Ghost Scout | Privacy-First AI Job Matcher for Tech Professionals

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 2: Side Hustle

What I Built

GhostScout is a privacy-focused, high-end job matching web tool designed for developers and tech professionals who want AI-powered resume analysis and recruiter outreach drafting without vendor lock-in.

• The Problem It Solves: Traditional job boards and AI resume matchers force users to upload sensitive career history and personal data into black-box, closed ecosystems. GhostScout gives users full control by utilizing open-weight models for precise resume-to-job scoring and customized outreach generation.
• Who Pays for It? Active job seekers, freelancers, and tech professionals who want an edge in their job search while maintaining data sovereignty. It features a freemium model offering 3 free scans, followed by a $9/month "Pro Scout" subscription via Stripe.

Demo

Live App: ghostscout.thehmv.tech

Code

GitHub Repository: AmjustGettingStarted/Job-Scout

How I Built It

GhostScout is built for speed, responsiveness, and a distinct visual identity:

• Frontend & UI: Next.js (App Router), Tailwind CSS, Shadcn UI primitives, Framer Motion for animations, and Lenis for smooth momentum scrolling.
• Aesthetic: A clean, paper-sculpted design system with origami-inspired geometric accents, stark typography, dynamic pill badges, and a coral-and-sand palette (#ff6b6b, #f4a261).
• AI Backend: Dual-mode inference supporting local open-weight models via Ollama or hosted inference via the Tinker API for private resume scoring and outreach email drafting.
• Monetization: Stripe Checkout integration (Test Mode) handling secure $9/month recurring subscriptions.
• Infrastructure: Deployed as a dynamic Web Service on Render with custom domain DNS routing through get.tech and automated SSL certification.

Why Does Open Innovation Matter?

Open innovation is critical for tools that process deeply personal data like resumes, career histories, and salary expectations. Relying on closed, proprietary APIs means handing over private professional data to third-party black boxes with opaque data retention policies.

Open-weight models (run locally via Ollama or transparently via Tinker) make true data privacy possible, letting users keep absolute ownership of their career footprint.

Prize Categories

• Main Challenge: Side Hustle (Hacktoberfest Open-Source AI Challenge Week 2)
• Partner Categories:
  • Best Use of Render: App hosted live as a dynamic Web Service on Render.
  • Best Use of Tinker: Powered by Tinker API for hosted open-weight inference.
  • Best Use of a .tech Domain: Deployed live on ghostscout.thehmv.tech.

Comments

[Dalbaeb]

good