Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Staffing • 220 Active Clients

Case Study 23: Recruitment Agency

Marketing-optimized case study for Canadian SMBs.

$118,000
Annual Savings
420%
ROI
3.1 months
Payback
Staffing • 220 Active Clients
Industry Focus

Executive Summary

Resume Screening: AI parses resumes, extracts skills/experience, and matches against job requirements. Scores candidates and identifies top matches within minutes of application.

Challenge

Solution

  • Resume Screening: AI parses resumes, extracts skills/experience, and matches against job requirements. Scores candidates and identifies top matches within minutes of application.
  • Candidate Engagement: Automated SMS campaigns keep passive candidates warm with relevant job alerts. Chatbot answers candidate questions about positions, salary, and application status.
  • Interview Scheduling: AI coordinator finds mutual availability between candidates, hiring managers, and panel members. Books video calls and sends reminders.

Technical Stack

Key Metrics

3.2
Time to first candidate submission reduced from 3.2 days to 0.4 days
47%
Candidate engagement rate improved 47%
45
Interview scheduling time reduced from 45 minutes to 3 minutes
38%
Placements per recruiter increased 38%
3
Eliminated 3 FTE sourcing specialist roles ($98k savings)

Implementation Timeline

10 weeks including ATS integration and recruiter onboarding

Ready to map your SMB workflow?

We can estimate ROI and scope the right MapleWorkSuite configuration for your team.

Start a Custom Case Study