Case Studies
Real photographers. Real workflows. Real results.
Wedding Photographer
2,400 images per event — delivered in half the time
Scenario
A full-time wedding photographer shooting 40+ weddings per year was spending 8–12 hours per event on culling and post-processing alone. The backlog was growing faster than the delivery schedule.
Challenge
Manually reviewing thousands of images per wedding, inconsistent culling decisions under fatigue, and no structured metadata for client archives.
Result
Post-processing time reduced by 70%. Consistent AI-driven culling with decision rationale. Every delivered image tagged with structured metadata for future retrieval.
Portrait Studio
15 sessions per week — zero bottleneck
Scenario
A busy portrait studio running 15 sessions weekly across two photographers needed a streamlined way to process, tag, and deliver images without a dedicated post-production team.
Challenge
Multiple photographers with different culling styles, no standardised metadata, and a fragmented tool chain spanning four different applications.
Result
Unified workflow across both photographers. Style-first AI learned each photographer's preferences independently. Structured metadata embedding eliminated manual tagging entirely.
Event Photographer
5,000+ images per event — same-day delivery
Scenario
A corporate event photographer needed to deliver curated galleries within hours of the event ending. Traditional workflows made same-day delivery impossible for large-scale events.
Challenge
Extremely high volume with tight deadlines. No time for manual culling. Clients expected consistent quality across thousands of images with full metadata for press use.
Result
AI culling processed 5,000 images in under 30 minutes. Enhancement recommendations applied in batch. Full IPTC metadata embedded automatically — enabling same-day gallery delivery.