Cameras that alert you
They watch an area and speak up when something happens that shouldn't: someone in the manoeuvring area without a high-visibility vest. What reaches you is an alert with its time, its camera and its video.
Infinity Neural · since 2011
It understands what happens in front of each camera and turns it into an alert or a number. Without changing the cameras and without touching the system you already have.
A control room with forty screens does not have forty pairs of eyes. It has two. The rest of the video is recorded, stored and watched by nobody.
And when something happens, the really expensive part starts: someone sits down and searches backwards, minute by minute, until they find the moment. That time never appears on an invoice, but it gets paid for.
Counting is worse still. How many people came in, how many lorries unloaded, how long the line was stopped. It is counted by hand, written down by hand, and each day's number depends on who wrote it down.
You don't have to change the cameras. The one already up there stays where it is: what changes is what happens to its image.
Everything goes in. Only what matters comes out. Routine is let through and what matters becomes an alert with its time, its camera and its video — or a number that comes out the same every night.
They watch an area and speak up when something happens that shouldn't: someone in the manoeuvring area without a high-visibility vest. What reaches you is an alert with its time, its camera and its video.
They measure and add up over a line or an area drawn on the image. What reaches you is a number that comes out the same every night and can be audited: how many people crossed that door on Tuesday at seven.
Asking is for finding. Counting is for measuring. And they are not done the same way.
A camera records. What it records is watched by someone, or by nobody. Infinity Neural sits in between: it looks at the image, understands what is there and what is happening, and lets the routine through.
What isn't routine comes out in one of two ways. Either it is an alert —with its time, its camera and its video— or it is a number that adds up and can be compared across shifts, weeks and seasons.
It doesn't replace anyone. It stops people spending their attention watching what isn't happening, which is almost all the time on almost any camera.
One tunes a single case down to the last detail. The other covers the whole installation. They don't compete: they do different things and they are almost always fitted together.
When somebody tells us 'I want the camera to alert me if this happens', there is almost never one right answer. There are two routes, and which one applies depends on how many cases have to be covered, how much precision each one needs and whether that installation has a line.
We study your scene and tune the detection for your case: your angle, your light, your product, your way of working. It is the highest precision possible in THAT case, because it was made for that one. It is processed off site, so it needs a connection. It is organised into six families — the ones below.
The system. It is installed and it covers the whole installation: every camera, many cases at once, with the video, the rules and the alerts in one place. And it works with the internet cable unplugged, which is what you need when an installation can't depend on a line.
It means somebody looks at your camera before promising anything. Where it is mounted, what angle it has, what light there is at six in the evening and at six in the morning, what happens when it rains, what crosses in front of it and how often. That is where the first thing we say comes from, and sometimes it is that it can't be done — and that is bespoke too.
If it can be done, what gets tuned is the detection for THAT scene. It isn't picking a model out of a catalogue and switching it on: it is adjusting it to your product, to the way you stack it, to the clothes your people wear, to the floor markings in your industrial unit. That is why it reaches a precision a general system can't reach in that particular case: because it isn't solving every case, it is solving yours.
What it asks in return is two things. First, time: you have to record, watch what really happens on that camera for a few days and correct. Second, a connection: the video is processed off site, so that installation needs a line that can take it.
And a third that isn't a cost but is worth saying: each tuned case is one case. If what you want is forty different things across forty cameras, tuning them one by one doesn't add up for you or for us. That is when what you need is the other one.
It means a system gets installed and from then on the whole installation is covered. Every camera, not one. Many cases at once, not one. And the video, the rules, the alerts and the history in one place, instead of spread across a recorder, an email and a spreadsheet.
The rules are written by your organisation, which is who knows what deserves an alert at four in the morning. IRIS automates applying them all the time without tiring, which is exactly what a person can't do in front of a wall of screens.
And it works with the internet cable unplugged. For a lot of people this is the first question and the last: there are installations that can't depend on a line, because of regulation, because they are isolated, or because the line that exists can't be guaranteed.
What it doesn't do is tune the way bespoke does. A system covering forty cameras can't be adjusted to each one's scene the way a detection built for a single camera would be. That isn't a limitation of IRIS: it is what covering a lot means.
Because a real installation doesn't have one problem: it has a background layer and two or three things that really matter. The background layer —knowing what is happening on every camera, having the video in order, having the obvious things flag up— is covered by IRIS. The two or three things that actually decide something are tuned bespoke.
One example of the ones that keep coming up: an industrial unit with forty cameras where the two things that hurt are that nobody walks in front of the forklift at the loading bay and that the counting at the door stands up to an inspection. IRIS covers the forty. Those two go bespoke, and one of them type-approved as well.
The odd thing is the opposite: paying for watchmaker precision in forty places where it isn't needed, or going without it exactly where it is.
That one is better than the other. It isn't. A system covering forty cameras can't be tuned like a detection built for a single one, and a detection built for a single one doesn't cover forty. That isn't anyone's limitation: it is how it works.
What we do say is which one is right for you, even if it is the cheap one. And if neither of them does what you want well, we say that too.
So far that is how it is organised. What comes now is the only thing that really convinces: what you see on screen when it is running. Every one of these detections was recorded at a real installation, not simulated — and if yours looks like one of them, you already know what to expect.
Lo que Lemon Neural entiende
Personas: cuántas, por dónde y cuánto tiempo.
Cada una es una grabación del sistema funcionando. Pasa el ratón por encima —o tabula hasta ella— para verla en movimiento.
Casos grabados
Infinity Neural optimiza la ocupación y rotación de mesas en zonas de restauración
Infinity Neural mide ocupación y colas en centros comerciales con IA en tiempo real
¿Pierdes dinero por retrasos, colas y riesgos en el embarque? Infinity Neural para puertos y ferries
Análisis de flujos y zonas de interés en tiendas y supermercados con la IA de Infinity Neural
Revoluciona tu bar o discoteca con Lemon Neural
Lemon neural: optimizando la ocupación de carriles en piscinas
Control de aparcamientos con Lemon Neural
Transforma tu restaurante con Lemon y Rust Neural
Sin rodeos: Lemon Neural descifra cada movimiento humano
Everything above can be shown running. There is one more thing that can be shown signed by someone from outside — and that is usually the one that settles an official file.
Anyone can put a counter on a door. The hard part comes when someone asks where that number comes from. And they do ask. An inspection asks when an occupancy figure has to be justified. The landlord asks when the rent is calculated on footfall. The advertiser paying for impressions asks. The committee asks when it has to decide how much staff to put on a Saturday.
At that point, 'a system we have counts it' isn't enough. You need to be able to say who has checked that the system counts correctly.
Type approval doesn't mean the system never gets it wrong. It means an independent body has measured how much it gets wrong, under defined conditions, and has put it in writing with its stamp.
That is exactly what you need when the number leaves your building and goes into an official file: not a promise from the manufacturer, but the measurement of a third party that doesn't sell the product.
The body here is the Centro Español de Metrología, the one that in Spain makes sure a metre measures a metre.
That it is 'the most precise on the market'. We don't know: that would need every other one measured under the same conditions, and we haven't done it. What we do know, and can be checked, is that it is the only European one type-approved to do this.
Or that the type approval covers any mounting. It covers counting done the way the protocol says: with the camera where it has to be and with the field of view it demands. Mounted any other way it counts just as well or as badly as any other, but it is no longer type-approved — and that has to be said before, not after.
That is everything: why it is needed, what it does, the two ways of having it, how it looks running and which part is measured by someone from outside. What is missing isn't something we can supply.
What is missing is looking at one of your cameras. Where it is, what angle it has, what can be seen from there at six in the evening and at six in the morning. That decides what can be got out of it, and there is no knowing before looking at it.
Sí, y hacerlo es clave para mejorar la efectividad de tus campañas. Cuanto más sepas sobre quién visita tu negocio (edad, género, si vienen solos o en grupo…), más fácil será diseñar mensajes, promociones o productos que realmente conecten con tu audiencia.
La mayoría de negocios físicos no tiene acceso a esta información sin recurrir a encuestas o programas de fidelización. Pero gracias a soluciones de análisis de video con inteligencia artificial como Lemon Neural , ahora es posible detectar y segmentar automáticamente el perfil demográfico de tus visitantes de forma anónima.
Esto te permite lanzar campañas dirigidas con mayor precisión, adaptar tus creatividades al público real que te visita y evaluar qué perfiles responden mejor a cada acción, todo en tiempo real y sin recopilar datos personales.
Leer la respuesta entera →Medir manualmente cuánto tiempo pasa cada cliente en un mostrador es ineficiente y propenso a errores. Sin embargo, existen soluciones basadas en inteligencia artificial que permiten realizar este cálculo de forma automática, precisa y en tiempo real.
Lemon Neural detecta:
Cuándo una persona llega al mostrador.
Leer la respuesta entera →Sí, existen soluciones que permiten monitorizar de forma automática cuántas personas están haciendo cola y cuánto tiempo esperan. Esta información es clave para tomar decisiones rápidas, abrir nuevas cajas cuando sea necesario y mejorar la experiencia del cliente.
Lemon Neural analiza en tiempo real:
El número de personas en cola por caja .
Leer la respuesta entera →Tener demasiadas cajas abiertas en momentos de baja afluencia desperdicia recursos. Tener pocas cuando el local se llena provoca largas esperas, mala experiencia y pérdidas. La clave está en anticiparse y tomar decisiones basadas en datos reales, no en intuiciones.
Lemon Neural te permite:
Medir en tiempo real cuántas personas hay en tienda.
Leer la respuesta entera →Saber si las cajas están funcionando con fluidez es clave para evitar cuellos de botella, tiempos de espera excesivos y una mala experiencia de compra. Pero muchas veces el personal no tiene visibilidad inmediata de lo que ocurre en tiempo real.
Lemon Neural monitoriza continuamente las zonas de pago, detectando:
El número de personas en cola .
Leer la respuesta entera →Las colas son uno de los principales puntos de fricción en la experiencia de cliente. Afectan la percepción del servicio, provocan abandono y afectan directamente a la rentabilidad. Reducirlas no siempre significa añadir más personal, sino actuar con datos.
Lemon Neural monitoriza en tiempo real la formación de colas , su longitud, tiempos de espera y velocidad de avance. Con esta información puedes:
Detectar patrones de saturación en ciertos horarios o zonas.
Leer la respuesta entera →Las colas largas generan frustración, abandonos y pérdidas de ventas. Pero muchas veces no se detectan a tiempo porque el equipo no tiene visibilidad en tiempo real, y tampoco es fácil medir cuánto espera cada cliente.
Lemon Neural te permite monitorizar automáticamente las colas : cuántas personas hay, cuánto tiempo lleva esperando cada una y si se forman cuellos de botella en momentos clave. Incluso puede alertarte cuando se supera un umbral de espera definido, para que tomes medidas inmediatas, como abrir más cajas o reforzar la atención.
Así, no solo evitas malas experiencias, sino que mejoras la eficiencia operativa y mantienes el flujo de clientes sin fricción.
Leer la respuesta entera →Tener rampas, ascensores o zonas amplias es fundamental, pero la verdadera accesibilidad no se mide solo por el diseño, sino por cómo se usa el espacio en la práctica. A veces, un local cumple con la normativa pero sigue presentando barreras reales: puertas estrechas, pasillos obstruidos o mobiliario mal distribuido.
Para saber si tu espacio es realmente accesible, necesitas observar cómo interactúan con él las personas con movilidad reducida: ¿pueden moverse sin obstáculos? ¿utilizan las rutas previstas? ¿hay zonas que evitan sistemáticamente?
Lemon Neural detecta de forma anónima la presencia de personas con sillas de ruedas u otros elementos de apoyo, y analiza sus recorridos dentro del local. Con esta información puedes identificar barreras no evidentes, validar la eficacia de tus rutas accesibles y adaptar el espacio para que sea verdaderamente inclusivo y funcional.
Leer la respuesta entera →Verlo funcionando en IRIS Neural El sistema de vídeo del grupo, con su propia web.
Get started
You tell us what you would like to know from one of your cameras and we tell you whether it can be done, with which family and what it would take. If it can't be done, we tell you that too.