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NVMS · Infinity Neural

Your cameras have multiplied.Your team's attention has not.

Everything comes in. Only what matters gets through.

IRIS is an NVMS: it connects to the cameras you already have, understands what is going on in front of each one and sets the routine aside. Your team only sees what calls for a decision.

  • Local processing
  • No pay-per-query
  • Works without internet
  • The cameras you have
  • Natural language
  • Neural video
  • 8 languages
Two cars have collided in the middle of the junction. One person is on the ground being treated by paramedics, a bus is stopped behind them and onlookers line both pavements; traffic is stopped on all four approaches.
CAM-14IRIS VisionLive

Turn on IRIS Vision

AI-generated image

The same image. What changes is what is understood from it.

The cost that never shows up on the invoice

Recording is not the expensive part. Watching it by hand is.

A hard drive costs what it costs, and every year it costs less. What never gets cheaper is the hours of people watching screens where almost nothing happens, or the hours that go afterwards into finding the exact moment inside the recording.

  • Attention runs out

    Nobody holds their focus on a wall of screens for a whole shift. It is not a lack of professionalism: it is how a human head works. After a few minutes the eyes are still there, but the attention is gone.

  • Almost everything recorded is routine

    Of everything your cameras see in a day, the vast majority is normality: cars going past, people walking, doors opening and closing. What genuinely calls for a decision is a tiny part of it, buried in all the rest.

  • Searching afterwards costs whole shifts

    When something finally happens, someone has to go through hours of video from several cameras to find thirty seconds. That time comes out of the same team that should be watching what is happening right now.

Every new camera multiplies the video, but it does not multiply the people. Your team should not be guarding screens. It should be solving situations.

Do the maths

How much of what you record does anyone actually watch?

Put in your own numbers. There is no trick and no figures of ours hidden inside: it is a division, and the whole formula is written below.

400
2
€22

9,552hours of video a day that nobody sees. You record them, you store them, you pay for them.

0.5 % · Of everything recorded, watched9,600 h · Hours of video per day

The whole bar is what gets recorded. The gold sliver is what anyone actually gets to watch.

  • 48 hHours anyone can watch
  • €385,440Yearly cost of those people watching

The formula, in full

Hours recorded per day = cameras × 24. A camera that is on records twenty-four hours, not eight.

Hours that can be watched = people × 24. This is the only assumption we make, and it is as generous as it gets: that each person watches one image at a time, without blinking, without a break and without tiring all shift long.

The percentage is one divided by the other. And because the assumption is impossibly good, in real life the number always comes out worse than the one you just got here.

None of this says anything about IRIS. These are your figures and a division. What IRIS does with the video nobody watches is what the rest of the site is about.

Real scenes

Six scenes that already happen. What changes is how they end.

None of these is made up. They are ordinary shifts, with ordinary people doing their job well. The problem is never the person: there are simply more cameras than eyes.

Airports and power plants

Kilometre 14, at three in the morning

  1. The scene

    It is three in the morning. The perimeter fence runs for eighteen kilometres and almost none of it is lit. In the control room the lights are dimmed so they do not bounce off the screens, and one operator sits in front of a mosaic of forty flickering images. He is five hours into his shift. In the last hour the system has gone off four times: two gusts of wind shaking the fence, and two foxes.

  2. Where it breaks

    Nobody looks at forty images at once. You look at them one at a time, and while you look at one, the other thirty-nine are on their own. That is not his failing: no human eye holds forty scenes for eight hours. And when the system has cried wolf four times in a row, the brain trusts the fifth one a little less.

  3. What happens

    At kilometre 14 there is a stretch with no lamp post. Someone walks up to the fence on that side, slowly, hugging the embankment. The scene is on screen: in a small tile, bottom right, on the secondary monitor.

  4. With IRIS

    IRIS watches all forty at once, always, without tiring. It can tell a person from a gust of wind and from a fox, so the wind and the fox interrupt nobody. When it sees someone approaching the fence, it pulls that camera onto the main monitor and says what it saw, where, and since when. The operator discards nothing any more: he looks at one scene and decides. He is still the one who calls the patrol; what changed is that he does it while it is happening.

The camera was already seeing it. All that was missing was someone looking at that screen.

Ports and rail

The vest that stayed in the van

  1. The scene

    Quarter to six in the morning, still dark. The terminal has not stopped all night: engines, reversing alarms, steel on steel. A maintenance technician is going to make a quick adjustment on a set of points, five minutes at most, and he wants to be done before daylight and the first traffic. He steps out of the safe zone and onto the shunting track. His hi-vis vest is on the van seat, forty metres away.

  2. Where it breaks

    There are cameras pointed at that track. They are recording, like every night. But recording is not watching: the video goes to a disk nobody opens, and at that hour nobody is assigned to that screen. Normally that disk only gets opened if something happens or an inspector turns up.

  3. What happens

    The technician steps over the yellow line and crouches over the points. Eighty metres away, a shunting locomotive starts to move. His back is turned and he is wearing ear defenders: he cannot hear it, and with no vest he is just one more shadow among the steel.

  4. With IRIS

    IRIS watches that track the whole time, quarter to six included. It recognises a person, sees that he has crossed the yellow line, and sees that he is not wearing a vest. That meets the rule Safety set, so IRIS speaks up: to the shift supervisor, with the camera, the place and the time, and, if you want, over the tannoy in that zone too. The supervisor decides, calls it in on the radio and stops the movement. Nobody had to be watching that screen for this to happen.

Safety stops being something you check after the accident and becomes something you check while the technician is still on the track.

Security and investigation

One white van in five hundred hours of video

  1. The scene

    Monday morning. Over the weekend, material went missing from the loading area. The security manager has a description and little else: a white delivery van that came in at some point between Friday afternoon and Sunday night. Fifteen cameras cover those entrances. Between them they add up to some five hundred hours of footage.

  2. Where it breaks

    The only way to find it is for someone to look. Two operators are pulled off active monitoring and set to fast-forwarding video, camera by camera, hour by hour. After two hours of watching sped-up frames, anyone starts to miss things. And while those two are doing that, the site has two fewer pairs of eyes.

  3. What happens

    By mid-afternoon the van turns up: it came in on Saturday at 04:12. That cost a full day's work from two qualified people. And they were lucky, because nobody knew for certain it was in there at all. If the description had been slightly different, they would have had to start over.

  4. With IRIS

    IRIS does not only keep the video: it keeps what it understood in it. So the manager can type what he is after in his own words — white van in the loading area, Friday to Sunday — and get back the moments that fit, each with its camera and its time. No timeline to drag, no hours to sit through. A person still decides which of those moments is the right one; what disappears is the whole day spent on the ones that were not.

Stop hunting for the minute. Search for what happened.

Local government

The bin that had been overflowing for three days

  1. The scene

    Tuesday morning at the public spaces department of a mid-sized council. A council officer opens her inbox: forty reports, four meetings, and the cleaning budget that has to be closed this week. In a neighbourhood at the far north end, a bin has been overflowing since Saturday: bags around it, flattened cardboard leaning against it, a mattress. Nobody from the department has been past, because the collection route does not come round until Thursday.

  2. Where it breaks

    The council has more than four thousand cameras. Nobody watches them: there is no control room with four thousand screens, and there never will be. They are there so you can look back at what happened, not to tell you what is happening now. So the neighbourhood finds out before the council does.

  3. What happens

    On Tuesday at half past ten, someone posts a photo of the bin. By eleven, the photo has two hundred comments and the name of the neighbourhood on it. At quarter past eleven, the officer learns about a three-day-old problem from a social network. There has been a camera pointing at that bin since day one.

  4. With IRIS

    IRIS watches that camera just like the other four thousand, all at once. Operations writes the rule down once — if the bin has been overflowing for more than two hours, tell me — and IRIS applies it without anyone having to think about it again. On Saturday afternoon, the officer would have got a picture, the street and the time. A truck goes past on Sunday morning, and on Monday there is nothing to post. The decision is still hers: what IRIS saves her is finding out late.

A city does not need more cameras. It needs the ones it already has to know when to speak up.

Logistics and industry

Forty minutes nobody can account for

  1. The scene

    Quarter to seven in the morning in the yard of a distribution centre. It is cold, and three lorries have had their engines running for a while, waiting. Dock 4 has been occupied since 06:05: a trailer parked with its doors open and nobody loading inside. The yard supervisor walks back and forth with a clipboard, answering the radio and deciding by eye who goes to which dock.

  2. Where it breaks

    Nobody is measuring anything. The yard supervisor keeps the times in his head and on a sheet of paper, and his head has the same problem as any head at seven in the morning. The yard cameras record, but they do not count minutes. At the end of the day there will be a figure for lorries unloaded and no explanation of why they left late.

  3. What happens

    At 06:45, dock 4 has been occupied for forty minutes without a single pallet moving. The forklift that should be working there is at dock 7, because someone called for it on the radio. The three lorries are still waiting, and every one of them will be late to its next stop.

  4. With IRIS

    IRIS watches the yard and counts. It knows when a trailer arrives at a dock, when it opens, when the first pallet moves and when it leaves. Operations writes one rule — dock occupied more than twenty minutes with no activity, tell the yard supervisor — and by 06:25 he already knows, with the camera and the running time. He is still the one who decides whether to move the forklift or switch docks. And at the end of the day he has the minutes for every dock, not a feeling.

The same camera that today only records can start measuring your operation.

Finance and legal

Paying because you cannot show it

  1. The scene

    Thursday afternoon. On the desk there is a claim: goods that arrived damaged, with a photo of a broken pallet and an email that has already been forwarded three times. The operations manager was on the dock that morning and remembers it clearly: that pallet went out intact, she watched it being loaded. The other side says otherwise and attaches its own photo. She is right, and she has no way of showing it.

  2. Where it breaks

    The video from that day exists. It is somewhere among the dock cameras, the yard cameras and the one at the exit, in one of the hours of that morning. Nobody remembers the exact minute, and the team that would have to look for it is the same team loading lorries today. Meanwhile the recording erases itself: the retention window keeps running even though the argument does not move.

  3. What happens

    The argument drags on: an email, a call, a meeting, another email. When someone finally sits down to look for the video, that date has already dropped out of the retention window. And the manager signs off the payment. Not because the claim was true, but because finding the moment cost more than accepting it.

  4. With IRIS

    IRIS does not only keep the dock video: it keeps what it understood in it. Which lorry, which dock, what was loaded and at what time. When the claim arrives, the manager types the number plate and the day, and has the moment in front of her the same afternoon she opens the email. Once the moment is pinned down, setting that video aside before the retention window closes takes one click. She still decides what to answer and what to negotiate; the difference is that now she answers with what happened, not with what she remembers.

Being right and not being able to show it costs exactly the same as being wrong.

Infinity Neural

AI has spent years locked inside a screen. We take it out onto the street.

That is what we do: take real artificial intelligence and put it to work where things actually happen. A junction, a loading dock, a platform, a school gate. And do it the simplest way there is: with the cameras that are already up.

  • It is simple

    No new cameras, no rewiring the building, no strange sensors. IRIS connects to the ones you already have and starts understanding what they see.

  • It is already running

    This is not a demo reel or a lab experiment. It is software that is installed, watching real cameras, every day and at every hour.

  • You notice it on day one

    You stop watching forty screens and start looking at what matters. That needs no chart to explain: you see it on that night's shift.

  • And it stays at home

    It can run inside your own site, with no internet at all. Your footage goes nowhere unless you want it to.

What does IRIS do?

IRIS sees, understands, decides and acts.

Cameras already see the world; IRIS is what makes them understand it.

Sees what is already recording

IRIS connects to the cameras you already have, as long as their video stream is available. Seeing was never the problem: the cameras were already doing that on their own.

Understands what is going on

It recognises people, vehicles, objects, zones and durations, and how they relate to each other. It moves from ‘there is something in the image’ to ‘this is what is going on’.

Decides by your rule

It compares what happens with the rules your organisation has defined. Decide once; IRIS applies it every time.

Acts and writes it down

It opens the incident, alerts, brings up the camera, records the figure and stores the evidence. The team receives a situation ready to be decided on, not an hour of footage.

Where is your problem?

The technology is the same. The pain is not.

IRIS installs the same way in a hospital as on a loading dock. What changes is what you ask it to understand. Pick the ground that looks like yours.

These four are the doors people ask for most, not the whole list. This site has quite a few more environments built: hospitals, schools, building sites, shops, hotels, banking, data centres and prisons. Not seeing yours? Tell us what is in front of your cameras and we will tell you whether IRIS understands it, or not yet.

See it working

Step into a city and look through its cameras.

A collision, a sinkhole, a water leak, a fallen tree. Step into any of them and you will see the raw image and, on top of it, what IRIS understands.

23
examples built
18
raise an alert when something happens
5
only measure

A real city has thousands of cameras. These are the examples that fit on one screen, chosen so you can see the two things IRIS does: raise an alert when something happens, and measure what is not an alarm. Because not everything that matters is an alarm — sometimes what matters is a number.

Enter the city
Illustrated aerial view of a coastal city: the port with cranes and containers, a seafront promenade lined with palms, blocks of colourful buildings, a beach with bathers, a pier and a lighthouse in the distance.

How is it different?

The VMS ended at the recording. The Neural VMS begins at the decision.

The VMS solved recording. IRIS solves what happens next.

Traditional modelIRIS · Neural VMS
Stores videoUnderstands what is happening
Shows camerasPrioritises what deserves attention
Detects motionUnderstands objects and context
Generates alarmsApplies rules and responses
Forces you to review recordingsTurns the archive into something you look up with a question
Produces videoProduces situations, metrics, decisions and evidence
Scales by adding operatorsScales by automating observation and repetitive tasks

Two things worth knowing early

No call to the outside. No meter running.

  • No outside connection

    Video is analysed inside your own installation or in our data centre. There is no outside service the image gets sent to, and none to ask permission from. In local mode you can unplug the internet cable and the system keeps detecting, alerting, measuring and recording just the same.

  • No meter on questions

    There is no charge per question. Not per search, not per alert, not per camera you open. One query and a million queries cost the same, and that decides who ends up using the system: when asking has a price on it, people stop asking and the tool sits idle.

Who this is not for

IRIS is not bought and forgotten. Part of the work is yours.

The most honest thing we can tell you before you read any further is this: nobody from outside knows what matters inside your site. We know how to make a camera understand what it sees. What deserves waking somebody at four in the morning, you know. If nobody on your side sits down and says it, IRIS will end up alerting about things that do not matter, and both of us will have signed off on that failure.

That is why the projects that work have an owner inside. A named person — the head of security, of operations, of the plant — who decides what gets watched, who gets alerted and what changes when the operation changes. Where there is nobody like that, the system keeps the rules from day one and six months later it no longer resembles what actually happens in front of the cameras.

And we are going to tell you no more than once. That this camera cannot read a plate. That this detection is not fixed by software, it is fixed by moving the pole. That the thing you want to measure is not in the image and needs another instrument. If what you are after is a supplier who says yes to everything in the first meeting, you will find one. It will not be us.

  • Somebody has to say what matters

    What deserves an alert and what does not is known by whoever knows the operation. We help you write it down, but we cannot decide it for you.

  • And somebody has to own it

    The projects that fade out are the ones with nobody inside to keep them alive when the operation changes.

  • We are going to tell you no

    Some cameras are not up to what you want. We would rather say so on the site visit than find out on the day of the incident.

  • If nothing will change, do not buy

    If the shift is going to carry on watching the same screens exactly as yesterday, this is just an expense. IRIS is only worth it if it changes how the team works.

What people usually ask

Frequently asked questions

Can IRIS work without internet?

Yes. IRIS can be deployed fully on site and work with no internet connection. Video, models, searches and rules can all run inside the customer's own infrastructure.

Do I have to replace my cameras?

Not necessarily. IRIS is designed to use the video infrastructure you already have, where the integration and available streams allow it.

Does IRIS make decisions for us?

No. Your organisation sets the rules and the limits. IRIS automates their repetitive application and brings people the situations that need human judgement.

What is an NVMS?

An NVMS is a Neural Video Management System: a video management system that also understands what is happening in the scene. It interprets objects, zones, timings and context, applies the organisation's rules and turns video into metrics and evidence.

How long does it take to get running?

It depends on the site and how many cameras are integrated, so we do not quote a generic timeline. The usual path is to start with a few cameras and one or two rules, check it detects what you expect, and grow from there.

Does IRIS replace my current VMS?

It depends on the site. IRIS can work as a complete video management system or sit alongside the one you already have, and that is decided after looking at your camera network, not before. We would rather go camera by camera and tell you what can be done today and what cannot, than promise it fits everything.

How much does IRIS cost?

The price depends on three things: how many cameras come in, how many detections you want on each one, and where the video is processed. We do not publish a fixed price list, because a twelve-camera site and a six-hundred-camera site have nothing in common. Tell us your case and we give you a real figure, not a range.

Does IRIS cut down false alarms?

Yes, and it is one of the reasons it gets installed. Classic motion detection goes off with rain, a branch or a cat; IRIS looks at the scene and works out what is there, where it is and how long it has been there before it alerts. We do not promise an alert will never fire needlessly again, because that does not exist: we promise the noise stops reaching the operator, and that when an alert does arrive, it is worth looking at.

The real interface, step by step

You set the rule once. IRIS applies it every time.

You will see a summary of the interface, played step by step and hands-free. Each round starts with another case. The complete tool does not fit in a demo.

  1. The rule gets built
  2. It goes to every camera
  3. Published, it watches alone
  4. And then it fires
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IRIS · Infinity Neural

And the best part

You do not need to buy cameras:you need yours to understand what they see.

Nothing gets built, mounted or rewired. It plugs into what is already up and running, and the only thing that changes is what those cameras understand.

Tell us your problem and we will say whether IRIS understands it, or not yet.

We reply the same working day.