LockedIn: an AI-Native Job Board app

LockedIn - Project Documentation
Team : Adil Zainul Syed, Korou Kshetrimayum, Mohith Sajeeth, Mohammed Zaid Chowdhary

LockedIn is an AI-native hiring marketplace designed to replace traditional, resume-driven job boards and saturated platforms like LinkedIn, where applicants and recruiters share the same cluttered experience and hiring often happens through cold emails or commenting “interested” on job posts.
LockedIn simplifies hiring by enabling recruiters and job seekers to match based on real skills, portfolios, and predicted success. Job seekers swipe through job openings based on their interests and skill levels, while recruiters are shown curated candidate profiles in a Hinge-style swipe interface, allowing them to evaluate talent through rich, visual portfolios rather than static resumes.

Problem: AI-Native Job Board
Traditional job boards rely heavily on resumes and keyword matching. This leads to:
• Poor candidate-role fit
• High hiring friction
• Time-consuming screening
• Low hiring accuracy
They treat all candidates as comparable on paper, rather than as individuals with different strengths and proven abilities.

Solution:
LockedIn uses AI to analyze:
• Summarized Candidate portfolios
• Project history
• Skills and endorsements
• Company-defined outcome tracks
This enables intelligent, swipe-based matching between candidates and roles, focusing on who is most likely to succeed rather than who matches the most keywords.


Features
• Hinge-style recruiter swipe UI for fast, intuitive candidate discovery
• AI-generated capability profiles built from portfolios, GitHub, and work history
• Outcome-based job definitions instead of vague job titles
• ATS optimization feedback to improve candidate portfolios
• Multiple portfolios per candidate, allowing job seekers to create different profiles for different career paths
(e.g., one for SDE roles, one for animation, one for music, etc.)
• Real-time matching engine powered by AI predictions


Business Model
• Recruiter subscriptions
• Pay-per-hire success fees
• Premium candidate profiles and visibility


Tech Stack
• Frontend: React
• Backend: Node.js, FastAPI
• Database: MongoDB, PostgreSQL
• AI Layer: Large Language Models (LLMs), Machine Learning–based matching and prediction models