The Buzz: Cisco opens AI model opportunity, N-able accelerates patching, Dell expands cyber resilience

Robert Dutt: Hello, and welcome to The Buzz from ChannelBuzz.ca. I’m Robert Dutt. Today is Wednesday, October 28, 2026, and here’s what’s happening in the channel today.

We’re coming to you from Vancouver, where Cisco Partner Summit 2026 is underway.

Yesterday, we took a broad look at Cisco’s efforts to help partners build more profitable businesses around artificial intelligence.

Today, we’re going to start with something a little more specific. And potentially, a pretty interesting new business opportunity for partners.

We’re also looking at new developments from N-able and Dell Technologies, both focused on helping organizations manage increasingly complex cybersecurity challenges.

Let’s get into it.

First, Cisco Model Foundry.

During yesterday’s Partner Summit keynote, Cisco president and chief product officer Jeetu Patel introduced a new service intended to give partners access to some of the company’s specialized artificial intelligence models.

And perhaps more importantly, to let them customize those models for individual customers.

It’s called Model Foundry, and it’s part of Cisco Cloud Control.

Now, Cisco has been developing AI models specifically for networking, security and infrastructure operations for some time.

These aren’t general-purpose models designed to answer questions about everything from programming to pizza recipes.

They’re models trained to understand particular technical domains.

For example, Cisco’s Deep Network Model is designed to understand network configurations, telemetry and troubleshooting.

Another model, called Antares, focuses on identifying potential software vulnerabilities.

And there’s a decision model designed to help AI agents determine which tools they should use, whether they have enough information to make a decision, and when they should escalate a problem to a human.

What’s changing with Model Foundry is that Cisco wants partners to be able to use those models directly in applications and services they develop for customers.

And they can go a step further.

Partners can fine-tune those models using information specific to a customer’s environment.

Think about a managed service provider that has years of information about a customer’s network, including configurations, support tickets, troubleshooting history and operational data.

Instead of relying entirely on a general-purpose AI model, that provider could potentially build an assistant that combines Cisco’s networking expertise with detailed knowledge of that particular customer.

That could create opportunities for more sophisticated troubleshooting, operational automation and ongoing managed services.

And Cisco is trying to reduce the technical barriers involved.

Model Foundry provides access to the models through APIs, along with tools for testing, customization and evaluation.

Partners don’t necessarily have to build or operate the underlying AI infrastructure themselves.

Cisco also presented some early results from work with World Wide Technology.

In a laboratory evaluation involving twelve network troubleshooting scenarios, a Cisco model fine-tuned using WWT data recommended the correct fix in eleven cases.

The frontier model used for comparison got eight correct.

Now, twelve scenarios is a pretty small test, and I wouldn’t read too much into that result on its own.

But it does illustrate the argument Cisco is making.

A model that understands both a technical domain and a customer’s particular environment may be able to deliver better results than a more general-purpose system.

And the more interesting part, from a channel perspective, is who gets to build that customer-specific intelligence.

Patel was quite explicit about wanting partners to develop practices around Model Foundry.

Cisco provides the underlying models and platform. Partners bring their customer relationships, technical expertise and knowledge of individual environments.

And potentially, they turn that combination into a new services business.

Of course, there are still some important questions.

How much will it cost to develop and operate these solutions? How much specialized expertise will partners need? And how much of the work can be repeated across customers?

Those questions are going to determine whether this becomes a broadly accessible opportunity for MSPs and solution providers, or something primarily pursued by larger organizations with substantial development resources.

There’s also a timing consideration.

Model Foundry entered controlled availability with partners first at Partner Summit, and Cisco is targeting general availability in June of next year.

So we’re still looking at an emerging opportunity rather than a mature services market.

But I think it’s one of the more interesting announcements from this year’s Partner Summit, because it points toward partners doing more than simply deploying AI technology.

They could increasingly be developing and operating specialized AI solutions that become part of how their customers run their businesses.

And that’s a potentially significant change in the role of the channel. In a briefing with press and anlysts here, Patel oulines how the company see the technology as a way to lower the barriers to sophisticated AI services, while acknowledging that partners will still need to develop the strategic and change-management skills to deliver them. I’m sure we’ll see much more before general availability next year.

Our second story comes from N-able, which is looking to accelerate one of the more frustrating parts of cybersecurity operations.

Finding vulnerabilities is important, but finding them doesn’t actually make an organization more secure until somebody does something about them.

And for managed service providers, that process can involve a lot of moving parts.

You identify a vulnerability, determine which customer systems are affected, prioritize the risk, deploy a patch, and then verify that the problem has actually been resolved.

Often, those steps involve different tools, manual handoffs and considerable administrative work.

N-able has announced new AI-accelerated Vulnerability and Patch Management capabilities intended to bring those activities together.

The enhancements are part of its Unified Endpoint Management platform.

The company says the system can help prioritize vulnerabilities based on exploitability, apply appropriate patches and then rescan systems to verify that remediation was successful.

Its N-zo AI assistant can also provide information about failed patches and help administrators determine whether it’s appropriate to try deploying them again.

N-able is positioning the technology as a way to reduce patching windows from days to minutes.

That’s a pretty ambitious claim, and actual results will obviously depend on the systems and vulnerabilities involved.

But the broader idea is interesting.

For an MSP managing hundreds or thousands of endpoints across multiple customers, reducing the number of manual steps involved in remediation could make a meaningful difference.

And it could also help providers demonstrate the value of their security services.

There’s a big difference between telling a customer that you’ve identified fifty vulnerabilities and being able to show which ones were addressed, how quickly they were resolved and whether the fixes were verified.

That’s where vulnerability management starts to become a more complete service rather than simply another collection of alerts.

And as attackers become faster at identifying and exploiting weaknesses, reducing the time between discovery and remediation is becoming increasingly important.

Our third story comes from Dell Technologies, which is expanding its cybersecurity and resilience portfolio.

The company announced new capabilities yesterday focused on protecting artificial intelligence environments, strengthening identity recovery and improving infrastructure resilience.

And there’s an interesting connection to the broader AI conversation.

Organizations are deploying increasingly sophisticated AI systems, but those systems depend on a lot of infrastructure that also needs to be protected.

There’s the data the AI applications use, the storage and computing systems supporting them, and the identity platforms controlling access to everything.

Dell is introducing new AI-focused services and PowerProtect capabilities intended to help organizations protect those environments and recover more quickly when incidents occur.

It’s also putting additional emphasis on identity resilience.

And that’s an important distinction.

When we talk about recovering from a cyberattack, the conversation often focuses on restoring data and applications.

But if an organization’s identity systems have been compromised, simply restoring its data may not be enough to get the business operating securely again.

Those identity systems control who can access applications, infrastructure and sensitive information.

So protecting and recovering them needs to be part of the broader resilience strategy.

Dell is also expanding integration between PowerProtect and PowerScale and introducing additional capabilities intended to address emerging quantum-related security risks.

For solution providers, this is another example of cybersecurity and business continuity becoming increasingly interconnected.

Customers need help understanding not just how to prevent an attack, but how to maintain operations and recover when something goes wrong.

And as AI becomes more deeply embedded in business processes, those conversations are only going to become more complicated.

That creates opportunities for partners delivering security assessments, resilience planning, implementation and ongoing management.

But it also creates a challenge.

Partners need to bring those capabilities together into services that customers can understand, afford and measure.

And that brings us back to a common theme across today’s announcements.

Cisco is trying to make sophisticated AI development more accessible to partners.

N-able is trying to simplify the operational work involved in vulnerability remediation.

And Dell is expanding the tools available to protect and recover increasingly complex enterprise environments.

Different technologies, but all addressing the growing need for expertise and services around systems that are becoming harder for customers to manage on their own.

If you haven’t heard it yet, yesterday’s episode of In The Channel features my conversation with Alex Pujols from Cisco’s global partner sales organization, recorded here at Partner Summit in Vancouver.

We discuss how artificial intelligence is changing the kinds of businesses Cisco partners can build, including opportunities in security services, AI-powered infrastructure and partner-developed applications.

Alex also walks us through Cisco’s Vulnerability Operations Maturity Model, and we talk about how the company is trying to make more sophisticated capabilities accessible to a broader range of partners.

It’s an interesting conversation about the opportunities AI is creating, but also the work partners will need to do to turn those opportunities into viable businesses.

You can find that episode, along with links to today’s announcements and more coverage from Cisco Partner Summit, at ChannelBuzz.ca, or wherever you listen to podcasts. We’ll have more episodes of In The Channel from here in Vancouver over the coming days, including Cisco Canada leaders Raj Juneja and Erin Gertner, distribution and sales leader (and Canadian) Andrew Sage, and the partner point of view as well. So be sure to check those out.

And that’s how we’re seeing the headlines today.

I’m Robert Dutt for ChannelBuzz.ca. Thanks for listening, and have a great day.