Executive Summary

  • Client: A multinational corporation hiring thousands of candidates annually.
  • Challenge: Manual resume screening was time-consuming, inconsistent, and costly.
  • Solution: AI-powered resume parsing and candidate matching system.
  • Results:
    • 80% reduction in screening time.
    • 3x faster candidate shortlisting.
    • 20% improvement in hiring accuracy by matching candidates to job roles based on AI-driven insights.

“American Chase’s AI-driven hiring platform transformed our recruitment process, making it faster, smarter, and more efficient.”

–  Director of Talent Acquisition

Client Background

Who They Are

A multinational company with a diverse workforce across multiple industries, hiring thousands of employees annually for various roles, from entry-level to executive positions.

Pre-Challenge State

  • HR teams manually reviewed thousands of resumes for each job posting.
  • Screening was subjective, leading to inconsistencies.
  • High time-to-hire resulted in lost productivity.

“Our recruitment team was overwhelmed with resumes. Manual screening led to delays, inconsistencies, and missed out on great candidates.”

–  Recruitment Lead

The Challenge

Pain Points

  1. High Volume of Applications: 10,000+ resumes per month led to bottlenecks.
  2. Inconsistent Screening: Recruiters had different criteria, leading to bias.
  3. Long Time-to-Hire: Manual shortlisting delayed hiring decisions.

Business Impact

  • Delayed hiring cycles, affecting project timelines.
  • Qualified candidates overlooked due to inefficient screening.
  • High recruitment costs due to excessive manual effort.

Client Goals

  • Automate resume screening and ranking.
  • Improve candidate-job matching accuracy.
  • Reduce time-to-hire while maintaining hiring quality.

The Solution

Approach

  • Implemented an AI-powered resume screening and ranking system to analyze and filter candidates efficiently.
  • Used Natural Language Processing (NLP) and machine learning to match resumes with job descriptions.
  • Enabled bias-free candidate evaluation based on data-driven insights.

Tools & Technologies Used

  • AI Resume Parsing: OpenAI GPT + BERT (for extracting skills, experience, and education).
  • Candidate Ranking AI: Hugging Face Transformers (for semantic job-resume matching).
  • Cloud AI Services: Azure OpenAI Service (for scalable resume processing).
  • Automation & Integration: LangChain (for workflow automation with ATS).

Key Features

  1. Automated Resume Parsing: AI extracts key details like experience, skills, and education.
  2. AI-Driven Candidate Matching: NLP algorithms rank resumes based on job descriptions.
  3. Bias-Free Screening: AI removes human bias, ensuring fair hiring decisions.
  4. ATS Integration: Seamlessly integrates with the client’s existing Applicant Tracking System (ATS).

Implementation Process

Timeline

  • Phase 1 (Analysis & Data Collection): 3 weeks of gathering historical hiring data.
  • Phase 2 (AI Model Training & Development): 2 months for model fine-tuning.
  • Phase 3 (Pilot Testing & Optimization): 6 weeks of real-world testing with HR teams.

Team Structure

  • AI Engineers
  • Data Scientists
  • HR Tech Consultants
  • Cloud Architects

Overcoming Hurdles

  • Challenge: HR teams were hesitant to trust AI-driven decisions.
    • Solution: Implemented an AI-assisted review instead of full automation.
  • Challenge: Complex resumes with non-standard formatting.
    • Solution: Used advanced NLP models for improved parsing accuracy.

Results and Impact

Quantitative Metrics

80%

Faster Screening

Reduced manual effort in resume filtering.

3X

Faster Candidate Shortlisting

AI matched candidates instantly.

20%

More Accurate Hiring

AI matched candidates based on skills rather than keywords.

Qualitative Benefits

  • 🌍 Scalability: Handled high application volumes efficiently.
  • ⚖️ Diversity & Inclusion: Bias-free AI screening led to a more diverse workforce.

“With AI-driven hiring, we focus more on interviewing the best talent rather than sorting resumes. This has improved our hiring quality significantly.”

–  HR Director

Project Snapshot

  • Client: Multinational Corporation
  • Project Duration: 4 months
  • Technologies: OpenAI GPT, BERT, Hugging Face Transformers, Azure OpenAI Service, LangChain
  • Key Metric: 80% reduction in screening time

“American Chase’s AI-powered recruitment automation transformed our hiring process, making it faster, fairer, and more efficient.”

Summary

Built an AI-driven HR solution to screen resumes and match candidates, reducing hiring time by 60%.