The client’s field operations suffered from inefficient data collection methods during store audits. Store staff frequently submitted poor-quality media, which created significant downstream bottlenecks:
Manual shelf image capture caused blurry and unusable photos.
Lack of real-time quality validation led to frequent retakes.
Delayed image submissions reduced retail data accuracy and timeliness.
Increased manual backend reviews slowed down overall operational efficiency.
Field staff struggled to judge correct distance and tilt.
Absence of instant feedback prolonged the store audit process.
Solution Provided
Icanio Technologies built a Smart AR-Guided Capture Application, integrating mobile computer vision to ensure perfect data collection on the very first try. The solutions include:
Developed an AR-guided cross-platform mobile app for accurate capture.
Implemented real-time validation for tilt, slant, and overlap issues.
Enabled configurable capture rules for custom retail quality parameters.
Built a reusable, modular AR SDK for iOS and Android.
Provided instant live preview feedback to guide store staff.
Integrated real-time checks to prevent duplicate image submissions completely.
Business Outcomes
Consistent high-quality
usable shelf images on the first capture.
Eliminated unnecessary
manual staff image retakes on the floor.
Reduced backend
manual data review and quality control effort.
Faster turnaround
for image submission and retail data processing.
Scalable technology
foundation supporting future retail and field applications.
Reusable AR SDK
integrated seamlessly across multiple internal field scenarios.
