Jul 17 2020
Guavus, a pioneer in AI-based analytics for communications service providers (CSPs), today announced the launch of Guavus-IQ -- a comprehensive product portfolio that provides a unique multi-perspective analytics experience for CSPs.
Guavus-IQ delivers highly instrumented analytics insights to CSPs on how each subscriber is experiencing their network and services (bringing the outside perspective in) and how their network is impacting their subscribers (understanding how their internal operations are impacting their customers). This single, real-time “outside-in/inside-out” perspective helps operators identify subscriber behavioral patterns and better understand their operational environments. This enables them to increase revenue opportunities through data monetization and improved customer experience (CX), as well as reduce costs through automated, closed-loop actions.
In addition, Guavus-IQ has been designed to be ‘operator-friendly’ for CSPs -- it doesn’t require the operator to be a data science specialist or expert. It combines network and data science and leverages explainable AI to deliver easy-to-understand analytics insights to CSP users across the business at a significantly reduced cost.
The new Guavus-IQ products build on Guavus’ ten plus years of experience providing innovative analytics solutions focused exclusively on the needs of CSPs. The products are currently deployed in 8 of the top CSPs in Europe, Latin America, Asia-Pac and North America.
Big Data Doesn’t Need to Come at a Big Cost
Guavus-IQ consists of two main product categories:
- Ops-IQ, for CSP Network Operations teams seeking to transform their operations with the introduction of AI-assisted analysis, and
- Service-IQ, for CSP Service Operations teams looking to grow revenue, retain subscribers and create new opportunities through a refined customer experience.
Just because data is big doesn’t mean it can’t be resource-efficient. The Guavus-IQ products leverage approximately 50% of the compute/processing-related hardware required by traditional analytics solutions through their use of advanced big data collection capabilities and real-time, in-memory stream processing edge analytics. This results in more powerful data collection from over 200 sources at half the cost.
Ops-IQ provides additional operational efficiencies through a combination of anomaly detection, fault correlation, and root cause analysis -- which not only lower OPEX but elevate CX. Ops-IQ fault analytics suppress more than 99.5% of alarms not associated with network incidents, and accurately predict incident-causing alarms by 93.9%. This significantly improves the Mean-Time-To-Response (MTTR) in a CSP Network Operations Center (NOC), saving more than $10 million a year in OPEX costs currently for a large service provider customer.
Service-IQ also plays a significant role in positively impacting CX and reducing costs. Service-IQ allows for flexible data reuse – when it ingests new data, it ingests data once and then enables the reuse of that same data for additional use cases across both Service-IQ and Ops-IQ. This new level of efficiency saves operators time with ingest, a costly and complex part of the analytics process.
Because the data pipeline of previously ingested data can be automatically re-instantiated for use within Service-IQ or Ops-IQ, CSPs don’t need to become big data experts in order to leverage the power and value of the data they’ve collected. Instead, the Guavus-IQ products apply proven data science methods inside the integrated solutions to do the heavy lifting for the operator. This also allows analytics projects to be streamlined and shortened by more than 40-50%, as many organizations struggle not only with managing and deploying the infrastructure but also with gaining value in the early stage of analytics and AI experimentation.
Supporting Quotes:
In the world of 5G, IoT and now a global pandemic, we’re seeing an even greater need for operators to take advantage of AI and analytics to deal with increased network complexity, operational costs and subscriber demands for improved experience. To address these challenges, operators need to better understand network and subscriber behavior and be able to do so in real time.
These challenges can be tackled by utilizing big data collection, in-memory stream processing and AI-based analytics capabilities to ingest, correlate and analyze data (on premise and in the cloud) in real time from operators’ multivendor infrastructure. Insights generated can then be used to better serve operators’ needs across network, service, and marketing operations.”
Adaora Okeleke, Principal Analyst, Service Provider Operations and IT, Omdia
We’ve seen a lot of excitement from the top CSPs worldwide in Guavus-IQ. Our customers plan to leverage the products for root cause analysis, subscriber behavior analysis, new personalized products, and IoT services, among other use cases. They like the fact that Guavus-IQ is easy to operate and it’s highly instrumented specifically for operators and their multivendor infrastructures versus traditional general-purpose enterprise platforms or homogeneous network-equipment-oriented solutions.”
Alexander Shevchenko, CEO of Guavus, a Thales company