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We generate real-time insights into digital workstations and their use.
With our Workplace Intelligence service, we activate a perimeter intelligence that aggregates, reconciles and normalizes information from multiple data sources (virtual environment, antivirus, asset inventory, ITSM history, etc.) to provide a common database, transversal to the IT department.
With our Workplace Intelligence service, we activate a perimeter intelligence that aggregates, reconciles and normalizes information from multiple data sources (virtual environment, antivirus, asset inventory, ITSM history, etc.) to provide a common database, transversal to the IT department.
HW and SW inventory data are not normalized: device duplications, wrong or incomplete SW headers, unrecognized suites, false positives.
Several users experience unexpected interruptions and the support works device by device to identify the cause but it would have been easier to identify the general trend (e.g. long logon times).
Most anomalies require simple operational interventions, such as rebooting, updating, or distributing patches. But it is difficult to recognize unmanaged devices and update delay.
With remote work, users use their personal devices to access company resources, but you don’t have information about their performance and you don’t know how they might affect usage.
HW and SW inventory data are not normalized: device duplications, wrong or incomplete SW headers, unrecognized suites, false positives.
Several users experience unexpected interruptions and the support works device by device to identify the cause but it would have been easier to identify the general trend (e.g. long logon times).
Most anomalies require simple operational interventions, such as rebooting, updating, or distributing patches. But it is difficult to recognize unmanaged devices and update delay.
With remote work, users use their personal devices to access company resources, but you don’t have information about their performance and you don’t know how they might affect usage.
According to IDC research, 41.6 billion connected devices will generate 79.4 zettabytes (ZB) of data in 2025. Edge devices (endpoints + iot Edge) are more and more protagonists in vertical sectors, such as healthcare, retail, supply chain. You have to use this data pool to good use so that it creates value. To do this, you should:
Manually aggregating data from multiple sources takes days to work, and in the meantime, new devices may be added that you have no visibility on. La maggior parte degli strumenti di inventariazione non sono in grado di fornire un elenco dell’istallato la cui qualità sia sufficientemente accurata. Dovresti predisporre sentinelle di avviso sulla data quality and use AI to reconcile and normalize inventory data quickly.
You need detailed information about connectivity and device status, as well as processes and running services. For each workstation you should have a risk assessment, such as the reputation of the installed software, the estimation of the succes of the updates and any proposals for improvement to make it more performing. These are data you already have, but they are not organized in such a way that you can make use of them easily. The detail must be ascribable in an overview, to understand if the same anomalies are impacting more devices and require massive intervention.
Manually aggregating data from multiple sources takes days to work, and in the meantime, new devices may be added that you have no visibility on. La maggior parte degli strumenti di inventariazione non sono in grado di fornire un elenco dell’istallato la cui qualità sia sufficientemente accurata. Dovresti predisporre sentinelle di avviso sulla data quality and use AI to reconcile and normalize inventory data quickly.
You need detailed information about connectivity and device status, as well as processes and running services. For each workstation you should have a risk assessment, such as the reputation of the installed software, the estimation of the succes of the updates and any proposals for improvement to make it more performing. These are data you already have, but they are not organized in such a way that you can make use of them easily. The detail must be ascribable in an overview, to understand if the same anomalies are impacting more devices and require massive intervention.
Artificial Intelligence is a valid support to quickly and accurately inventory data.To optimize your team’s time, you should then make them operable, integrating the collected information into automated workflows for patch distribution, anomaly resolution, criticality management. You just have to define the context rules, to make them operational.
We provide operational device information with sensor-based perimeter intelligence
,which suggests - upon query - insights, activity trends and real-time actions.
It is the starting point to codify and automate intervention and support operations effectively, saving time, costs and resources.
We provide operational device information with sensor-based perimeter intelligence
,which suggests - upon query - insights, activity trends and real-time actions.
It is the starting point to codify and automate intervention and support operations effectively, saving time, costs and resources.
We provide quick awareness about your own IT estate.
We simplify the detection and resolution of anomalies.
We connect intelligence to operation.
We provide quick awareness about your own IT estate.
We simplify the detection and resolution of anomalies.
We connect intelligence to operation.
Would you like to have up-to-date information about your workstations
to better plan your operations?
Would you like to have up-to-date information about your workstations
to better plan your operations?
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