Convergence - The Sequel (And How To Avoid Trade-Offs)

I recently published a blog, post-conversation with Albert Estevez Polo (current leader in “Broadband-Testing name of the year 2026” competition) from Zero Networks about the importance of minimising the cyber security architecture and addressing the threat “from within”.

However, you still need a secure data and application delivery mechanism, hence a recent conversation with Renuka Nadkarni, Chief Product Officer at Aryaka, talking about the company’s update of its Unified SASE as a Service platform (now 2.0) and, again, the art of using as few security tools as possible, in order to be able to realistically manage that environment. Naturally AI entered the building; Renuka explained how customer feedback had suggested that customers needed help safeguarding their GenAI apps and services, as well as the need to expand secure, high-performance network connectivity to hybrid workforces, wherever they are, something close to both my own heart and test report history, having featured as a “European tele-commuter” (remember that term?) in The Times way back in 1994 – oh yes! I even managed to get a photo in there with my Leeds United shirt on 😊 (MOT). Proudest moment…

The key, when combining networking and security, is to avoid the dreaded “trade-off”, both in terms of performance and security limitations. Renuka made the point that they have avoided this virtual pothole and it would be sweet to see it in action. Naturally, this is a fundamental factor when dealing with AI traffic. According to research from Roy Chua, Founder and Principal at AvidThink, enterprises are rapidly converging networking and security to support AI-driven growth. The study found that 35% of organisations have already converged, while nearly 60% expect to do so within the next 12–18 months, and almost none plan to delay convergence indefinitely. Both AvidThink and Aryaka see scalable AI adoption as a driving force behind converged secure networks, something that has been a logical marriage since the first network firewall was introduced (we actually tested the Shiva LAN Gateway back in the 90s and the first thing I achieved was to lock myself out of my test network – QED 😊).

Another feature Aryaka has introduced is “Next-Gen DLP”, aimed at using AI-powered natural language processing, granular policy tuning, and contextual pattern recognition to protect data in motion between networks, applications, locations, and users. As we noted in my previous blog, and in conversation with Renuka, AIs increasing use as a cyber attack tool makes this a very interesting (and even fair?)  fight. We’ll see who wins… Maybe Paddy Power is offering odds on it?

What is interesting about the thinking behind convergence – think back to Netevents debates back in the late ‘90s and early 2000s – is that it is another classic example of “what goes around comes (back) around”. I was in discussion with a longtime client, Aritari, yesterday, with its CEO Jonathon Nelson, and we talked about its secure VoIP and data optimisation technology now being more relevant than ever, not least with the urgent push in Europe for digital sovereignty, especially in secure messaging, given the barely veiled threats coming from the US right now. I can even see a role for Aritari’s ViBE technology in a SASE environment, but that’s another convergence story for another day.

Meantime, converge, avoid trade-offs, trade embargoes and excessive tariffing and look after your digital crown jewels.