Build powerful and comprehensive location-based multidimensional segmentation models, perform in-depth analysis based on handset, service uptake and usage.
​
Facilitate a seamless boarding experience that eases subscribers onto the network and allows for rapid service uptake and promotions.
​
Enhance service offerings and brand equity by engaging targeted campaigns based on a wide variety of customizable features.
​
​
Passive probing of network interfaces with zero impact on operational core forms real-time insights and actionable subscriber information and segmentation.
A robust and versatile standards-based platform that is flexible enough to incorporate a multitude of add-ons and customizations.
Intuitive and iterative implementation of Machine Learning ensures best use of historical or real-time data based on Big Data to enhance analysis, reporting and planning.
Intelligent provisioning of network services based on smart device detection and subscriber profiles to enhance quality of service and management of licensing costs.
Enrich subscriber intelligence by joining external data and reports to the data in the datalake.
A next generation solution to meet legislative compliance, protect network integrity, manage devices, subscriber profiling and commercial engagements.
Profile subscribers through the powerful and comprehensive location-based, multidimensional segmentation models, perform in-depth analysis based on handset capability, service uptake and usage – combine demographics and activations, faults and ARPU data in one simple reporting tool.
Use back-consolidation to link historical data to geo-location and incidents after they happened. Build a comprehensive oversight over the commercial performance of campaigns, subscriber segmentation and device types. Track Customer service calls across implication of new handsets or subscribers – even after they occurred.
Utilize customizable data visualization models, benefiting decision-makers across the enterprise to provide pattern recognition and superior analysis of trends and provide salient input into projection and forecasting.
Embrace a seamless boarding experience that eases subscribers onto the network and engages a rapid VAS uptake through targeted promotions and services.
Measure and monitor customer boarding experience through integrated customer service call monitoring and handset connectivity measurement - catch negative experience on-the-fly and enable proactive subscriber engagement. Measure activation results, update and quality of the boarding. Tailor offers and packages to handsets capabilities and service states through advanced subscriber profiling.
Integration into Customer Services Systems and loyalty programs to message and alert call center staff that this is a boarding customer or use the Open Machine Learning Tools to present best matching services and predict subscriber loyalty based on the current boarding experience.
Turn historical data about tracked usage patterns into actionable information to engage personalized campaigns for superior subscriber experience management by location, by data and/or voice consumption patterns and device upscale trends.
Enhance service offerings through IA, and, brand equity by engaging targeted campaigns based on a wide variety of customizable features.
Investigate service activation and uptake, store and replay subscriber movement in both historically and in real-time. Examine subscriber profile information and segment by multiple variables and locations - allowing for seamless service optimization and customization – and reuse this for allocating services and provisioning.
Automatically collect aggregated information on subscriber behavior to assist in developing personalized offerings to subscribers and to gain insight into how, when and where subscribers are invoking service.
Leapfrog data source integration through inobtrusive probing of service and service usage by utilizing the built-in probe for 2G, 3G, 4G and 5G networks. Utilize an easy to use data integration and collection solution working in the background to collect and group data from the network on-the-fly and in real-time.
​
All data is stored securely, ensuring that no subscriber can be personally identified and guaranteeing subscribers their privacy. Map what kind of data subscribers are using, what time of the day or night they are most active, and, the services they use most.
Drive internal development of new services by using Open API's for integration within existing systems and architecture, such as billing systems and Data Warehouses. Create internal services and prototype new offerings using industry standard tools like Visual Studio and NodeJS.
​
Build and utilize triggers based on predefined profiles – interface with deployments across internal networks, platforms and within enterprise systems to allow for seamless access to data sources and incorporation it into a homogeneous solution for developing new services.
Turn data, past and present, into future earnings by enabling easy to use model building based on an intuitive and iterative implementation of Machine Learning that ensures best use of historical or real-time data based on Big Data to enhance analysis, reporting and planning.
​
Use adaptable TensorFlow data models to create adaptive self-learning algorithms and intelligence to access, model and apply data sets. Interactively learn and refine, then perform future projection and forecast trends - and collect training sets and data - using integration to upload to google cloud or Microsoft Azure for processing of training. Install and update the models through continuous training to accommodate for changes in handsets and subscriber behaviour dynamically.
Intelligent provisioning of network services based on subscriber profiles and detection to enhance quality of service and management of licensing costs. Enable network resources on-the-fly utilizing a combination of subscriber information and handset information allowing intelligent provisioning of services based on device capabilities and subscriber profiling.
Offers measurable outcomes for reducing licensing costs, allowing automatic re-distribution of licenses based on device capabilities, enables allocation of capacity based on actual usage and possible usage by removing licensing in non-covered areas, on roaming and handset change.
Use the intelligent provision engine to enable flexible implementation of dynamic resource allocation from subscriber licensing over data to allocated frequencies.
Enrich subscriber intelligence by joining external data and reports to the data in the datalake by access through a standard API.
Allows for seamless integration of disparate data types, source systems and archival systems. No crucial information is inaccessible, no data is un-mapped.
Nuanced and supplementary data streams can be integrated and keyed into the storage model.
A next generation solution to meet legislative compliance, protect network integrity, manage devices, subscriber profiling and commercial engagements.
​
Create innovative services combining locations with device locking in geo-location for fixed "aired" solution in competition with fixed-line and fiber operators, or use the intelligent service selection to force 4G services in 4G coverage areas by disallowing 2G and 3G access on the fly using probe data to identify subscriber location. Block 5G fixed terrestrial installation from moving around to guarantee capacity and quality.
​
Employ next-generation functionality and support for networks from 2G/3G, 4G/LTE to 5G. Fully standards-compliant to enable integration with existing and planned infrastructure over an intelligence and rules-based system to ensure flexibility, mitigate problems with registration, and simplify Operator's meeting of regulatory requirements