Powering decisions that win
The brands your competitors are watching
Eight data types, collected to your requirement.
Retail Shelf
Real store shelves for planogram, out-of-stock, product recognition, and share of shelf.
Bespoke shelf images, built to your spec.
The shelves your model needs, from the retailers and markets it will run in.
Why shelf models fail.
Stock and synthetic shelves train a model that slips on real aisles, real packaging, and real gaps.
Reads a tidy planogram, slips on the messy shelves your model will actually see.
Holds up across the stores and markets you audit.
What stock shelves miss.
Rwazi shoots every one of these in real stores, so your model trains on real shelves before it ever audits one.
Real shelf samples for cases like yours.
A requested pack arrives as shelf images matched to your retailers and categories, each carrying store and region metadata and a consistent naming convention, dropped into your cloud.
Planogram-compliant shelves, category by category.
Gated requestOut-of-stock gaps and misplaced product.
Gated requestPromo displays and end caps.
Gated requestMixed-category aisles, real store conditions.
Gated requestWhat we capture, to your spec.
Captured your way, in real stores or controlled.
We work both ends of the spectrum. You pick the shelf conditions your model needs.
Real-store capture
For models that must hold up in production. Real aisles, real light, and real gaps, shot where your products actually sell.
Controlled capture
For models that need precision. Framed, evenly lit shelves shot to a tight brief.
Real shelves, from 190+ countries.
Most shelf images come from a few mature markets, so models misread the aisles everywhere else. Rwazi shoots real shelves across 190+ countries, in local stores with local packaging, from real people on the ground.
- 190+ countries
- real stores
- local packaging and SKUs
- planogram, gaps, and promo
- straight-on or aisle
What you get with Rwazi that stock shelf images leave out.
Built for the retail vision you are shipping.
Planogram compliance.
Compliance models trained on tidy planograms miss real resets and mixed facings.
Real shelves across retailers and markets, labeled to your planogram.
Retail shelf datasets for the task you are training.
Rwazi builds retail shelf datasets for machine learning, scoped to the retailer and category, including:
From your spec to your cloud, in four steps.
Run it as a one-off project or a recurring refresh, weekly or monthly.
How Rwazi compares to other providers.
The same data, captured in the physical world. Here is how that stacks up against the alternatives.
Rwazi plays in physical-world-first AI.
5 million mobile users collecting authentic data from real environments in 190+ countries. Making your models more competitive with real life data.
Every shelf image earns its place in your dataset.
You write the pass-or-reject criteria. Each image is reviewed by people, checked against those criteria, and logged with where it was shot, when, and by whom. We report what passed before the dataset reaches you.
Tell us what you are building.
Share your use case, and we will scope a shelf sample pack for it, then walk you through how we would collect it.
Contact The Rwazi AI Datasets Team
Book A Live Demo
Questions teams ask before they buy.
What is a retail shelf dataset?+
A set of real images of retail shelves, used to train computer vision models for planogram compliance, out-of-stock detection, product recognition, and share of shelf. Rwazi collects it to your spec across 190+ countries, with store and category metadata.
Can you label out-of-stock gaps and planograms?+
Yes. Bounding boxes, SKU labels, facings counts, and planogram tags are available as add-ons on top of the raw shelf images.
How current is the data?+
Collected on demand, so you receive shelves current to the retailers, categories, and window you specify.
Does each image include metadata?+
Yes. Store type, region, and category on every image, with richer fields available on request.
How is it priced?+
We quote per project. The drivers are volume, retailers, categories, labels, exclusive versus licensed, and cadence. Send your brief and we will price it.
How does this compare to stock or synthetic shelf images?+
Stock and synthetic shelves look tidy and slip in real stores. Rwazi shoots the real shelves, gaps, and promo your model will meet.
What is share of shelf?+
The portion of a shelf a brand or category occupies, measured from real shelf images by counting facings. Rwazi collects the labeled shelves that train and check share-of-shelf models.
What retailers and categories can you capture?+
Grocery, pharmacy, convenience, and more, scoped to the categories and brands you name, across 190+ countries.
What coverage do you have?+
190+ countries, with local packaging and SKUs, shot in real stores.
What formats and delivery do you support?+
JPEG and PNG, delivered to your S3, Azure Blob, GCS, or SFTP.
How do you handle consent and privacy?+
Every contributor shoots with explicit consent, sourced through Rwazi, and provenance travels with each image.
Where can I buy retail shelf or product recognition datasets?+
Tell us the retailers and categories you need, and Rwazi scopes a bespoke shelf dataset, shot to spec and licensed or owned outright.