SIE for Retail software teams
Your inventory system says in stock. The shelf says otherwise.
SIE gives teams building retail operations software one API to inspect shelf photos, read labels and return a stock check tied to the image evidence.
Self-host SIE in your infrastructure, or ask about managed deployment through SIE Cloud.
Shelf image, out-of-stock sign, price label and product context
The agent localizes the empty facing and reads the shelf label below it.
The operational problem
The model call is only one part of the job.
System inventory can drift from the physical shelf. Staff discover the gap late, after a customer sees an empty facing or an online order cannot be filled.
01
The shelf and the system diverge
Stock can sit in the backroom, the wrong location or an inaccurate inventory record.
02
A photo contains several signals
Empty space, a sign and a shelf label must be connected to the same facing.
03
Product identity has to be exact
The agent must distinguish size, pack and variant before it creates a task.
04
Store teams need a clear action
A detection only helps when it turns into a specific SKU check with evidence.
How SIE helps
Turn one shelf photo into a stock check
SIE runs detection and OCR through one API. Your retail product adds planogram, catalog and inventory context before creating the task.
Store, aisle, facing, likely SKU and the image crops that support the action.
Where it fits
Use SIE inside the product your team is already building.
Shelf availability
Detect likely out-of-stocks before the next manual walk.
Planogram checks
Compare observed facings with the expected shelf layout.
Price-label review
Read labels and route mismatches for store review.
Store task creation
Send a clear SKU-level check to the right team.
Representative task benchmark · Detect
Price, quality and speed for shelf evidence
One measured model job from this workflow. These figures come from SIE task evaluations, not from the industry example on this page.
300 crowded photos; 17,222 objects across four public benchmarks. Correct label and at least 50% box overlap; macro-average F1.
Recorded example
One shelf photo becomes a cited stock check
The existing example uses a pharmacy shelf image from a public dataset. It detects the empty space, then reads the nearby sign and product label.
Grounding DINO finds the shelf region that needs closer inspection.
The label identifies Panadol Children 5–12 Years Elixir, 100 mL.
The retail application can compare the result with store inventory before assigning work.
Deployment
Run SIE where your data can go.
The workflow uses the same SIE API whether you choose managed infrastructure or run it under your control.
Use SIE Cloud
Let the SIE team operate model serving, scaling and updates. Talk to us about availability and the right setup for your workload.
Get startedRun SIE in your infrastructure
Keep models and data inside your environment. Your team controls hardware, networking, access and deployment policy.
View the deployment guide