Monitoring grocery store shelf inventory with computer vision

Monitoring grocery store shelf inventory with computer vision

OneSix designed and implemented a computer vision-based product identification pipeline capable of rapidly identifying products on grocery store shelves.
AI & Machine Learning
Computer Vision

Overview

The complexity of grocery product identification

Grocery retailers rely on accurate, real-time product identification to manage shelf inventory, ensure planogram compliance, and reduce stockouts. However, the diversity of packaging, frequent product updates, and variable image capture conditions make automated product recognition extremely challenging at scale.

Our client, a provider of image-based grocery analytics, needed a robust, scalable solution to power its product recognition AI toolkit and enable high-speed identification from both mobile and robotic capture sources.

Our Solution

A computer vision-based product identification pipeline

OneSix designed and implemented a robust computer vision-based product identification pipeline capable of analyzing high-resolution shelf images and delivering product-level insights at scale. The solution featured:

Results

Faster, smarter grocery store shelf analytics

The end-to-end solution delivered measurable impact for grocery retailers:

By integrating computer vision, scalable infrastructure, and intuitive tools, OneSix built a flexible product identification platform that continues to power real-time shelf analytics and support evolving retail needs.

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