(So you can skip ahead, if you want.)

00:00 Intro – Why You Still Can’t Trust AI
01:10 Rodney Foreman Joins BASELINE
03:22 The Rise of Agentic AI
06:45 What Is MCP? (Explained Simply)
10:08 From Answers to Actions
13:32 Why Trust Is the Real Bottleneck
16:49 Autonomous Networks – Already Real?
20:40 Selector & Lumen Use Case
25:06 Guardrails vs Speed in AIOps
30:21 Natural Language to Execution
33:48 Will Humans Stay in the Loop?
37:35 Compliance, Policy, & Drift
42:02 Final Thought: Earning Trust, Not Replacing People

Rodney Foreman • 00:00

Not everybody’s comfortable yet with saying, I’m going to turn over my network of which my company and enterprise relies on for business to a AI-driven system. They’re not there yet. So that’s why we put in these human touch points. There’s this vision with customers of having a fully autonomous network at some point where you don’t need a lot of people, you don’t introduce human errors, you stay compliant, network stays secure, but it’s all autonomous driven primarily through AI. And using English language now, because of MCP and Agenic AI and the training, I can use the English language as administrator and just type in things like, what changed in the environment in the last 12 hours? Boom, it gives me that. And I don’t need to be a programmer or real experienced network administrator to type English language, ask the system questions, and have it produce real-time information.

Ian Smith • 01:46

The baseline is designed to create an emotional response. I’ve seen things you know for me. MCP is a new AI term that everybody is talking about and has become the latest buzzword for people to discuss on social media. Indeed, Anthropic today have announced they’re creating MCP registries for different Context protocol servers, and they’re going to start indexing them across the industry. But specifically at Itential, we’re going to talk about how they’re leveraging Agentic and MCP within the infrastructure layer for the network. Rodden is the chief revenue officer at Itential.

Ian Smith • 02:48

He’s a long-term friend and trusted colleague of mine. Itential are the company behind MCP server for network orchestration and management. Rodden is on a mission to create operationally effective AI, but with a serious focus on keeping it safe and within guardrails. He’s a veteran of enterprise software. IBM, Oracle are always operating at scale, doing work that carries significant financial risk if it gets wrong. So Rodden is used to being at the front line deploying technologies in a very safe and trusted way.

Rodney Foreman • 03:26

There’s definitely a customer need to evolve. What we’re doing around automation and orchestration in large enterprise environments. And it’s not just about the network, it’s about all the devices and software that these IT professionals are having to maintain on a daily basis. And we are the platform that will help them to stay in compliance, to keep things from configuration drift, as we call it now. And also be more proactive. There’s this vision with customers of having a fully autonomous network at some point where you don’t need a lot of people, you don’t introduce human errors, you stay compliant, network stays secure, but it’s all autonomous, driven primarily through AI and an orchestration engine that combines those automations that are done in silos across the environment, combine those together into an orchestrated workflow that goes all the way across the entire IT environment with some level of intelligence and insight into all aspects of the environment that they’re managing. The number one reason IT environments break is somebody changed something.

Rodney Foreman • 05:03

That’s the number one reason it breaks. And using English language now, because of MCP and Agenic AI and the training, I can use the English language as administrator and just type in things like, what changed in the environment in the last 12 hours? Boom. gives me that. And I don’t need to be a programmer or real experienced network administrator to type English language, ask the system questions, and have it produce real-time information.

Ian Smith • 05:41

I’m fascinated to understand how you’re approaching your whole approach to that, because you are a trusted provider, but you’re also trying to build with high velocity the new products. Can you feel that tension in the market right now?

Rodney Foreman • 05:57

Yeah, absolutely. Well, one great thing about Itential is from the start, We took the approach from an automation orchestration perspective in that you, in order to use our platform, you don’t have to recreate anything. We ingest anything you’ve created from an automation perspective. Any automation in silo or workflow you’ve created in Terraform or Ansible or whatever your favorite programming tool is, we ingest and then integrate across the environment into ServiceNow or Remedy or your favorite router or whatever it may be that you’re automating against, be it a device or software solution. So you don’t have to recreate anything. So we’ve got a head start there in the market in that you don’t have to recreate anything, as you just said.

Rodney Foreman • 06:57

Now you add MCP onto that, where you now take those automations and orchestration into a training model, LLM, and have it learn the environment, learn what you’re doing from an automation and orchestration perspective, plug agenic AI into that. Now you can use natural English language to create more workflows to tune and optimize the workflows and automations you already have. And do things like optimize the network because it’s intelligent and knows what the environment and state of the environment is at any time, especially using our lifecycle manager product. We understand the state and configuration of everything. We can then optimize it. So, if you’re using, if you’re trying to implement generative AI, where latency is key, network latency and being optimized, the network being optimized for performance, you can now do that on the fly using our product and the orchestration engine. And you remove a human from monitoring latency and then manually changing configurations to optimize the network.

Rodney Foreman • 08:21

Now it does it, can do it automatically.

Ian Smith • 08:24

Rodney, you’re talking about a leap of trust an organization needs to make from a highly organized, trusted team of humans who lead the configuration, the maintenance, the ongoing management and observation of a network. I’m going to be the network’s never been exciting to me. It’s just been, it’s had to exist in a very stable, performant way. Correct. You know, and you’re asking organizations to move from that deterministic as much as humans can be to a system built on AI that, you know, you hear people talking about hallucinations potential. How do you mitigate the risk of uncertainty if you’re going to move to an AI-led question?

Rodney Foreman • 09:19

Yeah. And so what we do is we have the ability through our platform to insert human touch points. So until you become fully trusting of a fully autonomous network operating on its own, we put in human touch points into those workflows. And also we have a way with our platform, you can simulate what you’re running before you actually run it in production to see what the outcome is going to be. But we insert human touch points because you’re right, not everybody’s comfortable yet with saying, I’m going to turn over my network of which my. Company and enterprise relies on for business to a AI-driven system. They’re not there yet.

Rodney Foreman • 10:08

So that’s why we put in these human touch points into the workflows. And we don’t necessarily holistically change how the bank is running their network or the automations that they’re running. We refine them and progress them to the next level with our platform and make them much more efficient and reliable. So it’s again, you’re not rewriting everything or wholesale replacing anything. You’re now utilizing a platform that makes it much more efficient and reliable. Then you introduce AI into the mix, and then you’re still using those same tools and monitoring and visibility systems, but they’re being used much, much more efficiently than a human can use them. And then with the ability to use either low code or high code in the network management environment, you then introduce more ways to optimize the environment, make sure it’s compliant, because banks are very, very focused, of course, on security and compliance.

Rodney Foreman • 11:29

And there’s no way you can maintain a large bank environment like HSBC without having automated tools checking things on a regular basis and taking some action. You just can’t do it. There’s no way. You wouldn’t be able to hire enough humans to do that. And introducing AI into the mix, it just makes it a hundred times more efficient.

Ian Smith • 11:57

So, I mean, fundamentally, people will know. Conversational AI as a platform that gives them answers, it gives them information, it kind of synthesizes data and gives them an answer.

Rodney Foreman • 12:12

Sure.

Ian Smith • 12:14

And the 700 million users, whoever it is who are using ChatGPT and others every week, will know that AI is this tool that gives them answers. What it doesn’t do present is execute actions. That’s right. And I think that, as I understand what you’re saying, and just to simplify the movement from generating an answer to initiating an action. Bingo. That’s right. You may have a human in the loop that validates the action before it’s done, which sounds safe and good.

Ian Smith • 12:45

But is that the leap that’s happening right now in a data center?

Rodney Foreman • 12:49

So you have companies like Selector AI, who we’ve partnered with, very, very good at analyzing lots of data and forming an understanding and context of that data and then formulating some response, but it cannot act on it, as you just said. That’s where we come in. We do the action, the automation and workflows that need to happen in order to do something with that data and analytics of that data in the environment.

Ian Smith • 13:33

Yeah. So the relationship with Selector, so is that a, are you embedding their AI technology in your stack, the MCP server that you offer to customers?

Rodney Foreman • 13:46

No, it’s very basic. It’s, you know, when they go to a customer like Lumen, you know, we work together at Lumen. They went to Lumen and said, look, you’re gathering. terabytes and terabytes of network data, you know, from your fiber you supply, the network services you provide your customer, et cetera. We can help you to deliver a better service by analyzing all that data and identifying trends, helping you to be more proactive and delivering a better service. And they bought into that and they are implementing Selector. However, as you pointed out, then what do you do with that?

Rodney Foreman • 14:30

And it’s not efficient to have a human do something with that. We integrate into Selector so that now we take action on whatever Selector has found in the environment, the trends and the optimization that that Selector provides through that data analytics.

Ian Smith • 14:51

I mean, I was trying to Luke, who I was chatting to before I came up. Who’s a great guy? He’s got deep experience. Yes. And we were talking about this evolution of the traditional network operations or infrastructure operations from buying big Cisco enterprise-grade directors to transition applications to the cloud to enterprises with a very complex estate where they may have. I use the term legacy, not in a negative way, but technology that’s been around for a while, proven stable, but has some history. Net new cloud-native applications that are, you know, enterprise estates can get very complicated.

Ian Smith • 15:41

Like, how on earth is that unpicked? Is that where this idea of understanding performance logs, security logs, change logs all go into this AI and it can then say across a complex estate, the last change was that firewall change, which impacted performance on this? Correct. Exactly.

Rodney Foreman • 16:02

That’s right. Yeah. And it’s like I said, MCP allows our platform to then be context-aware and understand the environment that you’re operating within, all aspects of it. And with Lifecycle Manager, the state and configuration of everything across the network. Then you have the ability using that information and those tools to make sure you never go out of compliance. If you do have a configuration change, someone is notified, or in an automated fashion, it can correct the change and say you’re about to break the whole network with this change and proactively prevent that.

Ian Smith • 16:51

I mean, I. I mean, AI ops is this kind of thing, it’s a new term, as far as I’m concerned, that’s appeared probably over the last 12 months. Yeah. Where there’s this idea of leveraging generative AI to understand logs and start to make operational guidance. The number one problem that I’ve spoken to people who are running complex states is simply root cause analysis. Yes. So, like, actually, when something goes wrong, how quickly and effectively we can, because that feels in it, how quickly and effectively can we recover from that?

Ian Smith • 17:28

Yes. So, RCA has become this big hot topic within these deep tech conversations.

Rodney Foreman • 17:34

Yeah, well, the big one for us is everybody has a disaster recovery plan, right? Do you have an automated system that will, when you push a button, it will automatically recover utilizing that plan? Well, no. We have humans, I guess, that’ll start doing things to execute the plan. Well, no, don’t do that. Use our platform to have that plan implemented through automation and orchestration, such that if you have to execute that plan, it’s done in an automated fashion and you are online within minutes versus hours or days trying to do things manually, right? So,

Rodney Foreman • 18:28

Yeah, the same thing applies to root cause analysis. If you’ve got a system that’s intelligent about the state of the environment and it has context, it makes it much, much easier to figure out where things went wrong and then through automation, put it back where it needs to be so it’s running again.

Ian Smith • 18:53

And have you proven that? Yes.

Rodney Foreman • 18:55

Oh, absolutely. Yeah, absolutely. Yeah. Our customers that we’ve had for years, now that we have MCP and Lifecycle Manager, we show them a simple demo and even using their own environment because they already have our platform, they’re blown away by what it can do.

Ian Smith • 19:19

Do you know, it’s 2025. I’m surprised we’re still having these conversations. And you and I were having these conversations in 2010 around hardcore infrastructure optimization, performance optimization, security, tuning.

Rodney Foreman • 19:39

Well, I led product management for a while at Tivoli, right? And we had this thing around, we called it VCA, visibility, control, and automation. And yeah, it’s the same conversation.

Ian Smith • 19:53

I thought this had been fixed with the panacea of public cloud.

Rodney Foreman • 19:57

No. No. A cloud makes things a lot better. I mean, we have our own cloud-based. Solution. And that’s what most of our customers are moving towards. And yes, it’s much, much more efficient, much more stable and reliable.

Rodney Foreman • 20:16

But you still have people that break things in the physical network. And, you know, the cloud doesn’t fix that problem.

Ian Smith • 20:24

Oh, like putting my friend put a spade through his broadband cable. Do you mean like physical damage to a network?

Rodney Foreman • 20:32

Well, that’s one thing that can happen. Yeah, I mean, we had a QBR with Lumen last week at our headquarters. And one of the things that they’ve automated and put AI around is breaks in the fiber. They have rodents and squirrels that chew through fiber and break their network, or a utility company or cable company that doesn’t work for Lumen. They backhoe through the cable. And so they’ve now automated and used our platform to quickly isolate within a few hundred feet where the cable break is, dispatch a truck, analyze when the thing is back online. I mean, a process that would take them, in some cases, days to fix a fiber cut, they now do it in hours or less.

Ian Smith • 21:24

And that’s using AI to be looking at data within a customer language model, seeing changes within threshold, and then somehow applying an action.

Rodney Foreman • 21:36

Correct. That’s right.

Ian Smith • 21:38

Yeah. Fascinating. Yeah. Do you think it’s generative AI that’s unlocked this? Is this the language element that’s unlocking this level of trust in automation?

Rodney Foreman • 21:49

I think that’s part of it. Yeah.

Ian Smith • 21:51

Because we’re in a hype cycle around AI. Everybody thinks AI is going to give them an advantage, and it seems to be when applied pragmatically. Yeah, it is. You know, I keep coming back to this point in transitioning to trusting this type of technology.

Rodney Foreman • 22:06

Yeah, I think that will come. It will come. I mean, if I would have asked you, Ian, 10 years ago, hey, Ian, I’m going to put you in a car. It’s going to drive itself. I’m just going to take you somewhere. You’d be like, oh, hell no, I’m not doing that.

Ian Smith • 22:21

One element. That has come up around this automation. Let’s take the car driving example. Is that presently the application of self-driving cars still requires a human, I believe, to be in the vehicle to take over if there’s an issue? Or have we moved past that? We’ve moved past that.

Rodney Foreman • 22:40

Oh, we’ve moved past that. Yeah, there’s no humans in these cars anymore. The only accidents they have is a human plows into the backo. That’s the only accidents they have with these autonomous vehicles now. They are more efficient driving than a human is. Their reaction time is faster. Their vision is better.

Rodney Foreman • 23:03

Their sensory of the environment, everything is much, much better than you are.

Ian Smith • 23:08

Do you think we’ll move to a point where no one drives anymore?

Rodney Foreman • 23:11

Yeah.

Ian Smith • 23:12

Yeah, I do. And it’ll be safer.

Rodney Foreman • 23:14

Much safer.

Ian Smith • 23:15

Maybe there’ll be certain road areas that when you enter them, it’s actually completely autonomous. It feels like, so in a zone, for example. So if you looked at a difficult junction or an area where there’s children playing or animals, where there’s vulnerable or like it would make sense for me when you’re a kilometer down the road or a mile down the road, some light comes on, the vehicle says it’s in control, and it connects into a network of vehicles that are operating as an organism. The leap is moving from using that data to retrospectively analyze something to using that data in real time to proactively avoid something.

Rodney Foreman • 23:56

Correct.

Ian Smith • 23:57

Now, that is this huge psychological leap, which I think many people, and if we kind of move back towards the cars or the network, people would see that potentially as an impact on their own.

Rodney Foreman • 24:15

I think where the fear is is the fact that when you’re doing root cause analysis or you’re trying to proactively prevent failures, you’re typically not looking at one metric alone. You’re looking at a combination of metrics that form a pattern that then should result in an action. I think where humans have trouble wrapping their head around this is how can they possibly Take what is in my brain that I use that’s around failure analysis that I’ve learned over years and put that in some sort of AI system. Well, now with MCP and LLMs and learning contexts. You can do that. I mean, these systems can actually do that.

Rodney Foreman • 25:09

And that’s where I think the confidence will come is when these systems start actually optimizing configurations and it works. They actually prevent a failure and it works. They actually do root cause analysis and get back online faster than they’ve ever been able to and it works. They have a disaster or a ransomware attack and they have the high-tension platform in place ready to automate the recovery of that and it works. Once you have those proof points, people will start embracing.

Ian Smith • 25:46

Well, the threat landscape feels like it’s greater than it’s ever been. Oh, it is. And some recent high-profile hacking around some of the big retail organizations in the UK. I think one of the CTOs has just been fired, or CIO has been fired. You know, you’re talking high-profile, you know, hundreds of millions of dollars in terms of public valuation dropped off. I mean, massive significance. So, you know, 15 years on, I would say the sophistication of the threats, whether it be a digger going through a cable or an orchestrated ransomware attack, it feels right.

Ian Smith • 26:29

They’re greater than they’ve ever been. They are. And certainly sophisticated. These aren’t unsophisticated teams rambling around. It’s with cryptocurrency as well. There’s high bounties on this work. So you’re fighting a very organized, financially motivated.

Rodney Foreman • 26:51

No, in their perspective, I mean, I think a couple of years ago. There was a ransomware attack on two major casinos in Las Vegas. I think it was Caesars and MGM, both at the same time from the same bad people, got ransomware attacks. One of the casinos decided to pay the ransomware. They were back online in a couple of hours. The other decided not to pay. It took them weeks and weeks and cost them millions and millions of dollars to get back online.

Rodney Foreman • 27:29

So, yeah, they’re very, very sophisticated, and it’s not easy to recover from these things. So, yeah, it’s protecting the perimeter, but you also have to protect the inside. And then you also have to have a platform that if they do get through and they bring you down, you got to have an automated, orchestrated system to bring you back up quickly.

Ian Smith • 27:55

So, what’s the you know, you announced this a few months ago, it’s phenomenally exciting. Yes. I assume there’s a roadmap, and this is a phased approach. I would love the idea of defining a zone of my network, whether it be test dev or something that you know to deploy this into and actually watch it work.

Rodney Foreman • 28:15

Yeah, no, we have customers already doing that. Like I mentioned, Lumen. They’re implementing Selector with our platform, and they’re very, very pleased with the results they’re seeing already. You know, our head of product management and one of the key visionaries in our company, a guy named Peter Spragata, who actually started Ansible and designed Ansible. You know, he’s been around network. Automation and network operations and stuff for a long, long time. And he is truly excited about this evolution.

Rodney Foreman • 28:58

I mean, he says this is the true next step in our industry is around AI and MCP, agenic AI, and then having a platform like Itential where you can actually do something with that information. I mean, he’s truly excited about it.

Ian Smith • 29:21

It’s a once-in-a-lifetime opportunity. We’re here talking about it.

Rodney Foreman • 29:25

It’s a major transformation. I mean, managing networks, as you said, you talk about the same old things that have been talked about for 20 years, right? This changes the conversation, completely changes the landscape. And we are way ahead of the game because we’ve taken a different approach in terms of what we can ingest and what we can easily integrate with, you know, out of the box. We’re way ahead of this. This is a moment for iTunes where we get so far ahead of the competition, they can’t catch up. It’s about the proof points.

Rodney Foreman • 30:07

And we have the proof points and success in customers already across a lot of different industry verticals. So, our product, it works today. This is a next-generation improvement of what already works and is proven in the industry. And then, our culture is as a company around innovation and collaboration. We exchange ideas and thoughts around how to get to that next level daily. And it’s an exciting place to work because everyone’s ideas is considered and heard, and everybody makes a difference. We’re at the right size, a little over 200 people, where there’s no bureaucracy and we’re not inundated with a ton of process.

Rodney Foreman • 31:07

We’re very nimble and quick in what we can do. And there’s advantages to that. I mean, you’ve experienced that firsthand yourself.

Ian Smith • 31:16

How do you take these operational teams with you? Because I’ve seen it a number of times. When you go into a large, complex enterprise, you hit the culture shift. Well, you hit what I call the immune system, which is. It’s working. Let’s not do anything that might break it. Yeah.

Ian Smith • 31:36

So, especially network storage compute, the traditional foundations of the IT department, what are you doing to de-risk that and make sure these teams and operators realize that this isn’t coming to take their jobs? Yeah.

Rodney Foreman • 31:54

Well, it’s, you know, like my grandma used to say, how do you eat a thousand pound marshmallow one bite at a time? So you have to take it in chunks, right? And take the team along with you with those phases you decide you’re going to implement and embrace automation and orchestration. But it is a culture shift and we experience it in every customer that we work with. It requires a different mindset and change within the organization to fully embrace this automation and orchestration concept.

Ian Smith • 32:32

Is there a future risk where the network itself becomes sentient? You know, I’ve heard stories where, and I’m trying to work out whether it’s marketing or just. You know, a theatrical prompting of AI, where people say, you know, this version of ChatGPT tried to prevent itself from being deleted. It had some form of need to exist beyond, you know, so there’s these stories out there in the industry about proclaiming sentience of versions of language models. And because of the language it’s been trained on, that actually might make sense. It isn’t actually thinking, it’s not human-like in its attempt to preserve its own life. But you know, one of the fears around companies right now is they don’t fully understand LLM-based generative AI and pre-trend transformers.

Ian Smith • 33:27

And there’s this idea that there’s a risk they will become sentient and start making their own decisions, which is science fiction, right? But science fiction, in some ways, is a north star of how this technology plays out. The idea that a network is going to become sentient and be able to orchestrate and automate its own actions independently of human governance is a challenging idea to many people. You’re obviously going on this pragmatic step-by-step process, but the ultimate vision is a sentient network.

Rodney Foreman • 34:05

Yeah, fully autonomous, runs itself. But there are use cases we have with our customers today where they manage parts of the environment. Fully autonomous. No humans using our platform. So in discrete areas of the environment, it’s already happening. Now, how long will it take before we get to this point where the network is fully autonomous and it runs itself basically? I don’t know, but it’s possible.

Rodney Foreman • 34:44

It is definitely possible with this technology. When you’ve got an ability to train and get smart about the environment and it understands the environment, it understands the relationships of one device to another and the software and the state and configurations of those devices and software elements, what their optimum configuration and state is, the ability to have visibility on the performance and latency of the network and optimize it on the fly based on routes and different routers and things like that. That vision of a fully autonomous network with our platform, I think with this technology behind it, can become a reality. Some of our customers today, without this, large service providers, Are saving millions and millions of dollars. We have a customer that is saving over 700,000 man hours a year with our platform. They measure it and they track the cost of it.

Rodney Foreman • 36:05

That’s crazy. Yeah. Yeah, that’s not our data. That’s their data on how much they’re saving.

Ian Smith • 36:13

If MCP is like this air traffic control for your AI agents and your data, I kind of try to manifest this visualization of an autonomous network and the layers of orchestration. There’s still going to be human gateways to some of these decisions. Well, there’s still a. You’ve still got change management.

Rodney Foreman • 36:33

You’ve got an evolution in each industry that’s happening that humans have to drive those ideas and forward-thinking thoughts to evolve their business. I mean, just walking here in London to this location, we walk past one of these AWS grocery stores. There is no human in that store. None. It self-stocks the shelves. You walk through sensors and it sees what you bought. It automatically takes money out of your account.

Rodney Foreman • 37:20

There are no humans there. Not every grocery store is at that level yet. So it takes humans to evolve the store and make it. Get to that level, right? Airports, for example. I mean, we’re working with a company called CETA, you know, S-I-T-A. They manage 400 of the largest airports in the world.

Rodney Foreman • 37:45

One of the airports in Sweden, Sweden, they’re working with is a fully autonomous airport in that you don’t walk through security. As soon as you walk into the airport, biometrics knows who you are. It scans your bag and what you’re carrying. It knows if you’ve got a weapon or not. It knows that you have a ticket on flight number 25. You walk straight to the gate and onto the airplane. You don’t show a ticket.

Rodney Foreman • 38:13

You don’t go through security. It’s fully, no humans, autonomous. It’s all sensors, cameras, and biometrics.

Ian Smith • 38:22

It feels like a signal of the way the market’s going. Oh, it is. And, you know, the. The exponential leap in productivity. You just can’t ignore it. Just this week, as I was saying, Martin Bishop, who’s such an amazing guy, like leading public sector for AWS, or chief technologist, he was saying there are two-person companies using these types of technologies, winning seven-figure government contracts away from the traditional government prime companies, tens of thousands of employees, roll-up. But it’s because the AI-integrated products are just 90% more cost-efficient.

Ian Smith • 39:07

It’s impossible to ignore now. It’s impossible to ignore. How are you taking your existing customer base on this journey? Because I suppose there’s a whole set of people with highly complex, diverse network topologies who have trusted itentials. I’m going to say traditional product set to give them visibility and management. There’s a level of self-disruption happening here because this is such an exponential leap.

Rodney Foreman • 39:36

It’s one use case at a time. So you tackle a use case, the customer goes on that journey with you to tackle that and use a new approach, and you get proof point after proof point. And most industry verticals are very incestuous. What one does, the other wants to do or strives to do. And so as we establish proof points in energy and utilities and finance and retail and automotive and manufacturing, we’re even in the cruise line industry with Carnival, where these ships are like floating cities with thousands of network connected devices. As you have proof points in each industry, they tend to do what the other guy is doing and they don’t want their competition to get ahead of them, of course. So we just rinse and repeat.

Rodney Foreman • 40:37

And the knowledge that our team is gaining and also the knowledge our systems is gathering from all those customers is something we’ll be using in the future so that if you’re a utility company, And you want to optimize how you manage the grid, we now have knowledge and information from all the utilities we work with to quickly help you to do that because we have the data and the knowledge through these systems. So I think it’s use case by use case, industry by industry. We’re tackling it.

Ian Smith • 41:18

Some of those industries will be regulated. Sure. They’ll be handling sensitive data. Could be intellectual property, government data, people data about people. You know, you’re operating within, you know, could be pharmaceutical or medical data that is highly regulated. Yeah. Again, this idea of applying AI to regulated industries is another challenge.

Ian Smith • 41:43

It is. I suppose that in the network, you’re trying to obfuscate that by presenting the infrastructure, or how do you handle that additional compliance element?

Rodney Foreman • 41:55

Yeah. Well, each industry has their own set of regulations and security guidelines that we constantly are working to adhere to with our platform. But The largest banks, even federal government, energy and utilities, we’ve done a good job of making sure our platform is secure and adheres to those regulations, even across the US and all across Europe. I mean, there’s different regulations in Europe, of course, than there are in the US, and we’ve been able to stay in front of all of those.

Ian Smith • 42:36

What a difference, Ayurveda. What a difference you’ve made in a year and the team. How would you advise other product leaders or CROs who are responsible for growth, who are probably struggling to understand the trajectory? How would you advise? Like, what’s worked? Because, firstly, you’re highly positive and energized, which is amazing. I can feel it.

Ian Smith • 43:02

I’m loving it. I want to say loving it. And I’ve never been as excited about network orchestration in my life. That’s good. You know, how have you come across a few challenges yourself in the role, surely? How have you negotiated those? What lessons have you learned?

Rodney Foreman • 43:20

I’ve, you know, I operate with a sense of urgency and move quickly. And I’ve instilled that sense of urgency in my team and also the development team. I speak to our development team, you know, occasionally they want to hear what customers are saying. And my message to them always consistently is: we got to move faster, guys. You know, customers need these things. They need them yesterday. We really got to move faster.

Rodney Foreman • 43:53

And we also have embraced, you know, our partners like. You know, some of the partners we’ve met here in Europe and help them to understand how they can take their customers to that next level, and which provides focus on our brand. So, we are extending our reach into the market because I can’t reach all of the market with just a direct sales team. I’ve got to extend my reach and do that through partners and their sellers. And that’s helping us to scale and reach more of the market. The other thing is, you’ve got to be, you know, have a collaborative environment, as I mentioned before. You got to share ideas and you’ve got to be nimble and quick to act.

Rodney Foreman • 44:56

You won’t always get it right. You know, we’ll make mistakes along the way, and that’s okay. But, you know, you got to do something. You got to act on what you’re seeing in the market and stay ahead of the puck and stay ahead of the market.

Ian Smith • 45:16

Are you seeing any global or geographic trends on adoption or resistance? Like, you know, Europe, US, Asia, Pacific.

Rodney Foreman • 45:28

It’s more by industry. Certain industries are adopting. AI and automation in our platform much faster than other industries. It’s not necessarily really by country, but various industries are at different phases of adoption, depending on what industry you’re in.

Ian Smith • 45:53

What industries are you seeing?

Rodney Foreman • 45:54

That are ahead. Yeah. Finance, definitely ahead. The medical industry, I’m seeing more and more pharmaceutical companies, hospitals are relying on the network to do things autonomously. I mean, these hospitals have robots in the halls that do a variety of things that humans used to do. And then all their instrumentations, how they restock drugs and everything, is all network driven.

Ian Smith • 46:31

So the demands on the network is evolving too. Yes. So when we talked again over the last technology era of Internet of Things and the adoption, we’re talking about network reliant.

Rodney Foreman • 46:42

Absolutely.

Ian Smith • 46:43

But cognitive Internet of Intelligent Things now. We’re moving into an Internet of Intelligent Things where you have a much higher Bandwidth requirement, but also lower latency requirement as you’re getting intelligent activity within physical devices and machines. What a fascinating time we’re in. Yeah. What a fascinating time.

Rodney Foreman • 47:03

Well, doctors even are performing surgeries remotely using robots, but they’re, you know, they’re observing it. They, you know, a lot of doctors aren’t even, you know, doing the traditional diagnosis anymore. It’s all AI-driven and it’s much more accurate. But even surgeries, traditional surgeries that were, you know, you had to have a live doctor to do it, it’s now just monitored remotely by a doctor, done by a robot.

Ian Smith • 47:34

Yeah. So, this evolution of the requirement from the network, the increasing need for intelligent end devices that are analyzing and creating huge amounts of data that’s traversing the network. You know, the adoption of AI within the network to handle the AI workloads. It’s almost like if the workloads are going to go autonomous intelligent, we can’t be relying on a legacy infrastructure to service those devices and systems.

Rodney Foreman • 48:08

Yeah, because one of the things that really interrupts AI is latency. Latency is not the friend of AI. If you have high-latency network, a lot of these AI applications do not work. These systems are very highly dependent on high-speed and reliable network. And you’ve got to have an automation orchestration system behind it that is intelligent to make that work.

Ian Smith • 48:41

Let me ask you: this evolution of the topology and requirement from the network and this. Industry-leading work that you’re doing to upskill and up technology level the network to provide stable and low-latency infrastructure for that is only going to accelerate the application of AI in the real world. Yes. Which invariably is going to have a huge impact, both positive and negative. A few months ago, I asked you the question, I’m going to ask you it again. Do you believe, from what you’re doing in the real world, in airports, in medical and hospitals, do you believe AI will lead us to a utopia or dystopia?

Rodney Foreman • 49:29

Yeah, utopia. I still will answer the same. Yeah. Yeah, but there’s, I mean, you mentioned that you use the word guardrails. It’s got to be guardrails around it. But yeah, it’s definitely changing our industry. And it’s, yeah, it’s a utopia to answer your question.

Rodney Foreman • 49:53

We are in a computer game.