The managed services conversation has finally caught up with how businesses actually run. In the mid-market, where IT complexity rivals the enterprise – but resources rarely do – partners are judged less by how many tickets they close and more by whether they can turn operations, risk, and data into a coherent, governed system that leaders can see and steer. Netrio’s latest release of NetrioNow, lands squarely in that shift, positioning “human-led, AI-powered” delivery as a practical operating model rather than an aspirational tagline. The company’s recent acquisition of Agio and its financial services lineage adds weight around compliance and board-level reporting – capabilities the mid-market increasingly requires.
CEO Mark Clayman explained that Netrio remains, at heart, a managed services provider, offering managed infrastructure, OS and server management, backup and disaster recovery, help desk and service desk, public cloud support, connectivity, and UCaaS. What’s different is breadth and scale; it has a national footprint, customers ranging from SMB up to the smaller enterprise (which he defines as having roughly $1–$3B in revenue), and a custom application development practice that migrates stubborn legacy apps off aging platforms. That span introduces enterprise-grade complexity, but, as Clayman notes, it also lets Netrio bring enterprise tools and disciplined service delivery downstream into the mid-market.
Clayman is frank about market segmentation: Many MSPs and customers are slow to embrace AI, which he sees as an inherent advantage for Netrio.
Mark Clayman
“With any new disruptive technology, there's always this large group of laggards that take years, if not a decade, to really consider moving to it,” he told me. “I think that, for a long time, there will be a lot of smaller, regional MSPs working with small companies, and neither side might have the capabilities, the thought leadership, to really start considering AI.”
Netrio is optimizing for a different buyer. According to Clayman, he is looking for companies that see technology as a differentiator and enabler, with AI part of that story. Those customers push Netrio to do new things, ask business-first questions, like “How do we free budget?” or How can we fix a manufacturing plant process?” or “Can we improve the patient experience?” That kind of forward-looking perspective forces the provider to translate technology into operational change. That’s not to say Netrio downplays the importance of other, more traditional clients, but rather that the more technologically inquisitive customers bring a different value mindset that drives Netrio to look for new ways to solve problems and surface new opportunities.
That orientation shows up in how Netrio sells. Rather than pitching AI in the abstract, the team leads with something tangible, such as a demonstration of NetrioNow.
“It’s important for our sales team to demo the platform because it gets companies really interested what we've done internally,” Clayman explained. “They think we're a little bit ahead in terms of the AI thought process, and that allows us to start having conversations with them about the different functional areas within their organizations, how we can show them how to push AI into those areas away from just traditional IT and into how they manage their data, the way they create reporting, the way they automate a finance function or sales process. Those are the conversations we're starting to have with our customer base.”
For Clayman, it’s important that Netrio is able show competency in AI in terms of its platform’s core functionality, because it makes the difference visible: Efficient delivery via automation, fewer manual errors, self-service capabilities, and transparency. If that competency lands, conversations naturally expand beyond IT to functional areas (e.g., finance, operations, manufacturing, sales and marketing), where automation, data, and reporting can change the economics of work. In other words, prove you can run IT differently, then help the business run differently.
Under the hood, the platform’s architecture matters as much as the features. First, an enterprise-grade ITSM core built on ServiceNow anchors tickets, events, problem and change management. Next to it sits a data warehouse that fuses ServiceNow records with external telemetry – for example, inventory and firmware data from a Cisco Meraki estate, plus known bugs or vulnerabilities. The result is that 80% of necessary research is done for technicians before they start troubleshooting. Above that is a customer-facing dashboard that exposes the same enriched context – turning the MSP from a black box into a glass box.
The latest release formalizes those ideas into product. A unified portal consolidates dashboards, support, reporting, and communications. An automation engine accelerates routine work, such as patching, monitoring, and incident response, so issues resolve in minutes, not hours. The NetrioAI suite layers on three capabilities:
An enrichment engine for case categorization, sentiment, and impact analysis;
Communication analysis to improve clarity, tone, and empathy; and
An insights engine that turns noisy operational data into executive-ready intelligence.
A Foundations Framework vertically integrates governance, including change management, risk logging, and auto-heal policies, so fixes are durable. Dedicated risk and compliance modules maintain a live risk registry on a single screen. Knowledge and collaboration tools scale learning, and customizable dashboards give each stakeholder a relevant view without fracturing the source of truth.
Clayman highlights one quietly powerful loop: Ticket-level sentiment.
“Whenever a ticket gets answered, we assign a sentiment grade to that ticket,” he explained.
That tracks tone, hand-offs (Help Desk → Network → L3 and back), and response times. He sees 20-40 of these alerts a day, and explains that the immediate, AI-driven feedback enables self-correcting behavior, where teams course-correct in hours instead of waiting for a month-end review. It’s culture encoded as product.
Internally, once AI is embedded, adoption compounds.
Clayman explains it as something akin to a strong current. “Once you introduce it and people see how it makes their jobs easier, it becomes a natural, undeniable force, and they just continue to look for that current to become faster and more powerful. It frees up their time to do other things, which I think is the most important impact.”
“In a perfect world, if we can push every one of our level one support requests and tickets and incidents, either out to the customer through self service or completely automated through agentic AI, that would, that would be phenomenal,” he adds.
Governance and data protection are the table stakes that make all of this credible. With Agio’s roots in hedge funds, investment banks, and PE-backed portfolios, compliance questions now account for the majority of formal and informal evaluations Netrio fields. Prospects ask where data goes, how it’s protected, and how controls are proven, and these are questions that will only intensify as AI pushes closer to core business functions and end-customer data.
NetrioNow’s audit trails, risk registers, and board-ready reporting speak directly to that reality, giving CIOs and CISOs a common language with CFOs, CROs, and directors.
But, Netrio’s strategy extends beyond direct customers, though, and it plans to offer NetrioNow as a white-label service delivery “solution in a box” for MSPs starting in 2026. It will include ITSM, reporting, and AI enablement, with Netrio continuing to invest in the roadmap so partners don’t have to. That dovetails with two inorganic growth paths: acquiring MSPs with similar customer profiles, and buying capabilities the firm wants to deepen – advanced security, AI consulting, and professional services. The company already has experience white-labeling for VARs who own the customer relationship but lack managed services. Productizing that experience could expand distribution without diluting standards.
“There are a lot of MSPs that could use an upgraded platform with AI built into it,” Clayman says. “We already understand kind of that mode of delivering through a partner to their end customers, and the NetrioNow platform really enables us to truly productize it.”
There’s a market reality beneath the buzz. Some providers and customers will remain comfortable with traditional models and, for them, incremental improvements may suffice. But the mid-market organizations that view technology as leverage are pushing for more in terms of visibility, speed, and outcomes. Netrio’s bet with NetrioNow – human leadership on top of a governed platform, powered by AI – meets that demand head-on. If the platform continues to compress resolution times, elevate staff to higher-value work, and turn operations into executive-ready intelligence, managed services truly becomes a major competitive advantage.
Edited by
Erik Linask
