How Synthetic Data Can Help
Our training cycles build out robust datasets and annotations that can detect if point-of-purchase displays are under-or-over performing, most- and least-trafficked areas of stores, and even signal the need to re-order product based on predictive analyses.
Accuracy benchmarks were also testing in a virtually unlimited array of lighting, weather, and crowd conditions.
Use Cases
CASHIER-LESS CHECK-OUT
Recognize size, orientation, and duplicates for accurate retail experiences.
INVENTORY CONTROL
Monitor inventory depletion and slow-sellers for proactive point-of-purchase data.
WEAPONS DETECTION
Detect customer movement and pose edge cases and activity abnormalities.