Guavus: Streaming AI and Data Analytics from the Forefront of Integrated Innovation

Stephen Spellicy

Guavus offers a platform, the Guavus Reflex Analytics Fabric, (RAF) which makes the development, deployment, and operation of machine learning based applications simple and fast. The company also offers a specific communications service provider (CSP) analytics applications for network operations, customer care, marketing, data monetization, IoT, and security use cases. Deployed in the top telcos, mobile and cable operators worldwide, Guavus differentiates itself on its CSP industry expertise, domain knowledge, and long CSP track record of success, and the ability to handle massive scale: at one operator, company’s Reflex solution processes 5 petabytes of data a day.  It runs its analyses very early in the data lifecycle, meaning that it can discard duplicate and unimportant raw data quickly.

Guavus develops software that provides highly instrumented analytics and uses cases that pertain to specific focus areas of the CSP market. For instance, the company has a large number of mobile customers using its marketing analytics solution, called Marketing Insight, to better understand mobile subscriber behavior.  For cable and mobile carriers, Guavus has customers that exclusively use its operational intelligence products to solve network monitoring and SLA management for their network operations and customer care teams.

 

All-Encompassing Set of Services

Guavus enables CSPs to leverage both customizable ‘self-service analytics’ and out-of-the-box analytics applications for advanced systems planning and operations, mobile traffic analytics, marketing, customer care, security, and IoT.

Guavus’s products have been architected and designed from the ground up to elegantly handle petabytes of data at high speeds. Built on an open big data platform, Guavus RAF is designed to ingest, process and analyze large datasets that are particular to CSPs. It’s flexible, scalable and allows customers to deploy both Guavus applications and build custom apps, leveraging the company’s advanced analytics techniques, and algorithms.

The Guavus RAF platform incorporates data processing and analytics layers, and supports the following modules:

•  Marketing Insight: Subscriber based intelligence

•  Live Ops: Service assurance for network operators

•  Security Intelligence: Network security insight

•  Smart Care: Customer care recommended actions

•  Edge Analytics for Smart Cities and IoT: IoT operations analysis

All of the company’s products are resilient and extensible, designed to easily integrate into CSP networks. Guavus streaming data collection systems are highly available with local redundancy and have the ability to replay data in the event of system failures. The company’s flexible-binning methodology allows it to intelligently and automatically handle data delays or mismatched speeds when aggregating data from multiple sites without any manual intervention. The solutions integrate with legacy systems and have been designed to co-exist with existing data warehouses to minimize duplicate technologies and avoid multiple collection scenarios.

 

Inputs for Technology

“At the forefront of AI-based real-time analytics and machine learning innovation, Guavus is driving digital transformation at all of the Tier 1 MSOs and at 6 of the 7 world’s largest telecommunications providers. Using the Guavus Reflex solution, the company’s customers are able to analyze big data in real-time and take decisive actions to lower costs, increase efficiencies and dramatically improve their end-to-end customer experience – all with the scale and security required by next-gen 5G and IoT networks”, said Stephen.

Guavus was founded on two key values, in which it still leads. First, the company understands that its value lies not simply in analyzing data to offer a superior interpretation of the world, but in fact, using data to change the world, that is, to drive decisions which save money, make money or otherwise help its customers’ transform. Second, Guavus’s perspective has always been that service providers’ and IIOT providers’ major product is the customer experience they deliver. Therefore, machine learning and data analytics lens should always be the subscriber. Simple as this sounds, the implications of this perspective are transformative for Guavus’s customers who today deal in a world focused on network elements and aggregate traffic flows.

The company builds tools that are driving transformation in CSP Care Operations, Field Operations and NOCs today. By incorporating years of feedback from inline field deployments, Guavus tools are designed to turn the insights generated into actions quickly; insights that are easy to understand by front-line team members and drive operational excellence while integrating with its existing toolsets.

Guavus customers’ success is the company’s success. Deploying its solutions is only the first step in the process towards operational efficiencies, OPEX savings, and improved Net Promoter Score. The company works hand-in-hand with all key stakeholders within a customer’s business to best understand their success criteria, what’s needed to guide their teams in order to realize the maximum benefit, and constantly strive to improve the user experience for advanced analytics. Guavus combines data and computer science with domain expertise to provide a robust yet open solution that will evolve with its customers’ business needs, now and in the future.

 

Analytics Graph from Present to Future

It is no longer good enough to leverage a diagnostic or descriptive analytics approach.  And companies are quite tired of looking in the rear-view mirror in terms of hindsight, what happened, why, and when. In contrast, some of the largest CSPs in the world use Guavus’s AI and analytics technology to predict and prevent issues from happening before issues and events occur. This has a profound impact on improving their customer satisfaction, increasing their Net Promoter Score and retaining subscribers (stemming their customer churn).

A predictive analytics approach is essential, especially based on the sheer volume of data and events per second in its customers’ networks. The issue is that the footprint of data is way too large for a human to manually explore or intervene in real-time. In contrast, a much more effective approach is to leverage artificial intelligence and machine learning to automate the discovery of pattern and anomalies and to deliver insights and recommendations. This approach gives customers a massive scale in their operation and allows them to be far more proactive, less reactive.

 

Uniqueness to Stand Out Among Rivals

Guavus has been fortunate to have the advantage of extremely strong technology as its foundation.  However, the company has a unique differentiator beyond technology alone — it combines data and computer science with domain expertise. Guavus has the ability to not only understand its customers’ business, their data, but the right approach to derive value from the data to deliver actionable insights which yield a tangible return on investment and competitive advantage for the customers. The company has helped CSPs reduce costs (bottom line) through gained operational efficiency and enabled them to generate revenue (top line) through data monetization opportunities.

 

Emergence of Tech-Evolution

Guavus firmly believes that its CSP customers are at an inflection point — with their planned adoption of 5G, increasing reliance on network virtualization and the introduction of AI in their operations. They are facing an unmovable forcefield that requires them to transform in order ‘to pass go’ and continue their journey.

The use of advanced analytics, AI and automation are critically important as networks densify, network services diversify, and customer experience becomes one of the primary metrics tracked by CSPs.

In order to be successful in their digital transformation, CSPs will require:

•  Turnkey use cases: With the exception of a handful of the largest operators, CSPs want solutions that address specific needs and can be integrated quickly. Most will run on a broader company platform, but the specific use case is paramount.

•  Analytics must be real-time and predictive: To support high reliability and agile operations, CSPs must have a view of network and service performance in real time, requiring continuous intelligence. Wherever possible, analytics should also identify impending problems so they can be fixed in advance.

•  Scale and easier integration: Each network element and service produce its own stream of data; CSPs often rank among the largest big data implementations (producing and consuming PBs daily) in a given country. Solutions should be robust enough to process this data speedily and reliably, and mature enough to deploy in the CSP’s environment relatively quickly.

•  Ease of use and the ability to interactively explore their data: Dashboards, predefined queries, and interfaces that enable queries by multiple personas, such as operations, data engineers, data analysts, and data scientists — to increase a network analytics solution’s usefulness. APIs and other capability exposures enable the solution to feed into automated operations.

•  Future-proof their analytics investments: Analytics solutions must demonstrate that they can handle network slicing, virtualized networks, and new service types, especially with the advent of 5G and massive growth from IoT.

 

Aspiring for Tomorrow

Guavus is focused on discreet, high-value use cases that leverage Guavus RAF as a foundational product.  Use case driven applications will be developed and delivered through an “app store” like experience. The use cases solve specific challenges that CSPs face as they embark on their digital transformation. Key target areas of the company’s innovation agenda are enabling CSPs to be better equipped to support network modernization, improve customer engagement, move behind the pipe (OTT) and provide competitive advantage through innovation. RAF and the targeted set of use cases listed in Guavus’s innovation agenda address these critical areas and provide a method for CSPs to build upon. Many of these are already being developed and early versions are actively being used by customers today.

Guavus has delivered tried-and-true products to the CSP market which the company will continue to invest in into the future. These products tackle major issues for Guavus’s existing customers and will enable them to improve operational intelligence and efficiency which will help them save money while creating new revenue opportunities.  The foundation for the company’s existing and future products is RAF. It enables the scale, performance, and flexibility to ingest, manage and analyze CSP data at scale.

From a business plan and strategy standpoint, the company has two primary paths to market: CSP led and Thales (Guavus’s parent company) led. Guavus has an investment strategy for each. For CSPs, the company has invested in developing a focused business plan to serve this market. This is supported by regional sales and CTOs, and product management with direct experience in the CSP market. For the Guavus’ CSP growth plan, the company will continue to hire domain experts in all geographies to serve its customers. Today Guavus has the footprint in most of the CSPs globally, with a predominance in the Americas and EMEA. In all geographies, its primary focus will be to introduce new use cases tied to the company’s customers’ digital transformations, taking advantage of the company’s RAF platform.

For Thales-led pursuits, Guavus is enabling Thales to leverage its RAF platform as a foundational component they can use to address the key needs of their customers. Their customers span defense, transportation, aerospace, and aviation – and are in more than 60 countries worldwide. The company is collaborating to embed RAF software into Thales product offerings and develop new solutions for their customers in areas such as preventive maintenance, predictive maintenance, IoT device/component monitoring, and monitoring secure IoT connectivity.

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