Beyond seeing. AI that operates.
We read the data piling up in your stores and lay out what to review today.
A person makes the final decision.
1,145
Visits today (top 4 stores)
19.7%
Avg conversion
82%
Calls acted on
| Store | Visits | Purchases | Conv. |
|---|---|---|---|
| Gangnam Stn. | 382 | 79 | 20.7% |
| Hongdae | 298 | 61 | 20.5% |
| Jamsil | 276 | 52 | 18.8% |
| Sinchon | 189 | 33 | 17.5% |
Where it breaks
Solve one more problem and the data you must read grows again.
- 01
Analysis is hard
Reading visits, dwell, conversion, inventory, and weather together takes a trained person.
- 02
The axes keep growing
Every new question brings another dataset that has to be pulled in.
- Visits
- Dwell
- Conversion
- Inventory
- Weather
- +1
- 03
The people stay the same
Data grows, but the hours and headcount to read it each morning do not.
3 top drinks sell out within the hour
Lunch traffic +18% · backroom in stock
Restock now* Sample screen · illustrative data
The actual product
We read the grown pile of data for you and answer with the evidence.
Ask in plain language on the left; a dedicated analysis screen opens on the right. The evidence is that store’s own visit, dwell, and pickup records.
Progress · step 1/1
✓Whole-store brief
Key: Last 7 days: revenue +48.2% while visitors fell −54.2% — a diverging trend. Today: lower orders on high-waste items and re-lay the top-revenue shelves first.
Store overview
Daily visitors
visitors
Gender split
%/day
By age
%/day
Conversion
visit→receipt
Stockouts
SKUs
Cleaning score
0–100
Basket pairs
co-purchase
Shelf pickup
gaze→pickup
Customer 4 · Store 4 — 8 metrics
Screens are illustrative and may differ from the actual service.
Four times a day, what to check first comes up.
POS and vision signals are read together, and the judgment that moment needs is laid out.
- 11:50
Restock the shelf now?
It warns you before the shelf runs out.
Push alert3 top drinks sell out within the hour
Lunch traffic +18% · backroom in stock
Restock now - 15:00
Recurring patterns, into a draft PO
Based on recurring patterns, saai agent proposes a draft purchase order.
Purchase order40 rice balls — in before open
Sized to tomorrow’s lunch demand
Send the PO - 18:00
Review and approve
Open the draft, adjust the quantity, and approve to send the order.
Awaiting approvalToday’s 5 calls — 4 approved
Nothing runs before you approve
Approve - 21:30
Your feedback changes the next recommendation
We use your feedback in the next recommendation.
Weekly report“Add the waste chart” — done
The conversation keeps its thread
Learned
* Sample screens · illustrative data
Applied across the board
Whoever reads it, the judgment is laid out on the same basis.
Results no longer split by how experienced the reader is.
The same method runs from a single store to a multi-store head office.
217
All stores
82%
Calls acted on
19.7%
Avg conversion
Three-step deployment
How deployment works
- First visit
We review the site and connect the existing CCTV with the best viewing angles.
- Build and ship
We configure a compact AI analysis device and ship it to the site.
- Second visit
We install the device, verify operation, and configure the operating view.
Get started about three weeks after the first visit. Timing can change with site conditions.
Continue your review