Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Real Estate • 340 Units

Case Study 10: Property Management

Marketing-optimized case study for Canadian SMBs.

$105,000
Annual Savings
455%
ROI
2.8 months
Payback
Real Estate • 340 Units
Industry Focus

Executive Summary

Tenant Screening: Automated background check, credit report, employment verification with ML-based risk scoring. Reduces screening time from 3 days to 4 hours.

Challenge

Solution

  • Tenant Screening: Automated background check, credit report, employment verification with ML-based risk scoring. Reduces screening time from 3 days to 4 hours.
  • Maintenance Routing: AI routes repair requests to appropriate contractors based on issue type, location, contractor availability, and historical performance.
  • Rent Collection: Automated reminder sequences with escalation workflows. Payment portal with multiple options reduces manual payment processing.

Technical Stack

Key Metrics

8.2%
Vacancy rate reduced from 8.2% to 7.0% ($68k additional revenue)
87%
Tenant screening time reduced 87%
2.1
Maintenance response time improved from 2.1 days to 0.6 days
94%
Rent collection rate improved from 94% to 98%
4
Administrative staff reduced from 4 FTE to 2.5 FTE

Implementation Timeline

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