Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Construction • 24 Painters

Case Study 51: Paint Contractor

Marketing-optimized case study for Canadian SMBs.

$96,000
Annual Savings
440%
ROI
2.9 months
Payback
Construction • 24 Painters
Industry Focus

Executive Summary

Visual Measuring: Computer vision analyzes property photos to calculate paintable surface areas, identify prep work needs (caulking, patching), and count openings. Generates material lists.

Challenge

Solution

  • Visual Measuring: Computer vision analyzes property photos to calculate paintable surface areas, identify prep work needs (caulking, patching), and count openings. Generates material lists.
  • Color Matching: AI helps customers visualize paint colors on their home using uploaded photos. Suggests complementary trim and accent colors.
  • Crew Scheduling: Optimization considers weather forecasts, job locations, crew skills, and project timelines. Automatically reschedules weather-impacted jobs.

Technical Stack

Key Metrics

48
Estimate turnaround reduced from 48 hours to 3 hours
32%
Material waste reduced 32% through accurate measuring
58%
Weather-related delays reduced 58%
4.3
Customer satisfaction improved from 4.3 to 4.8
2
Eliminated 2 FTE estimator roles ($68k savings)

Implementation Timeline

8 weeks including CV model training

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