Team (66) _ (Career-Tinder)

Career Tinder: Stop Guessing. Start Growing. One Swipe at a Time. The Problem Early-stage university students face a fragmented, overwhelming approach to career planning. They're expected to: Browse multiple job portals independently Decode vague job requirements Guess whether they're qualified Choose between applying now or upskilling first—with no clear guidance This leads to two common outcomes: students either apply blindly to hundreds of roles or delay applications due to lack of confidence. The core issue isn't lack of information—it's lack of actionable clarity. Our Mission Career Tinder closes the skills-to-job gap by transforming fragmented career data into personalized, confidence-driven roadmaps. Instead of asking "What jobs exist?", we help students answer: Where do I stand right now? Which roles should I pursue? What should I do next to improve my chances? The Solution Career Tinder is an AI-powered career discovery and readiness platform designed for Year 1 and Year 2 students, where exploration matters more than optimization. Our system integrates job data from multiple platforms with user profiles, skill matching, gap analysis, and AI-driven validation through interactive assessments. Powered by OpenAI's GPT-4 and GPT-4o models, we deliver intelligent, context-aware career guidance. Core Features

1. Profile-First Personalization Users build their foundation by entering: Year of study Current skills and certifications Target roles This profile becomes the anchor for all matching, recommendations, and AI reasoning—ensuring every insight is personalized, never generic.
2. Swipe: Intelligent Job Matching Our key differentiator is our job matching experience. Rather than endless scrolling, users swipe through ranked opportunities. Each job card displays: Match percentage based on skills and role alignment Missing skills ranked by importance Clear action paths: Apply now, Upskill first, or Save for later When users click "Apply" for a particular job, a detailed overlay appears showing: Current match score vs. projected match in 5 years (if they don't continue upskilling) Career timeline that predicts future market trends and provides smart insights Skills to develop with suggested courses This transforms job discovery from guesswork into guided decision-making and strategic preparation.
3. Discover: Confidence Verification Through Games Our confidence verification layer doesn't assume readiness—it validates it through: MCQ-based skill checks Case-study simulations featuring real problems students might face in that particular industry Games are dynamically generated based on the selected job title, user's current skills, and chosen difficulty level. After each session, users receive: A confidence score Cumulative performance tracking This makes career readiness feel earned, measurable, and motivating.
4. Coach: AI Career Advisor The Coach serves as a personalized AI mentor, reasoning over: User profile and CV content Current market opportunities The Coach can: Recommend best-fit specializations Suggest relevant internships Bridge pathways to adjacent roles Propose targeted upskilling plans This delivers context-aware career reasoning, not static advice.
5. Tracker: From Insight to Action Jobs can be tracked across stages: Upskilling In Progress Accepted Rejected This creates a closed feedback loop between learning, applying, and outcomes—helping users stay intentional rather than reactive.

Built With

• next.js
• node.js
• openaiapi
• typescript