SkillSprint - Byte3

Inspiration: We noticed that many learners who enroll in online technical certifications never complete them. While platforms like AWS offer valuable certifications, they primarily highlight the skills gained, not the economic outcomes tied to completing each stage. There’s a disconnect between earning certifications and clearly understanding the real career and salary progression that follows. We wanted to bridge that gap by connecting certification progress directly to tangible career milestones.

Our solution: We built skillsprint, a B2B SaaS platform designed for certification providers like AWS. The platform transforms certification pathways into structured economic progression models. Instead of only showing skills learned, skillsprint shows: • Salary progression at each certification stage • Degree requirements (required vs preferred) • Interview milestones throughout the journey • AWS job eligibility tied to certifications • Recruiter visibility and outreach signals This creates value for both learners and companies: • Learners gain clarity on how certifications translate into real-world career growth. • Certification providers increase completion rates by making ROI transparent. • Recruiters gain structured visibility into certified talent and performance tiers.

What It Does Skillsprint simulates how AWS could embed a progression layer into its certification ecosystem. On the learner side, users can: • View official AWS courses required for each certification • Track their certification-based career progression • See estimated salary increases as they move up stages • View interview events that appear at key certification levels • Browse an AWS-only job center that clearly outlines certification and degree requirements On the recruiter side, the platform provides: • A structured talent pool of certified professionals • Performance tiers (Bronze / Silver / Gold) • Resume viewing capability • Certification-based filtering The result is a clear path: Certification → Salary Growth → Interview Opportunities → Job Eligibility

How We Built It We began by designing the system architecture and UML structure to clearly define relationships between certifications, courses, jobs, candidates, and progression stages. For the tech stack: • Frontend: React, Vite, Tailwind CSS • Backend (demo-level data management): Supabase • AI tooling: Gemini for intelligent insights and data structuring After defining the data model, we implemented the UI layer and connected all components into a working MVP prototype.

Challenges We Ran Into • API key configuration issues delayed integration testing. • Refining the product focus took time, we initially explored broader ideas before narrowing to an AWS-specific course program. • Structuring progression logic in a realistic but demo-friendly way required careful iteration.

Accomplishments We’re Proud Of • Building a fully functional technical MVP • Creating a realistic enterprise-grade UI • Translating a real-world dropout problem into a structured economic progression solution • Connecting certifications directly to jobs and degree requirements

What We Learned • Certification dropout rates are higher than expected. Many learners lack clarity on the long-term payoff. • Economic visibility is a strong motivational driver. • Structuring progression stages carefully can make career growth feel tangible. • Working with Agentic AI tools accelerated our development process and helped us prototype quickly.

Built With

• css
• framer-motion
• github
• html
• javascript
• lucide-icons
• openai
• react
• react-router
• tailwind-css
• typescript
• vite