Career hub

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Inspiration

What it does

Inspiration

Many students know they want a good career but don't know what to improve next. They may have a resume, GitHub profile, projects, and certificates, but these are often treated as separate things without a clear picture of their overall career readiness.

This inspired us to build Career Hub — a platform designed to help students understand their current strengths and gaps and turn that information into actionable next steps.

What We Built

Career Hub is an AI-assisted career readiness platform for students and early-career developers.

The platform brings important career activities into one place, including:

• Resume analysis and improvement suggestions
• Career readiness assessment
• Skill-gap identification
• Project and portfolio evaluation
• Interview preparation
• Learning resources and skill-building recommendations
• Career opportunities and challenges
• Progress tracking

The goal is not simply to give students another dashboard, but to help answer one practical question:

«“What should I do next to become more job-ready?”»

How We Built It

We designed Career Hub as a modern web/mobile-oriented application with separate frontend and backend components. The project uses a structured application architecture so that features such as resume processing, career assessments, recommendations, and user progress can be developed and tested independently.

AI capabilities are intended to support tasks such as extracting useful information from resumes, identifying potential skill gaps, generating personalized recommendations, and assisting with interview preparation.

A major focus during development was making sure that the application should show real data and real results rather than simulated success states.

What We Learned

Building Career Hub taught us that creating a useful AI product involves much more than connecting an AI model to an interface.

We learned about:

• Designing reliable frontend and backend workflows
• Handling uploaded documents and user data
• Building meaningful career-readiness metrics
• Integrating AI into practical user workflows
• Testing features across different states and devices
• Identifying and fixing unreliable or misleading application behavior
• Improving UX based on actual usage rather than assumptions

Most importantly, we learned that trust is a core feature of an AI application. If an application says something is completed, analyzed, or connected, the underlying system must actually support that claim.

Challenges

One of our biggest challenges was ensuring that different parts of the application worked together reliably. Resume processing, authentication, AI services, user data, and progress tracking each introduced different technical issues.

We also faced challenges around avoiding placeholder functionality and making the application behave consistently across development and mobile environments.

These challenges changed our approach: instead of focusing only on adding more features, we focused on testing, reliability, usability, and building features that provide genuine value to students.

Vision

Career Hub aims to become a practical career companion that helps students move from “I don't know what to improve” to “I know my next step and I can measure my progress.”

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for Career hub

Built With

• and
• express.js
• firebase
• gemini
• github
• google
• node.js
• react
• rest-apis
• tailwind-css
• typescript
• vite