Case study · 01 / 06

SkillVision AI

Intelligent Career & Skill Intelligence System

Stack: React · TypeScript · Vite · Tailwind CSS · Express · Google Gemini API
Links: GitHub Live Demo

Fig. 01 — SkillVision AI · conceptual render

Screenshots

Actual captures from the running application.

Fig. 01.1 — SkillVision placement cockpit and analytics dashboard

Fig. 01.2 — SkillVision AI mock interview arena

Fig. 01.3 — SkillVision AI job matching hub

Overview

An AI-powered career copilot and placement platform — real-time resume parsing, ATS scoring, skill-gap analysis, milestone roadmaps, mock interviews, and AI job matching, powered by Google Gemini.

Problem

Job seekers can't see how their skills map to real roles, and generic career advice ignores what's actually on their resume.

How it works

01
Resume parsing
02
ATS scoring (0–100)
03
Skill-gap detection
04
Roadmaps + interviews
05
Job matching

SkillVision parses resumes into structured profiles, scores ATS compatibility, maps skill gaps against target roles, and generates milestone roadmaps, mock interviews, and matched job leads — with RAG retrieval grounding its guidance.

Key features

ATS resume scoring (0–100) + parsing
Skill radar + gap identification
Milestone roadmaps + streaks
Mock interview arena with AI critique
AI job matching + application tracking
RAG-based knowledge retrieval

Lessons learned

Lesson 1: Grounding guidance in the user's own parsed resume beats generic career advice.
Lesson 2: A quantified ATS score turns vague resume feedback into actionable fixes.
Lesson 3: Mock interviews need structured critique loops, not just Q&A.
Lesson 4: RAG keeps fast-moving career knowledge current without retraining.
Lesson 5: Milestones and streaks keep long learning journeys alive.

My contribution — Designed and built the platform — resume parsing and ATS scoring flows, skill radar and gap logic, roadmap and interview modules, job-matching engine, and RAG-grounded career guidance.