Guavus operational analytics brings together network, machine and sensor generated data within the context of enterprise data to identify new business opportunities, uncover security threats, enhance service quality and identify performance management issues. Our suite of operational analytics applications deliver contextually aware insights that enable better quality and timely decision-making and can be embedded into workflows to optimize business processes.
Collect, analyze and mediate IPDR (Internet Protocol Detail Records) from virtually any IP data sources in Telecom (such as Edge, Core and Access networks across any of the IP layers) and Cable such as cable modem termination systems (CMTSs) to address metered billing, bandwidth management, subscriber policy enforcement and other network activity.
Full support for DOCSIS 3.0 / CCAP IPDR Service Definitions and protocol modes. Proven deployments in large scale IPv6 Cable environments.
Guavus Service Assurance™ analytics applications allow Service Providers – Mobile, Fixed, and Cable – to improve the quality of experience (QoE) for subscribers and create better operating efficiencies. By correlating network related events with customer-impacting events, Guavus enables Service Providers to reduce the cost of care with fewer calls, eliminate unnecessary truck rolls, and automatically create/update/remediate network tickets based on advanced KPI monitoring, base-lining and anomaly detection.
Faster MTTR (Mean Time to Repair) —Reduce time and cost of resolution for ticketed and non-ticketed care inquiries with real-time root cause analysis and anomaly detection. Rapidly detect and diagnose service issues based on unique attributes of affected customers and route calls from affected customers to appropriate call menus based on problem severity.
KPI Monitoring and Identification—Understand the customers overall quality of experience with timely analysis of various network layers with drill down analysis into Radio Frequency performance, radio conditions and content mix for each service and provider. Identify key performance influencers and visualize degree of influence of contributing KPIs in relation to the service resource context for faster root cause and issue isolation.
Correlation and Impact Analysis—Reduce the complexity in diagnosing device and network issues. Clarify the impact of network operations on customer support by linking planned maintenances and outages via real time anomaly detection and root cause analysis
Align tactical network operations decisions with Radio Access Network (RAN) performance for quicker root cause analysis and relevant prioritization. Integrate network alarms with network performance, and align with subscriber activity to identify performance per subscriber or by an enterprise group.
Proactively monitor relevant performance metrics for various layers of service using automatically generated alerts. Understand the quality of experience (QoE) subscribers are having for 3G and 4G services and quickly identify the root cause when a specific network node impacts that service.
Traditional security solutions can’t provide the up-to-date and relevant network information CSPs need to effectively address rapid traffic growth and volatile traffic patterns. Guavus Security™ analytics applications use low-latency heuristic-based detection algorithms to identify DoS/DDoS attacks. The detection mechanism uses machine-learning methods by correlating data across the network to reduce false positives and generate more accurate alerts. The accelerated access to alerts means that network operations can react faster and more efficiently to protect customers and the network infrastructure from security attacks.
Increase revenues and expand customer base by identifying the right sales prospects for wholesale IP networks. Improve the bottom line by profitability analysis for customers and traffic analysis for Peers. Understand end-to-end visibility across various business entities in global IP networks.
Analyze NetFlow data to provide timely insights on how customers and peers interact with the network, analyze customer profitability, while evaluating risk profiles and churn analytics
Identify sales prospects that offer revenue uplift, design more profitable pricing plans to achieve higher margins and rebalance peering agreements based on existing service level agreements (SLA’s)