How an AI-Driven Smart Hiring Assistant Revolutionized Candidate Screening and Reduced Time-to-Hire by Over 50%
Client Overview
An international staffing and recruitment agency managing thousands of candidate applications each month, struggling with inconsistent resume screening and long time-to-hire cycles.
Project Goal
To create a Smart Hiring Assistant that automates resume parsing, skill extraction, and candidate ranking — enabling recruiters to focus on interviews rather than data entry.
Approach
We mapped the end-to-end hiring workflow — from resume intake to interview scheduling — and designed an AI-powered evaluation pipeline that integrates machine learning with recruiter decision logic.
The focus was on ensuring both high accuracy and transparency in candidate scoring.
Solution
- Resume Parsing: GPT-4 extracts structured data (skills, experience, education) from resumes in PDF and DOCX formats.
- Semantic Skill Matching: Fine-tuned BERT embeddings compare candidate profiles to job descriptions for deep contextual matching.
- Candidate Scoring: Weighted ranking system scores applicants on relevance, seniority, and cultural fit.
- Automated Scheduling: Integrated with Google Calendar to coordinate interviews between candidates and recruiters.
Value Delivered
The AI assistant eliminated manual screening, improved match accuracy, and created a unified data pipeline — transforming recruitment into a data-driven, insight-led process.
Quantified Outcomes
| Metric | Before | After |
|---|---|---|
| Resume screening time | 30 minutes | 2 minutes |
| Match precision | 70 % | 94 % |
| Time-to-hire | 21 days | 9 days |
