grounded dashboard visual based on the real CampusStudy AI web/mobile routes for study planning, materials, AI assistance, and course context.
RAG Retrieval Flow
Workflow diagram based on the implemented retrieval, chunking, citation, and generation service structure in the CampusStudy AI backend.
Background Worker Pipeline
Architecture visual grounded in the FastAPI services and Celery worker tasks used for extraction, processing, and study output generation.
Challenges & Solutions
Challenge
Students often use disconnected tools for study planning, notes, and AI help.
Solution
Designed a unified academic platform concept with AI workflows and retrieval-based assistance.
Challenge
AI output needs context from course material to be useful in an academic workflow.
Solution
Structured the system around a RAG-style retrieval layer that connects responses with study content.
Results / Impact
Demonstrates practical software engineering through modular structure, readable workflows, and clear technical documentation.
Shows ability to convert course and research concepts into working systems with real implementation constraints.