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AI/Automation

Leading Lights 2020 Finalists: Most Innovative AI/Analytics Strategy

The use of artificial intelligence and machine learning in network and service operations has long migrated from a fringe piece of service provider strategies to one that has firmly become embedded in the core.

Those AI-powered offerings and platforms, which all tap into and analyze data to provide quick and actionable insights into what's occurring on the network, have likewise graduated beyond one-off deployments to hit across the entire operation, touching multiple services, network types and the broader customer experience.

This year, nine companies have been shortlisted for "Most Innovative AI/Analytics Strategy." The award goes to the company that has devised the most innovative strategy built around the development or use of AI/analytics capabilities during the past year.

The nine companies in the running are:

The Leading Lights winners, and the identities of this year's Light Reading Hall of Fame inductees, will be announced online, on August 21, during a special video presentation on www.lightreading.com, one month before the start of the Big 5G Event.

Here's a closer look at the companies shortlisted in the Most Innovative AI/Analytics Strategy category:

A1 Telecom Austria – SARA
Following years of development, Austrian telecom incumbent A1 last fall unleashed an AI-powered platform to help support the rollout and ongoing management of mobile networks while also opening the door to sell the platform to other service providers.

While getting some marks for going with a nested acronym, A1's SARA –Superior Analytics of RAN (radio access networks) – owes its basis to supporting network planning and operations, while also expanding into other areas of the business, including marketing, sales and finance within its operations for Central Europe. The platform uses an Open API to help lower barriers of data accessibility so new apps and services can be built on top. At last check, A1 had launched the multi-vendor offering (Ericsson, Nokia and ZTE are among those involved) in Austria, Croatia, Macedonia, Slovenia and Serbia, with plans well underway to debut it in Brazil, Bulgaria and Colombia.

Altran – NetAnticipate5G
Taking aim at the next-generation of wireless, Altran's AI-powered offering is designed to handle self-configuration, monitoring and analysis of 5G networks without human intervention. The company notes that NetAnticipate5G platform is compliant with 3GPP and O-RAN standards and specs, and uses an autonomous feedback loop to help the network self-learn and continue to improve over time.

Use cases for NetAnticipate5G cover a lot of ground, including radio network and fiber layout planning and root-cause analysis. Early adopters include an unnamed tier 1 operator in the Middle East that is deploying NetAnticipate5G to intelligently manage the full lifecycle of 5G network slices. In North America, a global network equipment provider (also unidentified at this point) is using NetAnticipate5G for intelligent health-monitoring and diagnostics functions for its xHaul offerings, the company says.

B-Yond – B-Yond Clarity
B-Yond Clarity aims to add brains to the network, empowering telcos to use analytics to preemptively fix issues, break down organizational silos and provide visibility into how specific network investments are aiding the broader customers experience.

Clarity uses a mix of AI and machine language that, when applied to a multitude of structured and unstructured data, generates what that company calls a "Customer Experience Index," or CEI score that attempts to close the gap between real and perceived CX. The company claims that the platform, which breaks down silos between network and CX teams, has been shown to reduce capex by 4% to 6% and cut churn by up to 5%.

Cujo AI – Cujo AI Lens
Cujo AI Lens is designed to provide operators with granular, dynamic and near real-time actionable insights about how customers are using residential and business networks. A key objective for Lens focuses on providing these data-driven, actionable insights while also respecting customer privacy and maintaining a broader adherence to regulatory compliance requirements.

Using that mix of AI and data, the Lens offering rolls its insights into reporting dashboards that help network operators navigate, cross-correlate and report on info related to connected devices, applications usage, content access, security threats and privacy challenges that occur within consumer and business networks.

EXFO – Nova SensAI
EXFO claims its automated, AI-powered platform provides real-time analytics that can instantly detect, predict, resolve and prevent customer-impacting network performance and service assurance issues. The offering hits on a major need – citing live field trials (plus research from Heavy Reading, the analyst group with corporate linkages to Light Reading), operators are significantly (98.7%) blind to events that impact customer experience.

Rather than relying completely on an aggregated, delayed view of performance, EXFO says SensAI continually analyzes data streams from probes and sensors across all network layers and locations to give operators full, real-time visibility into the user experience and network performance, uncovering problems that could otherwise be hidden to existing monitoring solutions.

Huawei – iMaster NCI
Huawei's iMaster NCE serves as the brain of the fixed network and the network management and control unit of its broader Autonomous Driving Networks (ADN) initiative. By integrating a set of key elements, including the manager, control and analyzer, the closed-loop automation system is designed to hide the complexity of network infrastructures and create simplicity for cross-domain and applications, and to generally achieve what the company calls "single domain autonomy."

Among those elements, the analyzer module of iMaster NCE supports the scalability expansion of on-demand data processing of up to 3,000 types, the company says. Targets for iMaster NCE include home broadband, the optical transmission network and mobile backhaul.

Jio/Guavus – IQ AI/Analytics Strategy
Jio has teamed with Guavus (part of Thales) to deploy an AI/analytics strategy and set of solutions aimed at improving the customer experience of Jio's more than 370 million subscribers.

Under that co-developed deployment, Jio is using AI-enabled analytics products from Guavus to measure real-time CX and predictive analytics to automate troubleshooting of the network and generate subscriber insights in a form that can be used by the marketing division and provide a path to develop custom analytics applications.

Netcracker Technology – Netcracker 2020 Advanced Analytics Solution
Netcracker is working with a major service provider in Europe to deploy a cloud-native platform that enables the customer to migrate its small and medium-sized operating companies to a multi-tenant BSS platform.

Among the early results, the new system has reduced average product offering launch times by 17% by implementing a centralized product catalog and simplifying product configuration. It has also boosted the timeliness of bill cycles and improved overall bill accuracy, Netcracker says.

Transaction Network Services – TNS Call Guardian
TNS says its robocall detection platform has already been deployed by four of the six largest US wireless carriers, among others, as they seek out ways to use data science and machine learning to analyze inter-carrier call data from more than 1 billion daily call events.

While much of the robocall conversation in 2019 centered on implementation of STIR/SHAKEN, the caller ID authentication framework designed to combat illegal robocalls and caller ID spoofing in the US and Canada indicates that a mix of AI/ML will likewise play a critical role in detecting and combating robocalls, says TNS. It launched its Call Guardian Authentication Hub last spring in partnership with Metaswitch.

— Jeff Baumgartner, Senior Editor, Light Reading

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