How I Built Pathway AI: A Full-Stack SaaS Platform in 1 Month

How I Built Pathway AI: A Full-Stack SaaS Platform in 1 Month

I built Pathway AI, a SaaS platform for international students planning their study abroad journey, in roughly one month. Here's how I went from concept to live product using Next.js, Supabase, and TypeScript.

The Problem

International students face overwhelming challenges when planning to study abroad: fragmented information, biased agents, unclear visa requirements, and no clear way to compare destinations. I wanted to build something that solved this.

The Stack

• 
  Frontend: Next.js (App Router) + TypeScript + Tailwind CSS


• 
  Backend: Supabase (PostgreSQL) + Edge Functions


• 
  AI: Gemini API


• 
  Deployment: Vercel


• 
  Monitoring: Sentry for error tracking


• 
  Rate Limiting: Upstash Redis

Architecture Overview

1. User Authentication

Used Supabase Auth with Google and GitHub OAuth. This approach prevents spam and ensures data quality:

• 
  No password management — Students don't have to remember another password


• 
  Validates real emails only — Blocks temporary/trash email services (10minutemail, temp mail, etc.)


• 
  Prevents fake accounts — Reduces spam signups and ensures only genuine users access the platform


• 
  Better data quality — No throwaway accounts cluttering your user database
  

// lib/supabase.ts

import { createClient } from '@supabase/supabase-js';



export const supabase = createClient(

  process.env.NEXT_PUBLIC_SUPABASE_URL!,

  process.env.NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY!

);

2. Database Schema

Built around student profiles and their journey:

profiles → stores all student data (destination, budget, course, goals)

visa_checklists → tracks document completion

sops → stores Statement of Purpose drafts

resumes → resume builder data

countries / cities / courses → reference data for exploration

Row-Level Security (RLS) ensures students only see their own data.

3. Core Features

SOP Builder

Students fill their profile → system generates a Statement of Purpose draft using structured templates.

// lib/sop-generator.ts

export function generateSOP(profile: Profile): string {

  return `

Dear Admissions Committee,



I am applying to ${profile.course_name} at ${profile.preferred_university} 

in ${profile.target_destination} because...

  `;

}

Resume Builder

Similar approach — profile data → formatted resume sections → PDF export.

Career Advisor

Core system provides personalized guidance using rule-based logic tailored to student profile + target destination.

Production: Always uses reliable rule-based engine — fast, cost-free, predictable responses.

Self-hosted / Development: Optional Gemini API integration available. If you run this locally and add a Gemini API key, the Advisor can enrich responses with real AI personalization. This is gated behind a NODE_ENV=development flag — production deployments never call AI APIs.

Visa Checklist

Students track required documents for their target country. Sections stored as JSON, items marked complete as they prepare.

Country/City Explorer

Browse destinations side-by-side, compare costs, safety scores, job prospects, PR pathways.

4. Key Technical Decisions

Why Supabase over Firebase?

• PostgreSQL for complex queries (joins across countries/cities/courses)


• RLS for built-in data isolation


• Better for structured reference data

Why Vercel?

• Seamless Next.js deployment


• Serverless functions for contact forms


• Auto-scaling, zero ops overhead

Why TypeScript everywhere?

• Caught ~30% of bugs before runtime


• Server/client type safety


• Easier refactoring at scale

5. Deployment & Monitoring

Vercel: Automatic deployments on git push. Environment variables stored securely.

Sentry: Catches errors in production. Configured at build time.

Upstash Redis: Rate limits API calls (contact form, future exports).

Challenges & Lessons

Challenge 1: Handling complex JSONB data

Storing skills, experiences, languages as JSON meant flexible schema but harder migrations. Solved by keeping schema versions in mind from day one.

Challenge 2: Ensuring data consistency

With RLS policies, had to test extensively to prevent data leaks. Built a checklist: test as authenticated user, test as different user, test with no auth.

What I'd Do Differently

1. 
   Use migrations from day one — Supabase migrations would've saved rollback headaches


2. 
   Mock Gemini responses earlier — Would've validated UX before API costs


3. 
   Build analytics sooner — Knowing which features students use most helps prioritize


4. 
   Deploy to staging earlier — Caught mobile issues much later than ideal

Live Demo

Check it out: pathway-ai-olive.vercel.app

GitHub: github.com/krishna-builds-dev/pathway-ai

Key Takeaways

• 
  Supabase + Next.js is a powerful combo for rapid SaaS development


• 
  Rule-based logic over AI when it's reliable enough — simpler, cheaper, predictable


• 
  Type safety saves time — TypeScript caught real bugs

What's Next?

• Mobile app (React Native)


• Integration with university APIs


• Community features (peer advice)

Have you built a SaaS from scratch? Drop your stack and lessons in the comments below!

I'm a full-stack developer focused on Next.js + Supabase. Open for freelance work. Follow on GitHub or LinkedIn