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КыргызчаAutonomous Retail: Smart Shelves, Checkout-Free, Shrinkage Control
We are creating cashierless stores: computer vision, sensors, and analytics that provide accurate receipts and minimize losses.
Autonomous retail combines visual and weight sensors, shopping cart tracking, and checkout-free payment. Success depends on the accuracy of CV, latency <1–2 ms, antifraud measures, and reliable receipts.
Streams from Cameras and Scales; Synchronization of Events.
Catalog/prices; identification of buyer/session.
Edge pre-filtering; masking personal data.
Receipt in Real Time; Mobile Payment; Invoices.
Dashboards for shrinkage, SLA, and receipt accuracy.
Notifications for sensor errors; manual checks.
Frequently asked questions
How can we optimize latency (edge inference, batching, pre-filters)?
To minimize latency, techniques like edge inference, batch processing, and pre-filtering data are employed to improve efficiency.
How do we monitor shrinkage, SLA, and accuracy; what's the plan?
We continuously monitor shrinkage rates, Service Level Agreements (SLAs), and receipt accuracy while regularly updating product catalogs and embedding models.
What about privacy: blurring faces/bodies, edge processing?
Privacy is addressed through techniques like face and body blurring, edge computing for data processing, and minimizing the amount of personal data stored.
How do we ensure accuracy: SKU validation, drift control, embedding updates?
Accuracy is maintained by validating transactions against specific SKUs, monitoring price drift, and regularly updating product embeddings to reflect current inventory.
▶ Try it live
Everything above runs in your browser — open Inverse Kinematics (FABRIK) and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.