Applicant Tracking System

Tech Stack

The Problem

• HR teams spent days manually reviewing hundreds of resumes per open role before shortlisting began.
• Inconsistent evaluation criteria across reviewers caused qualified candidates to be overlooked unfairly.
• No automated system ranked candidates against specific job description requirements at scale.
• Peak hiring periods generated application volumes that overwhelmed recruitment capacity entirely.
• Manual data entry from resumes into HR systems introduced transcription errors and process delays.

Our Solution

• Built an intelligent ATS using NLP to parse and extract structured data from resumes automatically.
• Implemented a semantic matching engine scoring candidate profiles against job description requirements.
• Designed a ranked candidate leaderboard with transparent scoring breakdowns for fair HR evaluation.
• Automated pipeline stage progression based on configurable score thresholds to reduce manual decisions.
• Created Gemini-powered, role-specific interview question generation customised per candidate profile.

Impact

Reduced initial screening time by 75% while improving candidate-role matching accuracy.