RETAIL
Know what happened in every aisle.
Alerts on what is happening on the floor, and the insight to know what it means.
From checkout optimization to shelf monitoring to store safety - LexData powers the visual AI that helps retailers understand and improve physical operations at every location.
4M+ Annotations & validations
The case study ↓// From this field · empty slot · person · basket
Real footage · real labels · unretouched product output
// 01 · What breaks AI in retail
Store environments are chaotic
Changing displays, seasonal layouts, lighting variations, and customer density make every store visually unique. Models trained on one store configuration fail when the layout changes.
Alert fatigue kills adoption
False door alarms, incorrect traffic counts, and phantom theft detections flood store teams with noise. Real issues get ignored because the system cries wolf too often.
Scale across locations is brutal
What works in 10 stores breaks in 500. Every location has different cameras, angles, lighting, and foot traffic patterns. Scaling visual AI across a retail fleet requires continuous adaptation, not one-time training.
// 02 · Inside LexLoop
LexAnnotate
Shopper Tracking
Annotate in-store video for customer detection, employee identification, door events, and product placement. Distinguish between customers, staff (by uniform), and children within each camera's region of interest.
LexInsight
Conversion Analytics
Turn raw foot traffic data into conversion intelligence. Link visual detections to store zones, time slots, and operational events. Surface patterns that static dashboards miss.
LexAlert
Store Alerts
Monitor detection accuracy across store locations. Detect when camera repositioning, seasonal displays, or lighting changes degrade model performance. Route the failures back for retraining.
// 03 · Where it runs
Traffic Counting & Conversion
Who crossed the door, in and out, from the camera already above it, staff and deliveries told apart from a shopper.
Checkout Queue Monitoring
An alert when a lane has held above the store's threshold, from the camera already over the tills.
Shelf & Planogram Compliance
The empty facing and the pack out of plan, from the aisle camera the store already has.
Store Safety & Validation
The spill or the blocked exit, flagged by its own zone, from the floor cameras the store already has.
Checkout Product Verification
Every item on the counter by class, checked against the till's own list, from the camera already over the lane.
Employee Activity Monitoring
Measure staff engagement and service levels in key zones.
- The Challenge
- The models lacked high-quality labeled data, activity alerts came back false, and unmonitored registers left customers waiting at checkout.
- Our Execution
- Labeled customer and staff positions. Validated alerts and traffic counts for accurate footfall tracking.
- The Result
- Faster AI training with accurate labeling. Smarter alerts for open doors and empty registers.
// 05 · Why LexData for retail
01
Continuous model adaptation across hundreds of store locations - not one-size-fits-all.
02
Human-verified annotation reduces false alerts and improves detection confidence.
03
Alerts scoped to the store's own zones and schedule, not a blanket motion trigger.
04
Runs in the cloud, on your servers, or on a runner beside the recorder, footage stays wherever you choose.
// 06 · Same loop, different field
Bring us your retail edge cases.
Enterprise? Contact sales