Planogram Compliance AI

Add a real-time compliance layer to every shelf, endcap, and cooler with vision AI for planogram compliance. Built for the operations where a reset gets done at two in the morning and checked at the next quarterly audit, a competitor's product drifts into the facings you paid for, and the out-of-stock that cost the weekend's sales was sitting in the backroom the whole time. Whether you're a retailer running thousands of stores, a CPG brand paying for shelf position, or a merchandising team with a hundred field reps and a photo app, Roboflow checks every shelf against the planogram on the cameras and phones you already have, with store-level compliance scores and a photo record behind every finding.

Placement and Facings:

• Verify every SKU is on the right shelf, in the right slot, and facing forward, matched against the current planogram version for that store cluster
• Count facings per SKU and flag under-faced, over-faced, and missing products, so share of shelf is measured instead of estimated
• Detect foreign, competitor, and discontinued products occupying paid facings, and flag misplaced items returned to the wrong slot

Availability, Price, and Promotions:

• Detect out-of-stocks, low stock, and shelf gaps as they open, and route a restock task before the gap turns into a lost sale
• Read shelf labels and price tags to verify price, promotion, and label-to-product match, so the tag on the shelf is the price at the register
• Verify endcaps, displays, and promotional fixtures are built to the display planogram on day one of the promotion, not day nine

Audits, Scores, and Systems Integration:

• Score compliance by store, aisle, category, and SKU, and trend it by region and reset cycle, so the stores and categories that keep drifting surface on their own
• Turn every field rep photo and fixed camera frame into a timestamped, annotated compliance record, ready for retailer-supplier reviews and trade spend disputes
• Push findings and tasks into planogram, task management, and inventory systems through API and webhooks, so a violation becomes a work order without a second app

Bring intelligence to every shelf today. Stop planogram drift from becoming lost sales, disputed trade spend, or a category reset that never happened.

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More About Planogram Compliance

What is planogram compliance with Vision AI?

Planogram compliance with vision AI uses computer vision models to compare a photo or camera frame of a shelf against the planogram for that store and category: SKU identification and placement, facing counts and share of shelf, out-of-stocks and gaps, competitor and misplaced products, shelf label and price verification, and endcap and display execution. Models trained on your actual products, packaging, and store formats score every shelf from field rep phones, fixed shelf cameras, or existing store cameras, with per-store compliance scores and annotated photo records that support retailer-supplier agreements and trade spend audits.

Can Vision AI tell similar SKUs apart on a crowded shelf?

The crowded shelf is the hard case: a category can carry forty SKUs from the same brand that differ by flavor text, size, or a color band, packaging changes every season, the shelf is shot at an angle from a phone under mixed lighting, and half the facings are partly hidden behind the one in front. Deep-learning models trained on your actual products, planograms, and store photos learn each SKU's packaging, hold that recognition through seasonal artwork changes with a short retraining cycle, and read shelf labels as a second signal when the pack alone is ambiguous. Compliance is scored against the specific planogram version assigned to that store, and low-confidence facings route to review rather than being guessed.

Does it work with the cameras and phones we already have?

Yes. Planogram compliance runs on whatever captures the shelf: field rep and store associate phones through your existing photo or task app, fixed shelf-edge and ceiling cameras, existing store security cameras where the angle and resolution allow, and shelf-scanning robots or carts. Models are trained on your actual capture conditions, so the phone photo shot at an angle in a dim aisle is the training data, not an exception. Inference can run on-device for reps in the field, at the store on an edge box, or in the cloud, and every capture produces the same compliance score and annotated record regardless of source.

Can it integrate with our planogram, task management, and inventory systems?

Yes. Roboflow Inference exposes a standard API and webhooks, so compliance findings flow into your existing systems: planogram and space planning platforms like Blue Yonder, RELEX, and SAP, retail execution and task management tools like Salesforce Consumer Goods Cloud, Zebra Reflexis, and WorkJam, inventory and POS systems like Oracle Retail and NCR, and alerting into Slack and Microsoft Teams, through REST, webhooks, and direct database writes. A missing facing becomes a restock task, a competitor intrusion becomes a field rep visit, and every finding carries store, aisle, fixture, SKU, timestamp, and the annotated image, with a full audit trail behind every compliance score.

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