Inspiration
Job portals, course platforms, and resumes all exist—but they don’t talk to each other. Fresh graduates are expected to independently connect job requirements, skills gaps, past experiences, and learning resources across multiple platforms.
The TechFest problem statement highlighted a core issue we strongly relate to: career data is fragmented, static, and non-actionable. We wanted to solve this not by adding another job board, but by building a system that connects skills, experiences, projects, and learning into one evolving career profile.
What it does
Unified Career Platform transforms fragmented career data into a living, skill-based roadmap for employment.
At its core, the platform centralizes:
- User skills, experiences, and completed projects
- Job requirements with transparent skill breakdowns
- Application status tracking across roles
What makes it different is that everything is connected through a shared skill base.
When users follow a personalized roadmap:
- Completing a course or project automatically updates their skill profile
- Skill gaps for target jobs shrink in real time
- Resume matching improves as skills and experiences grow
Additional AI-powered features include:
- Resume-to-job matching with explicit skill gap analysis
- Personalized career roadmaps with embedded courses and hands-on projects
- AI-generated referral request emails
- AI practice resources for interview and technical preparation
Instead of static recommendations, the platform continuously adapts as the user progresses.
How we built it
We designed the system around a centralized skill graph that links users, jobs, roadmaps, and learning resources.
Key technical components:
- A unified data layer combining job listings, required skills, user profiles, and applications
- Skill normalization across jobs, resumes, projects, and courses
- A roadmap engine that maps:
- Current skills → missing skills → recommended courses & projects
- Current skills → missing skills → recommended courses & projects
- Real-time skill updates when roadmap tasks are completed
- AI models for resume matching, referral writing, and practice generation
This architecture ensures that every feature—from filtering jobs to writing referrals—operates on the same source of truth.
Challenges we ran into
The biggest challenge was making career data interoperable. Job descriptions, resumes, and courses all describe skills differently, yet the system needs to reason over them consistently.
Another challenge was UX complexity. With many interconnected features, we had to ensure the interface remained clear at first glance, without overwhelming users with data.
Accomplishments that we're proud of
- Built a truly centralized career data system, not just a feature collection
- Created a roadmap where learning progress directly updates employability
- Integrated projects into roadmaps, not just courses
- Went beyond job search by supporting preparation, referrals, and tracking
- Delivered a modern, intuitive UI that users can understand immediately
What we learned
We learned that effective career platforms must be stateful and adaptive, not static.
Technically, we gained experience in:
- Designing shared data models across AI-driven features
- Aligning machine intelligence with explainable outputs
- Building systems where progress feeds back into recommendations
From a design perspective, we learned that clarity beats completeness—users value knowing what to do next more than seeing everything at once.
What's next for Unified Career Platform
Next, we plan to:
- Expand job and course data sources in Singapore
- Improve roadmap personalization based on learning pace and career intent
- Add analytics to visualize job readiness and skill coverage
- Enable mentor and referral network matching
Our goal is to evolve Unified Career Platform into a career operating system, where skills, learning, and employment are continuously connected.
Built With
- next.js
- openai
- postgresql
- prisma
- resend
- s3
- tailwind
- zod
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