Don't let the customer be the one who tells you a shipment was faulty.
Scrap, downtime and accidents usually give warning signs: a measured value drifts, a bearing heats up, an escape route gets blocked. Using your existing cameras, sensors and machine data, AI continuously watches quality, machine condition and workplace safety, and alerts the person responsible before a fault turns into scrap, a stoppage or an accident. And you can answer the auditor’s questions with data.
One application for one line or area, in use within 2-3 months · built on your existing cameras and machine data
This is how quality, maintenance and production leaders tend to put it.
“I want to answer the auditor with data, not with opinions.”
Head of quality management, large enterprise
“I want to be able to tell production, with numbers, why we need to stop.”
Head of maintenance and operations, large enterprise
“An audit should be a query, not a preparation.”
Head of quality management, large enterprise
“Everything was fine in the morning, and by noon the line was down.”
Head of maintenance and operations, large enterprise
“I want to see it on the line when something drifts, not at final inspection.”
Head of production, large enterprise
“The same defect shouldn’t keep coming back.”
Plant manager, mid-sized company
Our expert will tell you whether it fits your situation.
At that point the head of quality has to say where the defect arose, why it was not filtered out, and what is being done to stop it happening again. If the root cause depends on who analyses it, and the history has to be gathered from several places, the answer can only be an opinion.
It watches areas and events, not employees
Under the EU AI Act, an AI system that evaluates employees’ performance or behaviour may qualify as high-risk. That is why camera monitoring only starts after a data protection impact assessment and after employees have been informed.
Source: Cuatrecasas
We use your existing cameras and machine data, and fit additional sensors only where needed.
We start on a selected line or area, after the data protection impact assessment and after employees have been informed.
When something deviates, it alerts the person responsible at once, calls them if needed, and automatically opens a ticket or a maintenance work order.
It logs every event with an image for audits, and analyses the causes of scrap and downtime every month.
You can start with any of them. We read the machine data from the machines and the manufacturing execution system.
Camera inspection on the line that flags deviations at once.
It collects OEE, cycle time and the causes of downtime, analyses them with AI, and you can ask it questions too.
From machine data (vibration, temperature, power draw) it predicts failures in advance and opens a work order.
Between two calibrations, it checks whether measuring equipment and machines are still measuring accurately.
It continuously shows the utilisation of machines, lines, the warehouse and the loading area.
Protective equipment use, restricted zones, blocked escape routes, smoke and flame, and forklifts too close to pedestrians.
The cause of a defect no longer has to be pieced together afterwards, from memory.
Who it is for: production and plant directors, heads of quality, maintenance, health and safety and fire protection, and operations directors at manufacturing, warehousing and logistics companies. It can also be introduced at a group subsidiary as a local project; we do not touch the group-level systems.
Existing cameras or cameras that can be fitted, access to the machine data, and a selected line or area to start with. Predictive maintenance also needs at least a few months of machine data.
Rolling out one application on one line or area takes 2-3 months. Predictive maintenance, including data collection, takes 3-6 months. The price depends on which applications we roll out and on how many lines.
Image and video analysis on the line, forecasting quality changes, gathering production data in one place, an executive dashboard you can also query by voice, AI agents handling alerts, and the ticket and work order management of the Omnit business platform.
We do not do PLC programming or machine building. The system does not replace the fire alarm and alarm systems required by the authorities, and it does not replace the health and safety or fire protection specialist.
What we did not cover on this page: the steps from a small first step to the complete solution, why it pays to go this way, and how we work along the way. Feel free to forward it to your colleagues.
In 2-4 weeks, the Situation Assessment shows where most time goes on manual work and how many hours a week that adds up to. It costs HUF 199,000 + VAT, which we deduct from the price of your first development. If we do not find at least 20 hours a week of replaceable manual work, we refund the fee.
Not necessarily. We build on your existing cameras and machine data, and fit additional sensors only where needed.
The system watches the area and the events; it does not evaluate employees’ work. Camera monitoring only starts after a data protection impact assessment and after employees have been informed.
The colleague responsible. The AI alerts them and opens a ticket or a work order, but the decision is theirs. The system logs every event with an image, so it can be looked up later.
Rolling out one application on one line or area takes 2-3 months. Predictive maintenance, including data collection, takes 3-6 months, because it needs at least a few months of machine data.
The price of one application for one line or area consists of a one-off implementation fee and a monthly fee, with discounts for further lines. We give you an exact quote after the Situation Assessment or a conversation with one of our experts.
Production KPIs next to the company figures, with one definition and one owner.
It reads paper checklists and reports, and opens a ticket when something deviates.
A single trusted item master in every system, so the data from the lines can be compared.
How camera images and machine data turn into decisions, and what machine vision can do today
Read on the blog how AI is used in manufacturing, or subscribe to the Signal over Hype newsletter.
Describe the situation in a sentence or two, and an expert in the field will get in touch with you.
Or call: +36 30 235 0100
