Deepwork Labs
PRODUCT · RETAIL INTELLIGENCE

Get your shelves right.

On-prem retail intelligence: computer vision and analytics that read any shelf photo into per-row, per-product sales — so you know which shelf, row, and facing is working, and why. Built for one retailer, now open to others.

on-premyour data never leavesyou own the model
retail-intelligence · shelf detection
The product reading a real shelf photo: every facing detected, priced, and counted, with per-row sales
live deploymentone shelf photo → every facing priced and counted
[ 01 ] · THE PROBLEM
Knowing what's working on the floor is slow, manual, and mostly guesswork.
01

Where is everything?

Hours of manual shelf audits just to know which product sits where — and it's stale the moment the clipboard is closed.

02

The shelf is a blind spot.

POS tells you a SKU sold. It can't tell you the planogram broke, a facing went empty, or your eye-level row is being wasted.

03

Data you can't digest.

Mountains of POS numbers, no time to read them, and no view that ties revenue back to a specific shelf, row, or facing.

[ 02 ] · HOW IT WORKS
From a photo to a decision, in four moves.
one model, on your hardware →
01

Capture

Snap or upload a shelf photo. No special hardware — a phone on the floor is enough.

02

Detect

Computer vision reads every facing — product, price, and count — in under ninety seconds.

03

Score

Each facing is tied to live POS, so you get per-row and per-product sales, not a store-wide average.

04

Act

A prioritized worklist surfaces what's losing money — empty slots, dead stock, stalled top sellers — and what each fix is worth.

[ 03 ] · THE PRODUCT
See your store as data you can act on.
store names anonymized →

The store, prioritized.

Every morning, the handful of things that need attention — ranked by revenue at risk. Top sellers that stopped selling, empty slots you're not earning from, shelves still dark.

retail-intelligence · dashboard
The store, prioritized.

Any shelf, read like a page.

One photo becomes a planogram: every facing detected, priced, and counted, each row tied to its own sales — with the gaps and dead stock flagged for review.

retail-intelligence · shelf detection
Any shelf, read like a page.

The sales, explained.

Category share, revenue by day, top movers, and what's quietly declining — down to the individual SKU, not a quarterly summary.

retail-intelligence · analytics
The sales, explained.
more in the box
[ 04 ] · WHY ON-PREM
Your data never leaves the building.

It runs locally, on your hardware. No footage, no sales data — nothing goes to a cloud you don't control. You own the model, so there's no subscription rent. It just runs on your electricity, and it gets cheaper every month you keep it.

data sovereignty

Shelf photos and POS data stay on-site. Compliance-friendly by default — nothing to leak, nothing to subpoena from a vendor.

you own the model

No per-seat, per-store, or per-API-call subscription. The model is yours; the value compounds instead of renting it back monthly.

cheap in the long run

It runs on your electricity. The more you use it, the lower the cost per insight — the opposite of cloud SaaS pricing.

[ 05 ] · PROOF
Built for a major retailer.
retail-intelligence · live deployment
The live analytics view from the deployment, client identifiers redacted
live deploymentreal numbers · client name redacted
“We finally know which shelf is pulling its weight — and which one isn't. The audits that used to eat a day now run themselves.”
— ops lead · a major retailer (name on request)

Client unnamed pending their sign-off; store names in the screenshots are anonymized. Every screen above is the live on-prem deployment.

OPEN TO A HANDFUL OF RETAILERS

See your floor as data.

We're taking on a small number of retailers to deploy Retail Intelligence on-prem. Book a walkthrough and we'll show you the live product reading real shelves.