AI, IoT and immersive technology, put to work on specific business problems.
Technology that starts with the problem.
AI, IoT, immersive technology and experience monitoring, applied to specific business problems. We do not adopt a tool because it is trending.
What you get
AI and machine learning
Find patterns in your data, forecast what comes next and improve key processes. We start from the business problem, not the model.
Internet of Things (IoT)
We connect your devices and systems, so the data they produce reaches the people who act on it.
Immersive technologies (AR, VR and metaverse)
Engage customers, train staff and work together across teams with AR, VR and metaverse tools.
Digital experience monitoring
We watch the digital services your customers and staff use, in real time, so problems are found and fixed quickly.
How it works
Pick one question
We start from a business problem, such as demand, equipment failure or slow digital services.
Prepare the data
We connect the devices and systems involved and prepare the data the work depends on.
Build and test
We build the model, platform or tool and test it on real cases.
Put it to work
We bring the result into the process your people already use.
What changes when the technology fits the problem
Problems predicted early
Models built on your own data flag issues before they affect service.
One live view of assets
Devices and systems share one platform, so live data reaches the right teams.
Data ready for what is next
Clean, connected data supports analytics and AI later.
Training without downtime
Staff practise in a simulated environment, and experts guide work from anywhere.
Problems found before users complain
We monitor the experience from the user’s side and trace each slowdown to its cause.
A working use case
The aim is a result in live operations, not a stalled pilot.
A typical scenario
The situation
A large operator holds years of maintenance, customer or case data. Teams still react to problems after they happen.
What we do
We pick one business question, such as demand, equipment failure or fraud. We prepare the data, build and test the model, and put it into the process people already use.
What changes
Problems are predicted before they affect service. Decisions rest on patterns in your own data, and the use case runs in live operations.
A typical scenario, not a named customer.
What each capability delivers
Taken from typical scenarios in large enterprises and public bodies.
AI and machine learning
Problems predicted before they affect service. Decisions based on patterns in your own data.
Internet of Things (IoT)
One live view of assets across sites. Issues spotted from data, not from complaints.
Immersive technologies
Staff trained without taking equipment offline. Less travel for training and expert support.
Digital experience monitoring
Problems found before users complain. Service levels measured on what users experience.
Questions we are asked
Where should we start?
Start with the problem, not the technology. If you hold data but react late, look at AI. If devices run on separate systems, look at IoT. If users report slowness your dashboards miss, look at experience monitoring.
Do AI and IoT projects need clean data?
Yes. They depend on clean data from your core systems, so we prepare the data before we build the model.
What is the difference between Emerging Technology and Enterprise Applications?
Emerging Technology applies AI, IoT, immersive technology and experience monitoring to specific problems. Enterprise Applications covers the systems that run the business. One Emircom team delivers both across the UAE and KSA.
Where do multi-cloud and data analytics sit?
They sit with Data Centre and Hybrid Cloud, so one team owns your infrastructure and your data platforms. Emerging Technology applies new tools on top of them.
Can immersive tools help with training?
Yes. We build AR and VR training and remote-assist tools. Staff practise without taking costly equipment offline, and experts guide work from anywhere.