“Guavus and Reverb have a successful history of working together within large-scale carrier deployments, including jointly providing RAN analysis for a Tier-1 wireless service provider on traffic of more than 20M subscribers,”
“Guavus’ operational intelligence platform combined with Reverb’s InteliSON module is a carrier grade solution that paves the way for CSPs to not only achieve true end-to-end visibility into both the bearer and signaling streams, but gain additional insight into network operations so they can realize greater operational and efficiency gains. Our joint solution enables end-to-end network management, all the way from the user’s device, through the RAN, to the OSS/BSS, and enables the operator to optimize networks to achieve both revenue and performance goals,” said Ben Parker, principal technologist at Guavus.
InteliSON modules include Coverage and Capacity Optimization, Dynamic Load Balancing, Automatic Neighbor Relations, Mobility Robustness Optimization and SON Director, for both 3G and 4G networks. Reverb Networks has been awarded a number of SON patents for technologies, algorithms and methods implemented in its software. The company is partnering with leading managed services providers to offer the benefits of the full SON ecosystem to mobile operators. The Company’s partnership with Guavus makes InteliSON the application that turns customer and network data into the right action at the right time for the operator's network.
Guavus’ Reflex Operational Intelligence Platform provides a real time integrated view across customers' business and operations for improved decision making. As a result, CSPs benefit from an end-to-end view across their enterprise with a highly granular resolution and actionable insights that can be embedded into automated workflows to rapidly implement value added services and develop network policies that effectively reduce capital and operational costs. Reflex uses highly optimized computational algorithms and machine learning to distill actionable insights from very large datasets. This allows for continual optimization of the computational process, as well as enables improved forward-looking and predictive analysis, real-time decision-making and workflow automation.