Who sees the sales that never reach the register?
In a store, data isn’t there to keep watch. It’s there to sell more.
We show ten cameras here: four that raise an alert when something needs fixing and six that alert nobody, they just measure. Each image is a different store on the same street — a supermarket, a clothing store, an electronics store — because “retail” isn’t one single format. And none of the ten is looking for shoplifters: they’re looking for the sales that are lost today without anyone seeing them.

Without IRIS this is just a street with stores.
AI-generated image
The sales nobody sees today
The register receipt only records what did get sold. It doesn’t record the customer who reached the shelf and couldn’t find their brand, or the one who abandoned a shopping cart in the line because eight people were ahead of them, or the one who got tired of waiting for a fitting room and hung the clothes back on any rail. Those three sales appear in no report the store has, and they’re sales.
And whatever needs fixing today is nearly always reported by a customer. The spill gets flagged by the person who almost slipped on it. The dead light in the aisle turns up in a review two days later. That the store was impassable on Saturday is something you learn on Monday. IRIS watches for you: it analyzes every camera the store already has, all at once, and only interrupts when a rule your own team set is met — a gap on the shelf, something spilled on the floor, an area left in the dark, the floor busier than the shift can handle.
And where there’s nothing to alert about, IRIS measures. How many people come in and at what time. How long the wait at the registers is, and with how many registers open. How many give up on the line before their turn comes. How many walk past the promotional display and how many stop at it. How the floor splits up: how many reach the back and how many turn around halfway down the aisle. Today that is decided by what the store manager reckons, and they’re usually right; with the numbers in front of them they are right more often, and they can explain why. And that number has backing: IRIS people counting is approved by the Centro Español de Metrología — Spain’s national metrology institute — so the store’s foot traffic figure is guaranteed by a third party and not by us. The approval covers people counting, not the whole product. It’s a Spanish approval. What crosses over isn’t the seal, it’s the method: the same line, in the same place, every day.
And two things said out loud, because they’re the first ones anybody thinks of on hearing “cameras” and “store.” First: IRIS does not identify anyone. It detects objects, behaviors and situations. It does not recognize faces, does not compare them against any database, does not store who anybody is, does not follow a person from one store to another and is not cross-referenced with your loyalty program. What it sees is “a person,” “a shopping cart,” “an empty shelf” and how long it’s been that way. Second: this isn’t about catching shoplifters. None of the ten cameras on this page does that. It’s about selling better and about the store being in the state it should be in.
The real scale
Ten cameras here. A whole chain open out there.
This demo shows ten cameras because ten fit on a screen. A chain doesn’t fit. Here the axis isn’t miles or passengers: it’s opening hours and stores. A store is open for many hours every day, every day of the week; a chain has dozens or hundreds of stores open at the same time, and the operations director can’t be in any of them. Not even the store manager can be everywhere in their own store: while they deal with the stockroom, the back of the shop floor is on its own. That’s the problem IRIS solves: it analyzes however many cameras there are, in every store, for every hour they are open, and only interrupts when a rule is met. And where there’s nothing to alert about, it measures — store by store and hour by hour — so that two stores can be compared with the same yardstick.
Examples
These ten are just examples.
Four raise an alert when something needs fixing and six alert nobody: they only measure. Each one is a different store on the same street, and that’s deliberate: a supermarket, a clothing store and an electronics store don’t have the same problems, but they’re watched by the same system. They aren’t the ten things IRIS can do in a store; they’re the ones that fit on a screen. Open any of them and you’ll see the image as it is, and then with what IRIS understands on top.
The real interface, step by step
Everything comes in. Only what matters gets through.
This sums up what IRIS does with one alert, from the moment it appears until it’s closed. The real screen holds far more; this is the main thread.
- You ask
- IRIS searches
- It shows you
Now think about your own store
Imagine knowing all of it while the store is still open.
A gap on the shelf that’s been empty since this morning. Fourteen people who left a shopping cart in the line today and walked out. A promotional display everybody walks past without stopping. The back of the store, where hardly anybody gets to. The dead light in aisle three, which nobody has spotted because aisle three is behind the registers. The fifteen minutes at seven in the evening when the line turned the corner and only two registers were open.
All of that is happening right now, in front of cameras your store already owns and already paid for. And right now nobody knows: the manager is in the stockroom, head office looks at next month’s report, and the customer who walked out doesn’t come back to tell anyone. IRIS watches all those cameras at once and tells you while the store is still open. In front of cameras that already exist.
What a retail group’s committee asks
The ten questions that come up in the operations meeting.
Answered in the first line, straight, and without promising sales we can’t prove.
Does IRIS identify our customers?
No, IRIS does not identify your customers: it detects objects, behaviors and situations. It does not recognize faces, does not compare them against any database, does not store who anybody is, does not follow a person from one store to another and is not cross-referenced with your loyalty program. What it sees is “a person,” “a shopping cart,” “an empty shelf,” where it’s and how long it’s been there. That’s why a store’s counting never says who came in: it says how many, through which door and at what time. If somebody ever offers you the opposite, know that we don’t do it, and that this isn’t an oversight: it’s a decision.
Does it work with the cameras we already have in the store?
Yes, IRIS works with the cameras you already have in the store. It connects to the feed of the ceiling IP cameras and analyzes it as it arrives: what changes isn’t the hardware, it’s what gets understood from the picture. During the project we check camera by camera whether the framing is enough for what you want to see there — a camera set up to watch the door may not reach the shelf at the back — and we tell you plainly which ones fall short and which just need turning a few degrees. Adding a new camera is the exception, not the starting point.
Is this for catching shoplifters?
No, this isn’t for catching shoplifters, and we’d rather say so before it comes up in a meeting. None of the ten cameras on this page does that, and it isn’t because it never occurred to us: detecting theft means judging the intent of one particular person, and IRIS doesn’t look at particular people. What it does do is what you have on this page: flag a gap on the shelf, something spilled on the floor, an area left in the dark or a shop floor busier than the shift can handle; and measure lines, fitting rooms, shopping carts, how people spread across the floor and what the promotional display actually achieves. In other words: sell better and keep the store in the state it should be in. If what you need is loss prevention, you’ll need something else, and we’ll tell you that in the first meeting rather than the last.
How do I know how many people give up on the line and leave without buying?
You know how many people give up on the line because IRIS counts two things separately: how many people enter the waiting area at the registers and how many reach the point of payment. The difference is the people who left before their turn came. Two more clues get added to that: the average wait in that line, and the shopping carts left abandoned in an aisle or beside the registers, which nearly always belong to someone who got tired of waiting. And all of it carries a timestamp, so it can be cross-referenced with how many registers were open at that moment. We aren’t going to tell you how much money that is — we don’t know, it never went through your register — but we’ll tell you what time it happens and with how many registers open it stops happening.
Can it tell me whether a promotion is working?
IRIS can tell you whether a promotion is working in the part you can see from a camera: how many people walk past the display, how many stop and how long they stay. The sale itself is in your register, and we don’t go in there. But putting the two halves together changes the diagnosis: if a lot of people walk past and almost nobody stops, the problem is where the display sits or how it looks. If a lot of people stop and it still doesn’t sell, the problem is the price or the product. Today those two situations look identical in the sales report — it sold badly — and they’re two different problems with two different fixes. The same works for comparing the same display in two stores, or the same spot in two different weeks.
Does it work when the store is packed?
IRIS works when the store is packed, with one caveat we’d rather say before signing: when a lot of people are close together, some block others and a camera stops telling them apart one by one. That happens to any vision system, ours included, and anyone who tells you otherwise has never tried it on a Saturday afternoon. What doesn’t get lost is exactly what matters most at that moment: occupancy. Measuring how many people are in an area and how they spread across the floor doesn’t require telling each person apart, so it keeps working, and detecting that the store is overwhelmed works precisely because it’s full. What does degrade is counting people one by one through a narrow, crowded gap; in that case the counting is moved to the entrance, where people go through in single file, and occupancy is left to cover the shop floor.
Does the video leave the store?
The video leaves the store or stays inside depending on the option you choose, and there are exactly two. In the on-site option it doesn’t leave: the servers are in your own facilities — in the store or at head office —, the video comes in over your network, it’s analyzed there and the system doesn’t need the internet to work. In the other one it is processed in our data center, which is our own cloud and not a third party’s. In both, communications are encrypted and the terms are set out in the contract. In a chain it is worth deciding early, because a server per store isn’t the same as bringing the analysis to one single place: it drives the network in every branch.
And what about data protection, with a store full of customers?
Data protection is handled by configuring the processing piece by piece: what’s stored, for how long, who can access it and from where. And above all of that sits the part that weighs most in a store: IRIS does not identify anyone, so there are no identities to protect and no customer profiles to build. Compliance, though, doesn’t depend on the software alone: it also depends on how you deploy it and what you decide to process, and that’s signed off by your organization, not by us. What we can put on the table is that our way of working is certified for information security and for privacy by an external auditing body. That paper isn’t signed by a salesperson: it’s signed by an auditor, and you can ask us for it before you sign anything.
Does it work for a single store, or do you need a whole chain?
IRIS works for a single store and for a chain alike; what changes isn’t the system, it’s what you do with the data. In one store it helps you decide your store: when to open the third register, where to put the promotional table, whether the back of the store gets visited at all or needs a reason to walk to. In a chain something appears that a single store doesn’t have: comparison. The same promotion set up in forty stores and measured the same way in all of them. The store where the line spikes half an hour earlier than the rest. The one that is the same size and has half as many people at the back. Starting with one store, seeing what comes out and deciding afterward is the normal way in, and it’s what we usually recommend.
How much does it cost to put IRIS on a store’s cameras?
You pay per camera. What it comes to depends on how many cameras are analyzed, what’s detected or measured on each one, how many stores are included, which deployment option you choose and whether the hardware is yours or we supply it. There’s no single price list, because measuring the registers and the entrance of a corner store doesn’t cost the same as covering the whole floor of a large supermarket, and one store doesn’t cost the same as forty. Tell us how many stores you have, how many cameras are in each and what you want to see, and we’ll give you a figure. Write to hola@infinityneural.com. Or call Spain: 011 34 902 02 70 91.
Next step
The highway
Who watches an entire highway?
10 cases: 8 raise an alert when something happens and 2 only measure. You see each image as it is, and then with what IRIS understands on top.
Public transport
Who watches a whole station at rush hour?
17 cases: 11 raise an alert when something happens and 6 only measure. You see each image as it is, and then with what IRIS understands on top.
And the best part
We’d rather promise less.Let the first week be the surprise, not the brochure.
What it can’t do gets said on day one, not on the last day. A short list that holds beats a long one that falls apart the moment it is turned on.
Tell us your problem and we’ll say whether IRIS understands it, or not yet.
A person answers, the same working day.









