?? Scaling, Simplifying, and Monetizing: The Future of Telecom

From managing skyrocketing data volumes to unlocking AI’s real potential, telecoms are at a crossroads. This month, we’re diving into:?

?? VMs vs. Kubernetes – Is your mediation infrastructure ready to scale??

?? Customer Success Story – How one CPaaS provider tackled data complexity.?

??? Podcast Feature – The real monetization challenge? It’s all about customer value.?

?? Quick Tip – A pro tip on AI-driven pricing transformation.?

??Industry Insight: Is Your Data Mediation Infrastructure Built to Scale?

Why More Telecom Operators Are Moving to Kubernetes for Data Mediation?

Telecom operators handle massive volumes of network and service data daily. From real-time billing to processing surges in usage data during live events, data mediation is at the heart of seamless operations. But as data demands grow, is your infrastructure ready to scale??

For years, operators have relied on Virtual Machines (VMs) for data mediation. While VMs provide a stable, familiar environment, scaling requires manual provisioning, which can lead to inefficiencies in handling fluctuating workloads. That’s why more telecoms are shifting to Kubernetes—a cloud-native approach designed for flexibility and scale.?

Why Kubernetes is the Future of Data Mediation?

? Dynamic Scaling: Automatically adjust mediation workloads to handle traffic spikes in real time, reducing costly over-provisioning.

? Optimized Performance: Process high-volume CDRs and UDRs with low latency, ensuring seamless billing and usage monitoring workflows remain responsive—even during peak loads—without the delays associated with manual VM scaling.

? Future-Ready Flexibility: Adopt containerized architectures and CI/CD pipelines for faster deployments and cloud-native integration.

The Bottom Line??

Kubernetes is redefining data mediation, giving telecom operators the agility and efficiency needed to stay ahead.?

?? Want to dive deeper? Download our latest White Paper where we break down the key differences between VMs and Kubernetes for data mediation—helping you make informed deployment decisions.?

?? Customer Success Story

How a Comms Provider Dealt With System and Data Complexity With Automation and Efficient Processes?

Global Communications Platform, as a Service provider, addresses revenue leakage, data complexity, and inconsistent reporting with consolidation, automation, and efficient processes.

Customer:??

This Communications Platform as a Service (CPaaS) has acquired a significant number of messaging companies over the last number of years and now faces the challenge of integrating processes, architectures, operations and technical platforms from these disparate companies into a single efficient entity.?

Challenge:??

Following numerous acquisitions, the company's system architecture became overly complex, incorporating various commercial and in-house tools, leading to disjointed processes. Operationally, inconsistencies arose in customer billing for messaging services due to unreliable usage report deliveries from carriers and invoice synchronization errors, leading to mismatches between services consumed and invoiced.?

Solution:?

By creating a common, centralised location for the data coming in from multiple systems they would be able to reconcile transactions and identify errors or discrepancies. With this level of visibility and controlof the data, the company could generate accurate reports to support revenue and settlement accuracy and assist in forecasting for revenue leakage avoidance.?

Outcome:?

With the DigitalRoute Usage Engine at the heart of the company’s solution, it now has a single source of truth and simplified access to master data across all business functions. All data from multiple systems is located in a single location, and Usage Engine has become the commercial solution for SMS Billing Mediation. The solution will support the company with the reporting on revenue leakage and help prevent it in the future.?

Read the full customer story here.

??? Podcast Feature

What is the current state of AI in the telecom industry, what are the challenges, and what are the potentials for growth? Geoff Hollingworth, CMO of Rakuten Symphony, shares his company’s data-driven approach to customer-centricity and the importance of modern infrastructure in leveraging institutional data.

Key Insights?

1?? AI is just technology

“Do you care about technology, or do you care about customers? That foundational approach to the market defines some of the largest companies that have been most successful versus companies that are struggling to fit in. The biggest companies care about customers and they’re trying to serve value to fit into where customers are looking for and have needs. I think the telecom industry is stuck in cycles of obsession about technology that it becomes very hard to unlock immediate and short-term opportunities.”?

2?? Breaking Data Silos?

“What is currently existing in telecom is legacy infrastructure and operations from the last 30 years. There’s a huge amount of data that flows through the system, but the data is not available or addressable by the business especially in real-time. It’s siloed. It’s locked. So the first thing that telecom has to do is actually what Rakuten has spent the last five years doing, which is building a modern infrastructure, and it’s not the infrastructure per se, it’s the software layer that sits on top that allows you to take all that institutional data and surface it into a consistent, usable form.”

3?? Make Everything AI-enabled?

An efficient use of AI enables organizations to eliminate huge amount of manual tasks. AI is an advanced tooling that enables Rakuten to automate everything that can be automated in network operations.??

??? Check out the full episode with Geoff Hollingworth to learn more about AI and monetization in the telecom industry here.

?? Quick Tip of the Month

As more and more companies launch AI features, Jeff MacMillan from Autodesk advises to test out Beta or Early Access Programs.

“Prior to launching Autodesk Flex, we had a pilot with 15 large-ish customers that were spending greater than six figures of US dollars with us. The sales reps were hand holding the customers. We were working with partners. It was on a very small scale and we were actually able to take the learnings from that and then apply it to the mass market and sell Flex in quantities as low as 100 tokens or 300 US dollars.”?

That's all for now! If you enjoyed this newsletter, be sure to subscribe so you don't miss out on next month's issue. See you in March! ??