Edgify

Founded 2015

Detect retail checkout shrinkage and recognize barcodeless products directly on store hardware

Pricing model

Demo

You can use Edgify to prevent retail loss and identify barcodeless items directly on existing checkout hardware. The software runs machine learning models locally on scales, scanners, and self-checkout terminals without sending raw camera footage to the cloud. You can automatically flag non-scans, barcode switching, and missed cart items before shoppers finish paying. It also identifies fresh produce inside bags to speed up weighing. Store teams can connect the system to AI agents through an MCP server and update models across thousands of devices over the air.

What Edgify does

Detect non-scanned items at checkout registersRecognize unpackaged produce on weighing scalesAlert checkout attendants to suspicious scan behaviorDeploy model updates over the air to store devicesLog intervention history for shrinkage reportingQuery live store device inventory using MCP toolsTrack back-of-house waste and discarded itemsOn-device inference with zero cloud latency or raw data transferBarcodeless fresh produce recognition through plastic bagsReal-time checkout intervention for non-scans and barcode switchingModel Context Protocol (MCP) server for querying store telemetry via AI agentsOver-the-air model updates and rollouts across device fleetsSelf-learning models that train locally on confirmed in-store interactionsHardware compatibility with existing scales, scanners, and terminals across 40+ OEMs