Big Data

Incelligent Analyzer: A tool providing network insights and predictions based on heterogeneous data sources

Do you want to make sense out of the big data of your network logs? Would you like like to know what will happen in your network and be able to take actions in advance? That is exactly what IncelliAna, Incelligent's Analyzer can provide you.

One of the main innovations that it incorporates is the exploitation of highly heterogeneous input. In general, input is either network - related or non - network - related. In our various studies and pilots the network related input includes aspects like the traffic load offered, the network capacity/coverage/performance metrics, the QoS delivered, etc. The collection relies on standardized interfaces of network management systems. The non-network input includes aspects like the weather, the date/time, the associated events in time and space, the user mobility, etc.

Our product uses advanced machine learning and predictive analytic mechanisms for exploiting the heterogeneous input. Our output offers simple, intuitive and sophisticated visualizations of the history and future state of the network. Essentially, the latter includes insights/foresights in the following sample forms:

"probability x% that an element will encounter y% load level at specific time / date range"

"probability x% that elements {a,b} will be congested on Tuesday evening"

"probability x% that an element will be underutilized between hh:mm and hh:mm"

Moreover, our product enables you to drill down and navigate through network big data and find root cause of a problem or exploit an opportunity. 

Incelligent's Analyzer is applicable at Mobile networks, Wi-Fi networks and core networking.

Company: Incelligent
Location: Athens, Greece
Contact name: Serafim Kotrotsos