SLOS

An intelligent Student Life Operating System that turns academic chaos into prioritized tasks, personalized plans, and focused action.

Comment

Inspiration

As a final-year B.Tech Computer Science Engineering student, I have experienced firsthand how difficult student life can become when assignments, exams, projects, internships, deadlines, and personal responsibilities all start competing for attention.

Looking back at my university journey, I realized that I have collected many lessons and, honestly, a few regrets about how I managed my time and priorities.

I cannot go back and change those experiences. But I can try to make sure other students don't have to face the same problems.

One thing my father has always told me is:

"If you are sincere and dedicated, you can achieve anything in this world."

I believe sincerity and dedication become much more effective when you know what to prioritize and where to spend your time.

That idea became the foundation of SLOS — Student Life Operating System.

Instead of making students use one application for tasks, another for schedules, another for focus sessions, another for productivity tracking, and separate AI tools for understanding academic documents, I wanted to bring these concepts together into one student-focused system.

The goal was simple:

Turn academic chaos into clarity.

What it does

SLOS (Student Life Operating System) is a cross-platform productivity application designed specifically around the challenges students face in managing their academic lives.

SLOS helps students:

  • Create and manage academic tasks
  • Organize assignments, exams, projects, and deadlines
  • Prioritize tasks based on urgency and importance
  • Plan their workload
  • Track task completion and progress
  • Enter focused work sessions through Focus Mode
  • View upcoming responsibilities from a single dashboard
  • Use AI to analyze academic information and generate actionable tasks

AI-Powered Academic Planning

One of the main features of SLOS is its AI integration.

Students can provide information such as:

  • Exam timetables
  • Syllabus documents
  • Assignment PDFs
  • Project requirements
  • Screenshots containing deadlines or schedules

The AI analyzes the information and helps transform unstructured information into structured tasks.

For example, if a student provides an examination timetable along with a syllabus, SLOS can help generate relevant study tasks and organize them according to deadlines and priority.

Instead of simply asking:

"What tasks do I have?"

SLOS is designed to help answer:

"What should I work on next?"

Intelligent Prioritization

SLOS is also influenced by productivity techniques such as the Eisenhower Matrix, which separates tasks based on:

  • Important + Urgent
  • Important + Not Urgent
  • Not Important + Urgent
  • Not Important + Not Urgent

This helps students focus on what actually matters instead of treating every task as equally important.

Focus Mode

Once a student decides what to work on, SLOS provides a dedicated Focus Mode where they can work on a specific task and track their focused time.

The idea is to create a complete workflow:

Capture → Prioritize → Plan → Focus → Complete → Analyze

How we built it

SLOS was built as a full-stack cross-platform mobile application.

Frontend

The mobile application was developed using:

  • React Native
  • Expo
  • TypeScript

I initially considered building SLOS with SwiftUI because of my experience as an iOS developer.

However, since students use different platforms, I chose React Native to make the application accessible across both Android and iOS.

Backend

The backend was built using:

  • Node.js
  • TypeScript
  • REST APIs
  • JWT Authentication

The backend handles authentication, task management, academic data, AI requests, and communication between the mobile application and database.

Database

SLOS uses:

  • PostgreSQL
  • Prisma ORM

The database stores structured information such as users, courses, tasks, deadlines, events, and other application data.

AI

AI capabilities were integrated using the OpenAI API.

The AI layer is designed to process academic information and transform it into useful structured information rather than simply generating a conversational response.

The overall architecture follows:

Student
   ↓
React Native + Expo
   ↓
REST API
   ↓
Node.js Backend
   ↓
┌───────────────┬────────────────┐
│               │                │
PostgreSQL    AI Service      Authentication
│               │                │
Prisma        OpenAI API        JWT
└───────────────┴────────────────┘

Built With

Share this project:

Updates