Chris Wade

You can't fix what you can't see—and partial visibility simply isn't enough anymore. 👀 In today's intricate environments, conventional network monitoring tools are insufficient. Our newest article delves into why integrating flow data with performance metrics and service state is not merely a "nice to have," but essential for contemporary NetOps. 🔗 Read the full post:

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Every telecom executive I speak with is facing the same reality. 5G standalone rollouts. Open RAN integration. Cloud-native core migrations. AI-driven automation. Cybersecurity escalation. And yet the one resource required to execute all of this at scale is becoming the hardest to secure. Network engineering talent. The global network engineering services market is projected to grow from $60.7B in 2025 to $133.28B by 2034. Demand is accelerating. Supply is not. So the real question is no longer whether to outsource. It is where to build your next engineering hub. Kosovo sits at the heart of Europe, operating in CET, within real-time collaboration distance of London, Berlin, Zurich, Milan, Vienna and beyond. For U.S. operators, it enables a true follow-the-sun model without night-shift premiums. But geography is only part of the story. Kosovo has the youngest population in Europe, with more than 50 percent under 35 and over 2,600 IT and engineering graduates entering the workforce annually. More than 30 percent of university students pursue STEM fields. Certifications across Cisco, Juniper Networks, Fortinet and other ecosystems are deeply embedded in the market. This is not theoretical talent. It is production-grade telecom experience. Kosovo's telecom ecosystem includes 5G deployment, a €15M radio modernization program across 400 base stations, Ericsson's R&D presence, 96.4 percent internet penetration, and full regulatory alignment with EU standards. Engineers here are not learning in labs. They are operating real carrier networks. Now let's talk about what procurement teams actually care about. Cost. Engineering labor costs are 50 to 70 percent lower than equivalent roles in the U.S. or Western Europe. Corporate tax is a flat 10 percent. Operational overhead is 45 to 50 percent lower than the EU average. For a 10 to 50 person engineering team, annual savings range from $0.6M to over $8M depending on role mix. But cost alone does not win Tier 1 contracts. Execution does. 75,000 plus ports migrated for a nationwide metro core refresh across all 50 U.S. states. Zero customer-impacting outages. Six months ahead of schedule. 900 plus workloads onboarded across 120 branches and three data centers with spine-leaf EVPN and Zero Trust segmentation. This is what happens when you combine young, hungry engineering talent with strict SLA governance, MOP discipline, NMS integration and outcome-based pricing. Kosovo is not a backup option. It is a strategic advantage hiding in plain sight. If you are a telecom operator rethinking how to scale your engineering capacity in 2026 and beyond, this whitepaper lays out the full economic model, risk framework and implementation roadmap. Built for decision-makers who care about resilience, margin and speed. Download the full playbook in the comments and see why Kosovo is becoming Europe's most cost-effective network engineering hub. Your network. Your SLAs. Your outcomes.

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At Somos, Inc., we’re fortunate to work with visionary advisors like Craig Lennon — a pioneer whose work has shaped how the world connects. From his early days in the labs of Lucent Technologies to leading voice and messaging infrastructure at Google, Craig brings rare insight into what it means to build trust and scale in modern communications. In our latest feature, Craig shares his invaluable perspective on: - Building scalable communications through ecosystem-wide partnerships - The transition beyond SMS with Rich Communication Services (RCS) - The future of Agentic AI in shaping next-gen networks Craig reminds us that innovation isn’t about going it alone — it’s about rethinking how we partner, design, and lead together. You hear a lot about big ideas on this platform -- Craig has those big ideas and actually brings them to life. 📖 Read the full story:  https://bit.ly/3HQ9c8B #Leadership #Connectivity #AIinTelecom #SomosAdvisoryBoard #TrustInTech

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https://lnkd.in/gZhhuhRk Cloud comms ARPU is expected to drop 20% — and that’s just the beginning. If you’re managing multiple UC platforms and paying per seat, you’re not optimizing — you’re losing margin and scale. Consolidation isn’t optional anymore. It’s how providers stay profitable. 👉 Learn more: https://bit.ly/45NbW0J #UCaaS #MSP #PoweredByNetSapiens

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I’ve been experimenting with ways to bring AI into the everyday work of telco — not as an abstract idea, but as something our teams and customers can use. On a recent build, I created a live chat agent I put together in about 30 minutes using n8n, the open-source workflow automation tool. No code, no complex dev cycle — just practical integration. The result is an agent that handles real-time queries, pulls live data, and remembers context across conversations. We’ve already embedded it into our support ecosystem, and it’s cut tickets by almost 30% in early trials. Here’s how I approached it: Step 1: Environment I used n8n Cloud for simplicity (self-hosting via Docker or npm is also an option). Make sure you have API keys handy for a chat model — OpenAI’s GPT-4o-mini, Google Gemini, or even Grok if you want xAI flair. Step 2: Workflow In n8n, I created a new workflow. Think of it as a flowchart — each “node” is a building block. Step 3: Chat Trigger Added the Chat Trigger node to listen for incoming messages. At first, I kept it local for testing, but you can later expose it via webhook to deploy publicly. Step 4: AI Agent Connected the trigger to an AI Agent node. Here you can customise prompts — for example: “You are a helpful support agent for ViewQwest, specialising in broadband queries – always reply professionally and empathetically.” Step 5: Model Integration Attached a Chat Model node, plugged in API credentials, and tuned settings like temperature and max tokens. This is where the “human-like” responses start to come alive. Step 6: Memory Added a Window Buffer Memory node to keep track of context across 5–10 messages. Enough to remember a customer’s earlier question about plan upgrades, without driving up costs. Step 7: Tools Integrated extras like SerpAPI for live web searches, a calculator for bill estimates, and even CRM access (e.g., Postgres). The AI Agent decides when to use them depending on the query. Step 8: Deploy Tested with the built-in chat window (“What’s the best fiber plan for gaming?”). Debugged in the logs, then activated and shared the public URL. From there, embedding in a website, Slack, or WhatsApp is just another node away. The result is a responsive, contextual AI chat agent that scales effortlessly — and it didn’t take a dev team to get there. Tools like n8n are lowering the barrier to AI adoption, making it accessible for anyone willing to experiment. If you’re building in this space—what’s your go-to AI tool right now?

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I genuinely applaud T-Mobile and Verizon on there Private 5G solutions. I truly believe all solutions in the Private 5G space build value and momentum for the ENTIRE Private 5G space. BUT..... The disconnect that I see from the US MNO's is that not all Enterprises want an MNO led/deployed Private 5G solution. So where does that leave the majority of Enterprises that want to deploy there own Private 5G solution, utilize it to the fullest extent possible, and keep native number calling and messaging? It leaves them frustrated!!! The only truly scalable solution that fits an existing MNO approved solution is #PRV8Calling NETWORKFX For the latest from James Blackman https://lnkd.in/d7iAmgNh For the latest from Michael Robuck https://lnkd.in/dXeHs_wZ

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