Incelligent enables MNOs to maximize the reliability and performance of their network, through technologies that yield deep insights and foresights (predictions), on their network behaviour and efficiency.
Incelligent facilitates mobile network operators (MNOs) to maximize the reliability and performance of their network, hence, augmenting the customer experience and reducing costs. The approach is based on technologies that yield deep insights and foresights (predictions), on the requirements posed on the network, and on the overall network efficiency and behaviour.
Incelligent derives insights/foresights by analyzing, in various time scales, highly heterogeneous and seemingly uncorrelated input data. The accuracy and long confidence interval of these predictions is amplified by Incelligent’s ability to exploit telco-related data (e.g., performance, availability, reliability) or non-telco-related data (e.g., related to transportation conditions, events taking place, weather conditions, etc.).
Through Incelligent’s technology MNOs boost their competitive advantages by taking the appropriate actions, at the optimal time and location, with respect to the customer experience. Hence, we have proven considerable improvements, in terms of disconnection rate, average or worst download time or bandwidth achieved etc.
In parallel, Incelligent contributes to cost efficiency. MNOs can also drastically reduce their costs, indicatively at 35% level, due to the efficient use of radio resources, the optimal traffic steering and the high automation. Moreover they can increase their revenues, by driving traffic to underutilized network resources.
Our tools learn and predict traffic network state (including demand) per area and time period; the addressable actions include configurations of Mobile (3GPP) and Wi-Fi radio access networks, in terms of allocation of power levels, channels and associated traffic steering. This can be then used either in order to support already available to the MNO SONs (Self - optimizing network software), which will increase their effectiveness through Incelligent's predictive knowledge, or independently, by applying predictive management techniques.