Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Creative Services • Wedding & Portrait Photography

Case Study 52: Photography Studio

Marketing-optimized case study for Canadian SMBs.

$68,000
Annual Savings
490%
ROI
2.4 months
Payback
Creative Services • Wedding & Portrait Photography
Industry Focus

Executive Summary

Photo Culling & Selection: AI analyzes RAW files to identify best shots based on focus, exposure, composition, and facial expressions. Flags duplicates and technical issues. Reduces culling time by 85%.

Challenge

Solution

  • Photo Culling & Selection: AI analyzes RAW files to identify best shots based on focus, exposure, composition, and facial expressions. Flags duplicates and technical issues. Reduces culling time by 85%.
  • Automated Editing: ML applies consistent color grading and exposure adjustments based on photographer's style. Handles batch processing with 92% acceptance rate.
  • Client Gallery Management: Automated gallery creation with AI-generated captions. Facial recognition groups family members. Recommends print packages based on selections.

Technical Stack

Key Metrics

6
Photo culling time reduced from 6 hours to 50 minutes per event
73%
Editing time reduced 73% (initial edits automated)
3
Gallery delivery time reduced from 3 weeks to 4 days
4.4
Client satisfaction improved from 4.4 to 4.8
35
Capacity increased from 35 to 52 bookings annually ($68k revenue increase)

Implementation Timeline

Week 1-2

Training ML model on 5,000 edited photos

Week 3-4

Lightroom integration and workflow setup

Week 5

Gallery automation and facial recognition

Week 6

Testing and refinement

Week 7

Production launch

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