As telecom networks become more complex and operators face rising costs, fragmented data, and the need for real-time optimization, Kenmei’s AI-driven automation solutions are helping communication service providers (CSPs) shift from reactive troubleshooting to proactive decision-making. The company’s cloud-native technology streamlines operations, boosts network performance, and ensures seamless data integration, all while maintaining security and control. By utilizing artificial intelligence (AI), Kenmei enables operators to work smarter, reduce inefficiencies, and pave the way for self-optimizing networks.
In an exclusive interview with Telecom Review, Vicent Soler, CEO of Kenmei, highlighted how the company’s innovative approach is transforming telecom operations and shaping the future of network automation.
How do Kenmei's cloud-native solutions specifically address the most pressing challenges telecom operators face in their digital transformation journey?
At Kenmei, we understand operators' critical pain points, from fragmented data systems to rising operational costs and increasing complexity in network optimization.
Our AI-driven solutions are designed to relieve engineers' burdens, automating everything from network anomaly detection to real-time optimization.
One of the biggest concerns for CSPs is interference management. Traditional solutions require manual intervention and a reactive approach. Our machine learning (ML)-driven interference detection system works proactively, automatically classifying and geolocating radio frequency (RF) interference before it impacts service quality.
The days of siloed network analysis tools are coming to an end. Our cloud-native Data Fabric seamlessly integrates multi-domain data, enabling operators to analyze performance holistically. Instead of relying on multiple isolated tools, CSPs can now access a unified, intelligent network optimization platform.
Ultimately, our goal is to shift telecom operations from a reliance on manual, engineer-led decision-making to AI-driven automation, ensuring operators can deliver better service with fewer resources.
Can you elaborate on how Kenmei’s Data Fabric enhances data governance and security while ensuring seamless integration across multiple systems?
Telecom networks generate massive amounts of data, but the real challenge is making that data usable across various network functions without compromising security. Our Data Fabric is engineered to solve this.
Unlike traditional systems that create isolated data silos, our Data Fabric ingests and correlates data from multiple sources—including configuration management (CM), performance management (PM), and fault management (FM), and call traces from all significant radio access network (RAN) vendors.
This ensures CSPs have a single source of truth for network analytics, enabling more intelligent decision-making.
Security and governance are non-negotiable in telecom. That’s why we’ve designed our solution to execute queries within the operator’s environment, eliminating the need to expose sensitive data to external cloud-based AI models.
One of the most powerful aspects of our Data Fabric is its ability to scale. Operators can use their agreements with cloud providers to minimize costs while maintaining complete control over their network data. Instead of building costly in-house analytics solutions, CSPs can leverage our framework to turn raw data into actionable insights instantly.
What measurable impact have Kenmei’s AI-driven automation solutions had on reducing operational costs and improving network efficiency for telecom operators?
AI-driven automation is about cost reduction, but mostly it’s about efficiency. Traditional troubleshooting methods require engineers to sift through dashboards and reports manually. Our AI Agents handle this automatically, detecting and resolving network anomalies in real-time. This reduces downtime and improves service-level agreement (SLA) compliance, keeping customers satisfied.
CSPs often spend millions on field testing, including drive tests to evaluate network performance. Our AI models process mobility data at scale, reducing the need for physical drive tests while still providing accurate network performance insights. This significantly decreases operational costs while increasing speed-to-resolution.
When it comes to network optimization, timing is everything.
Instead of reacting to congestion or interference after service quality is already impacted, our AI models proactively predict and mitigate issues before they escalate. This ensures networks remain resilient even under heavy load.
By automating routine network management tasks, we free up engineering teams to focus on strategic initiatives rather than firefighting operational issues. This shift enables operators to scale efficiently while keeping costs under control.
With AI and automation evolving rapidly, how is Kenmei staying ahead of the curve to ensure its solutions remain innovative and future-proof?
The telecom industry is at an inflection point. Traditional software models, where engineers rely on predefined dashboards and tools, are becoming obsolete.
We believe the future belongs to AI-driven decision-making, and we’re already leading that charge.
Our transition from Software-as-a-Service (SaaS)-based tools to an AI Agent ecosystem is key to our long-term innovation strategy. Rather than requiring engineers to interpret data manually, our AI Agents autonomously analyze, decide, and act, notifying engineers when necessary.
Scalability is a core principle of our approach. Our modular AI Agent framework allows CSPs to deploy automation incrementally, ensuring they can evolve without a disruptive overhaul of their existing infrastructure.
Our investment in our Data Fabric technology ensures we remain compatible with evolving telecom architectures. By supporting multi-vendor, multiple radio access technology (multi-RAT), and cloud-native deployments, we provide operators with a future-proof automation framework that can adapt as network technologies evolve.
We recognize that trust is crucial when it comes to AI adoption in telecom. That’s why we emphasize transparency, explainability, and human oversight in all our AI-driven processes, ensuring that automation enhances, rather than replaces, human expertise.
What is your long-term vision for Kenmei, and how do you see the company shaping the future of telecom network automation?
Our vision is to redefine telecom network management through fully AI-driven automation.
We believe CSPs should no longer have to rely on human-intensive, manual network operations. In the long run, telecom operators are transitioning towards self-optimizing networks, where AI continuously fine-tunes performance without needing constant human intervention. Our role is to provide the intelligence layer that makes this possible.
We are committed to making AI-based automation scalable, cost-effective, and secure. By ensuring that AI Agents work seamlessly across different network environments, we provide operators with a future-proof solution that evolves alongside their infrastructure.
One of our core beliefs is that automation should empower, not replace, network engineers. We design AI Agents to enhance decision-making rather than act as a black-box system. Our approach encompasses augmenting human capabilities and making operations smarter and more efficient.
Looking ahead, we envision a world where AI is not just an add-on feature but the backbone of telecom network operations. Kenmei will continue to be at the forefront of this transformation, pioneering AI-driven solutions that enable CSPs to operate more efficiently, more sustainably, and more intelligently than ever before.
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