HITT – AI Enablement Strategies for SMB and Mid-Market Customers

We have a wonderful team from Keystone Technologies Keystone Solutions. Excuse me. And the group here has been a part of the Telarus portfolio for a long, long time. And many of you will hopefully recognize them. They have a an outstanding reputation for focusing on SMB and mid market customers, specifically in and around the managed solutions and security practice. They have a great go to market in that space, but they’ve also have focused on looking at what the gaps are in and around SMB and mid market, specifically with AI. And not only are they are we gonna go through this today and go through what their offering is gonna bring to the table with their CEO, Preston, Aaron, who’s the head of their AI enablement, Richard King, who’s the president of the company, and Jay Morris, who you probably are all familiar seeing because he’s at virtually every Telarus event that we do across the country.

He’s their channel chief. But what we wanna dig into today specifically is what is the SMB missing? How can we help them through this process? Help them understand what’s going on with AI and help them leverage it and set up themselves for success.

So all of this is gonna be a a part of the discussion today. And the one thing I wanna harp on specifically is you are going to get bombarded over the next week here in a good way as Telarus partners on a new Cloud Launchpad. That Cloud Launchpad is going to give you access to not only these recordings and all this information, but also our key cloud suppliers and trainings and all kinds of blogs, any type of services that we’re we’re focusing on, like VMware, which is another thing that that Keystone can discuss and help with as well. There’s all kinds of different things in this Cloud Launchpad.

So keep an eye out not only in your email, but also on our socials and LinkedIn and all that type of stuff. It’s coming out today. You’re gonna see it for the rest of the week and moving forward, and we’ll do a big formal announcement at partner summit too. But without further ado, let’s bring on Preston West.

He’s gonna lead the conversation here. And, Preston, if you can talk through really what brought this about. We’ve had some conversations internally, myself and your team here, about what’s happening in the AI space in SMB. But just kinda walk us through how this all kinda came about and then what your offerings are here. Sure.

So hey, everybody. My name is Preston West, CEO of Keystone Solutions, and we are a, MSP, MSSP based out of Southeast Tennessee.

And kinda going to what you were you were asking about, Chad, I think it’s no surprise to anybody that we are being inundated with people asking us about AI. And, usually, the questions that come to us are less about, like, doing it properly, but just, hey. We gotta do something with AI or we’re gonna get left behind. And so we saw right now as a perfect opportunity for us to officially expand what we do as a company to not just kinda leveraging AI as an add on or a license, but actually a full piece of our practice as a as a staff discipline, to be able to help walk customers, whether they’re a customer today or not, with navigating AI, doing it safely, doing it effectively, doing it on purpose, and then making sure that they’re getting the most out of what they’re actually spending.

So we have added a AI enablement services. Aaron West has joined our team this year to help us build that discipline, which includes not just the consulting and the advisory services, but also the actual automation and development practice. Aaron comes from, almost fifteen years of working in AI and automation development, workflow development, big data with some big projects that are, in his history and in his in his head. So he comes to us with a lot of experience around this.

And then using this as a good opportunity to really supplement what we already do for our customers today, which is making sure that what they’re doing around technology is effective, it’s safe, and that they’re getting the most out of what they do. And they have a partner in somebody that brings that expertise to the table. So that’s that’s kind of how we got to where we are today in talking about this.

That’s great. I I think, you know, one of the key things as you’re gonna discuss here with the enablement, practice is is really just getting, as you said, getting that groundwork established properly so that, you know, we don’t run into the issue that we talk about a lot of times on the Telarus side here at our events is garbage in, garbage out. If the data is bad, then the outcomes are gonna be bad. They’re gonna be wrong. They’re gonna not give what what the customer is ultimately looking for or to gather from that information. So if you wanna talk us through what this AI enablement practice looks like here, that would be great.

Absolutely.

I appreciate it. So you can go to the next slide.

So I’m not gonna be surprising anybody with with this type of data. I think we all know right now that spend around AI is growing. It doesn’t appear to be slowing down.

What we’re noticing is that very rapidly, it’s moving into the small and medium business spaces and kind of that mid market. Spend is up tremendously, both the vendors and their actual infrastructure spending, but also what our customers are spending. But on the flip side, what we’re finding is is that most of the spending being done by customers just isn’t landing yet. Either we’ve got people that know that their staff and their and their team are using AI, but but they’re looking around going, well, we spent all this money on AI. But the statistics, and these are recent as of some post polling this year, is that only about twenty two percent of people are saying that what they’re spending on AI is actually meeting their ROI expectations.

And that a big percentage of those same customers, it it becomes pretty clear just in the marketing in the or not the marketing, in the data and the statistics, not not to mention our conversations with our customers that they don’t have a plan and they don’t have a policy at all.

And so we wanna go through today some of the the gaps that we’re seeing over and over and over again around this space to make it to where the customers that you bring to the table with opportunities, are not making the same mistakes, and they can be outside of that, twenty two percent.

That that’s that’s a problem right now. So you can go to the next slide.

One of the things as we’re transitioning here is, you know, what I see time and time again is these small businesses, don’t understand or don’t even know really where and I’m seeing some comments in here that that this has seen a lot as a couple of our partners chiming in that are VCOs and and acting in that capacity. But the customer doesn’t even really know where a lot of the data resides most times. So some of it may be in SharePoint or OneDrive. Some of it may be in file folders elsewhere. Some of it may be in an old server in a closet somewhere. Do you are you seeing that a lot of this really needs to be, and we refer to it as data readiness, but it’s more along the lines of helping them kinda gather what data are they accessing regularly to do what they’re doing on a daily basis versus trying to, you know, rebuild everything from the ground up. It’s it’s really kind of taking what they do and and transitioning it into a a single dataset, a single clean dataset.

Yeah. I mean, when we get a little bit deeper into our slides, I think the the thing that we will point out specifically is that data cleanliness and data hygiene is a huge piece of what makes these projects actually successful. And Aaron’s gonna get into that in in a little bit of detail here in just a second. So that is a really good point.

And and I think that’s where our approach to this is a is a little bit different, and it’s by design, is that we are putting advisement and consulting into the products around AI. So even if we’re putting a product or licensing into a customer, a huge piece of that is not just the the system and the technology, but it’s actually working with the customer to solve those problems. We look at their data. We’re gonna be doing sort of readiness assessments.

And then at near the end of what we’ve prepared today, we’ve got some tools on our website already available that helps the customer go through that themselves and ask themselves the questions. I I think on the screen, what you’re seeing here are the things that we, feel like are questions that customers should have settled before they buy an AI solution. What are we trying to accomplish?

Have we talked about costs? Is what we’re talking about even an AI problem? And I think a lot of times people are are kind of feeling that FOMO and jumping the gun and diving straight into some sort of a product or a solution without doing the the work that you’re talking about with data cleanliness and hygiene and making sure they can even wrap their arms around things from a governance and a compliance perspective. And so where we wanna injected into this is making sure that these questions are being asked upfront before people jump into solutions. And so they’re not getting into things and then having projects and implement implementations that just never go anywhere.

Or on on the even, worst side, they are are getting data back that’s not actually trustworthy, which is a completely different issue. So when when we are, and and, again, these aren’t things that we would expect you guys when you’re talking to your customers or the company about AI to be able to answer, but it’s worth you noticing if nobody has asked these types of questions. Right? And so that that gets us into a couple things we wanted to talk about that’s really pointed exactly about what you just brought up, Chad, on what happens when nobody’s asking these questions. And Aaron has seen this way more times than I have with his with his experience and his background. So I’ll turn it over to him to go over some of the errors and the problems we see with implementations when these questions aren’t kind of answered effectively.

Thanks. Great.

And I’d love to be able to call myself an expert, but I don’t think anybody gets to be able to call them themselves an expert in a industry that changes every three months, you know, with AI. And so but the real the reality is is that, you know, we’ve built up a lot of scar tissue and and figured out you know, walked through the bramble bushes as it were to figure out how to do this right and seen a lot of things on the ground floor.

And I think the the main thing that’s super interesting about AI is that the output from a grounded system that has access to all the right data and an ungrounded system look almost identical. And so on the surface, they they appear to be as valuable. And so there is a lot of temptation for organizations to jump in and just start start building stuff. And I think the the danger that comes with AI is that the line between what you should be doing with it and what you shouldn’t is pretty fuzzy and is always kind of changing and changes depending on what how the quality of your AI system is implemented on the ground floor.

And so because that’s really fuzzy, you know, you have to either check every output, which reduces the value of the AI in in the organization. So that’s one kind of failure modality. And so there’s a lot of organizations who have already tried to adopt AI. Maybe they’ve gotten a bad taste in their mouth for it.

And and, you know, from an ungrounded system that they have to feel like they always have to check every time. But or on the other side is you get things that are confidently wrong, and people are just using it. And there’s all kinds of things, you know, terminology like work slop and things like that that have been invented. But, really, the the idea is we’re not trying to be AI Luddites or anything like that.

This is actually an opportunity because where there’s a lot of value for AI to be really transformative and super valuable when it’s safe, but also being, you know, risky when it’s not, creates a lot of value for us to be able to provide solutions for organizations who want to adopt it and keep them grounded in something that works. And you can go ahead and move to the next slide.

And so really, the idea is that as we move through these these different things and you can you can move to the next slide about people and process. Yeah. And so really, this is the most common failure mode for AI adoption is kind of thinking of it as a pure technology problem. And it really is a lot more than that.

There are a lot of processes that need to radically change to implement that level of automation and speed into the environment. And I think it’s important to think to consider too on the people side. This is one of the first workforce skills that it has an expiration date on it.

As things are changing month after month after month, the people side is super important to consider and is an opportunity. On the process side, is really important.

Organizations not really understanding how they operate. One example that I’ve used from time to time is building a kind of response writer for an organization who’s responding to RFPs and RFIs. They they wanted to understand, you know, were these things compliant? It sounds like a very easy question to ask an AI, and you can easily throw a document in there and it’ll just ask you, or it’ll just say, yes. Compliant. But what we found out in practice is that the organization didn’t know what compliance meant and that there were different parts of the organization that thought compliance meant thing a and different parts of the organizations that think thing b. And that’s a very simple case and it kind of metastasizes over time.

And so what we were able to do is feed all of the responses they ever had done, extract those rules as a canonical kind of canon of these are this is what the organization actually believes and, you know, the manifestation of many different writers kind of culminates in there. And so that that’s what a service that we were able to provide to help understand to help the business understand itself.

And so as we move to the next slide, I think Can I pause you there real quick, Aaron?

Go ahead.

I think this goes back a little bit too, Chad, to what you were just asking about. So there’s there’s a two modes to data hygiene. The first mode is around what you were referencing. Where does the stuff live? Right? It where where does where can these systems actually find it?

And and it does it have the right security controls around it? Does it have the right access to it? But then the other piece of this data hygiene is do we have our processes documented in a way that a machine can even understand what it’s supposed to do? And I think that’s that’d be, I don’t wanna skip over that as part of that data hygiene is that we’re talking about a couple of different things here.

Yep.

Yeah. And and I’ll I’ll I’ll dovetail straight into this next slide here where we’re talking about kind of how that manifests itself. So when we’re talking about that data hygiene, I think it it really has, like, business legibility. Like, can can the business understand what’s going on?

A friend of mine uses the the phrase, if you want a automated car, you first have to have a software defined car. And you have to have all of the telemetry in in there to be able to do that. And so one of the failure modes that we see a lot of times is that a lot of AI adoption happens unexpectedly or unintentionally. You’ll have one senior leader potentially go out and adopt a tool, it becomes just kind of a tacit thing across the company.

Or you have a lot of, like, behind the scenes adoption that nobody really talks about but everybody knows is happening. And really, this is where we talk about what is that strategic advantage that we can bring as an organization to help that AI adoption. So one of those strategy pieces is, okay. What happens when the pricing model for AI fundamentally changes?

Are we ready for that? Have we integrated AI into this critical business processes that now depend on AI costs that have 10x in price, which is a reasonable outcome. It may not manifest itself, but how do we manage that risk? And so there’s a whole risk management piece.

And so as we work up from kind of understanding the goals of the business and the and the mission, I think there’s the opportunity here.

And the way that we solve for it is really by inverting AI into these problems. And so as much as, like, the data cleanliness and things like that, we’ve had a ton of success being able to provide and surface that data with AI help and assistance, always human in the loop and and things like that. But using AI to kind of propel AI further into an organization is absolutely, like, one of the best ways to encourage it, and you have to do that strategically. And and like Preston said, on purpose.

And I think that it’s important to understand that there are these error modes and that there’s opportunity in in solving them. And like in, you know, the first time you learn how an electrical fire smells, you know, once you kind of smell what’s going on, you kind of say, okay. I I get that this is a people process or a process problem. And Preston’s gonna work go into the next slide and tell us a little bit about what that actually looks like in practice.

Cool. Thank you for for digging into that just a little bit. So, you know, a big piece of of what your guys’ job is, especially towards us, is is identifying opportunities. Right?

And so the these are the types of things that we hear customers say in their own own words, and they are dead giveaways that they may not have been asking the right questions up front or they’re making some of these errors that we keep seeing over and over. And the nice thing is that every one of these is an opportunity, and it’s an opening to to put put something in front of the customer that they need. And our take is none of these stand alone is kind of a license problem. With with licensing around all the AI platforms, we feel like the license is kind of the last ten percent of the actual work, and every vendor is fighting over that ten percent.

Our our approach to this is to be, the one that gets placed in the ninety percent of the actual hard work that needs to be done to make sure this stuff is successful and then working with the agent or whoever to make sure that the right products and the right things get placed into the customer so that they’re using AI effectively, and that they’re actually getting the business outcomes they need.

So you can go to the next slide.

So for Keystone, what does this mean for you guys in practice? What could I sell today, and where can I make money placing a a provider and a partner with my customers who can help them through this process? So we’ve got four doors that we’ve built around offering this to customers, and they all serve a a slightly different niche and a slightly different angle. So we’ve got our secure AI model that’s powered by hats.

You may have heard of them. And I think one of the things to to really highlight about everything we’re do we’re putting together as a product is that we will not sell a product around AI without the consulting hours baked into that product sale. We we believe so fundamentally that the work that we were just talking about and the plan and making sure the data’s right and talking about governance and security is foundational in making sure that organizations do this well and do it safely, that we are baking that into everything we do. So SecureAI is the fast path.

It’s the customer that just says, we just need something so that we can get in front of our users, and they have the ability to start using AI, but we wanna do it in a secure way. The the the differentiator here is that Secure AI path is actually priced per organization. It’s not a per seat, and we’ll get into why that’s important in just a second. The gateway path is for customers that may already be using AI, but they are wanting a safety layer that goes around it.

So it’s a managed AI gateway that that Keystone manages. We we charge a little bit for access to the platform and then some advisory and consulting services baked into that. And then it’s a consumption based model just like a lot of these other LLM platforms end up being. What this allows us to do is add guardrails around how people are actually using AI.

We can put in, like, policy enforcement to make sure that people, say, can’t put PHI into an LLM call. Right? We can stop it before it actually goes to an LLM and make sure that if they have compliance requirements that they don’t have, users inadvertently breaking compliance. And a lot and most of the time, what we see is people aren’t trying to be malicious.

They’re just trying to do the thing that’s most expedient to get their job done. Right? So it’s a safety layer that we can put against most of the ways that people are already using AI.

And then the the third door is digging into a lot of that deeper automation and development. That’s where a lot of the real money is. It’s helping customers actually dig deep into their data hygiene and their workflows, automating those things, and those will always be very bespoke.

The the the way that we’re structuring those engagements is that they are always going to be more of a subscription base. And so they’re a recurring revenue model for us.

They will probably always include the hosting and the LLM tokenization and things like that. But but by keeping these things on, a recurring revenue piece, there’s another onus on us as the adviser to make sure that the customer’s using the products we put in front of them. Right? We make more money.

You make more money if they’re actually adopting this and using this. And so that’s a big piece of what we’re doing is actually pushing adoption through their organization to make sure that they’re getting the best income or the best, outcomes, out of what we’re putting in front of them, and then we’re all taking advantage of being part of that revenue chain on the, on the back end. And then the last one is the advisory consulting stand alone engagement. That’s the only one of these that doesn’t have a recurring model, But that’s for the customer that says, I don’t I don’t know what to buy, and I’m not sure that we need to buy something.

We just need help figuring out where we are. And that’s something that we do today, and we’ll be able to to put in. And it’s the the the highlight there is it’s not an add on tax on top of the products. Remember, we we put advice and engagement into the other three products by default.

And so the advisory is just someone who says, let’s spend some money here so we don’t spend fifty grand on something later that’s not actually giving us the output that we need and the and the the outcomes that we need.

So, Preston, this is great because it it kinda breaks down the different offerings. And what what we have a question from Mark in the chat here is, do you have a, an example of how an SMB customer has used AI for their organization, specifically in and around your consulting? I know you’ve done this, and this is what’s kind of prompted you to to bring this to the channel here, through Telarus. So can you give us an example of something, that you’ve done in the in the recent past?

Sure.

The one that one that comes to mind specifically is, you know, remember our core business and where we started was as an MSP. Right? And that’s what we still do today. That’s our bread and butter today.

And so our customers look at us and look to us, most of them, as their sort of internal IT department. And so we have had we had a customer recently who, you know, came came to us and said, hey, guys. I discovered Claude Code, and I built all this stuff. And it’s really cool.

And they weren’t even thinking about any of the security aspects of it. They weren’t thinking about where where they were opening up potential gaps in their in their security posture. They were just asking us to attach this thing that was custom built into their Microsoft ecosystem so it could, like, read email and do things with email. Right?

And so that that is a prime example of customers getting ahead of their skis. And we don’t ever wanna be the people that gatekeep because we’re big fans of AI. We have adopted so much of what we’re talking about internally at Keystone, and it is becoming transformational for the way that we’re able to surface data and understand what’s going on day to day. And so it it’s a natural progression for us to say, okay.

Let’s let’s kind of go into an advisory mode for this customer and say, alright. Let’s show us what you’ve built. Let’s make sure we understand it. Let’s make sure that you understand how this may actually be circumventing a listed policy that we’ve built with you on this other side.

Right? Because I think a lot of times, a customer just wants to move forward so rapidly. And AI is cool. I mean, it can do some really cool stuff, and I am continually blown away with what what we can ask some of these platforms to do, and it actually, like, puts together something really cool.

But we wanna make sure that we’re tempering that with realistic expectations.

And for us, one of our key taglines is we keep you up and we keep you safe. Right? And so if we’re not doing that advisory service around what the customer’s wanting to accomplish with AI, we’re missing a big piece of that as well.

Yeah. I I think I think the key factor here is, you know, every everybody is trying to figure out how to how to leverage this, especially in the SMB space because it theoretically can add a lot of productivity. It can bring things to the table that they never really had access to before in the SMB space. But to your point, Preston, what I see is, I I I look at this, and I see a huge opportunity for the partners to bring the the umbrella over top of this.

Like, the their their customer is is leveraging this, whether it be ChatGPT or Claude or any of the others out there, and they overlook to your to your, point and statement there, they overlook a lot of the security aspects or the personal information or the customer’s information that’s that’s out there and that could potentially be shared for the sake of, hey. This is cool. I wanna roll this out. So I I really think what what is missing in our portfolio right now from a Telarus perspective, especially in the SMB space, is just this.

And this is why I was excited to have you guys on this week is the overarching understanding of the security practice that you bring to the table as an MSSP and leveraging that now overarching what what can be done in the in the AI space in and around these LLMs. So thank you for that.

Yeah. So you can go to the next slide. And we’re we’re okay on time, but I wanna make sure to leave a lot for, questions and things. So I’m gonna breeze through this one.

And I I think the highlight here, guys, is that sometimes what we find in these engagements is maybe the answer is Copilot licensing or Claude. Right? It doesn’t have to be something bespoke. It doesn’t have to be something that we provide necessarily.

But but the dangers here and the things we always wanna highlight, and this is part of the education process, is we see a lot of organizations just throwing licensing out at all their users and not actually getting the adoption that they want. They’re overpaying for seats. And then the other potential issue is that the more you do work in a specific ecosystem, you’ve gotta be sure that what you’re building is portable. So if you’re actually building things that your business runs on day to day, something in the industry changes.

Now you need to move that to a different platform, a different model, a different system. Is what’s been built portable? And if not, then you could be, you know, looking at some vendor lock problems and things like that. So I won’t spend too much time here, but just saying we our approach isn’t necessarily only selling in what we provide, but it’s it’s about making sure that what the customer is doing with their AI dollars is landing where it needs to land.

You can go to the next slide, please.

So here’s just a couple of high level examples of some potential deals just to give you some real world dollars, and taking it out of the the abstract. So the SecureAI product has a number of tiers. We’ve only highlighted the two most common ones here, that that we see people using. The managed gateway product, I have already outlined.

And remember, hours are included. Advisory hours are included in all of these products for us.

And we have the automation, the development stuff. And so the key here too, guys, is that you’re going to be able to place AI enablement with a customer, and you are able to participate in that recurring revenue as long as the customer is is consuming it from Keystone or wherever the other licensing is coming from, as long as it’s in service.

Next the next slide is a little bit of a call out, and I would not be doing my job if I didn’t, you know, help you guys understand the parlay in some of these opportunities moving into our managed services products as well. The reality is is that when we are doing AI enablement for customers, we have to necessarily touch all these different aspects of their business to make sure what they’re using is accurate, it’s right, and it’s what they’re supposed to be doing. What we end up finding is that there’s oftentimes gaps and there’s oftentimes other things that we can find, and everything we find as part of that process can become a real conversation and a real opportunity for another piece of other things that we provide in the MSP and the MSSP space.

The the the call out here for the partners is that this potentially becomes two revenue events for you, not just the one. Right? So if you’re bringing a customer into us, we’re doing an AI enablement, engagement with them, and it more so over time into an MSP engagement, you are still the agent of record against that account, and you can participate in that business too. And, again, that’s always worked in as a recurring revenue model too.

So it’s something I just wanted to make sure is that’s in our mind too. We know that most of your customers are not our MSP customers, and we’re good with that. But we do see this as a foot in the door to make sure that we stay as sticky as possible within these customers. And what’s what’s stickier than literally building and helping them craft a piece of their day to day business workflow and then the trust that comes along with a partner where they know we can also provide the security, we can provide the compliance, and we can provide the actual day to day support of those systems in in kind of a single package.

And so I don’t wanna spend too much time here, but I wanted to outline that that is something we see as an opportunity as well with putting this in front of you.

I think because what’s popping up here is is a question about, you know, existing MSPs and, you know, a lot of existing MSPs are gonna be addressing the AI, situation just like the customer is with a lack of understanding of and this is a great slide in my opinion because it it it outlines everything that needs to be touched. So when you have a situation where, you’re not the MSP, you’re gonna do a a a work with the existing MSP, alright, to to come alongside and help outline and specifically establish what the guide guide or guardrails guidelines or guardrails are in order to implement the AI properly for that customer. Correct?

Yeah. That’s right. That we we try as hard as we can. And and whether it’s a incumbent MSP or an internal IT department, we always try to be the friends in the room that’s helping us all accomplish our goals.

We try really hard not to try to come in like we’re gonna steal the business or move things around unless that’s what naturally develops through the customer relationship and those types of things. Right? So I guess the short answer there is yes. We absolutely work with other providers and or internal IT departments to make sure that we’re supplementing what they’re doing and not just starting on a replacement job from day one.

Great.

Go ahead.

No. I was just gonna say there’s some other questions kinda rumbling around here, but it’s more on your MSP side. So we’ll address those at the end here.

Okay. And then we’re we’re short or we’re almost done. So the Yep. The next to last slide is the last thing I wanted to highlight. So couple things you can do tomorrow.

A, we’ve got some free tools on our website. If you go to Keystone dot solutions slash AI dash resources, Calling back to that twenty five percent of people don’t even have an AI policy, we have a policy builder on the site that anybody can use.

It’s free to use.

The second tool we have is actually an AI readiness self assessment, and this is designed for the customer themselves to go through the six different dimensions of what makes these things possible.

And and we’re asking them to ask those questions we gave everybody at the top. Right? The questions they never ask themselves. And so prompting them through asking those questions about where does your data live?

Do you is your security set up properly? Do you have ROI goals? Have you budgeted for this? Right?

So all of the things that need to be part of that process. And then we’ve got a general AI adoption road map that is really a a framework for how we bring customers through this AI enablement.

All of these things are free to use. Full disclosure, we do collect email addresses and things to get email delivery of the outputs by necessity. We have to ask for email addresses.

So if you are pointing customers to our resources, be sure to let us know that you’re pointing customers to those so that if they do, come to us with more questions and things, we can make sure to credit the right people.

The second thing is be thinking about and, listening for those flag signals. Hey. We’ve got people using AI all over the place. We don’t know what they’re doing.

Hey. We put these licenses in our business, and it didn’t seem to do anything or change anything. We’ve got outputs that are disagreeing with each other based on AI. All the things we were talking about before, start putting together a list of things you’re listening for that are dead giveaways for opportunities here, and then make an introduction.

Jay is our channel chief. He is the he is your funnel, the keystone for any opportunities that may be around this or the MSP or the MSSP business.

He can help make sure we’re having the right conversations. We are, doing the discovery properly, and we’re actually putting the right solutions in front of your customers and building that trust with you and with the customers over time as well.

So that’s all that we have on the prepared side, Chad, and we are happy to answer some other questions. I think Aaron’s been answering a few in the chat, but happy to answer some other questions as time allows.

Sure. So the one that just came up from Frank, is wanted to address, you know, I think it’s a a situation where he’s an MSP. Frank is an MSP, and his concern is, you know, bringing a customer to you when, technically, your competition. How can you address that upfront, so that it’s you can attack it together where maybe he doesn’t have the expertise that you do, but what you wanna alleviate the concern of of the customer moving to you. Will you do some paperwork in between to make sure that customers don’t move, that type of thing? Will you structure it that succinctly?

Yeah. Well, I I think the short answer is yes. Right? And that’s our that’s our, that’s our strategy for most things.

Yes. And here’s what we can do to make that true. It has always been true for us and something we’re very careful and deliberate about working with Telarus is that we are not going over around any of the partners that bring business to us. And so when you bring business to us as a Telarus partner, you get to sort of build the rules of the engagement, so to speak.

And we can absolutely and usually do before we ever talk to a customer, we wanna make sure that those are those are understood. Here are the guardrails. We don’t want you talking about VoIP, please, because we already make money on the VoIP business. Or we already sell a email security thing, and so we don’t want you talking about email security.

So we’re we’re already used to doing that as it relates to our our other services, and this to me is no different than that. We develop the the rules and that we make sure that that we’re not overstepping each other because the the value here is that is that it’s your relationship. You want to be building trust, and we can help you build trust with your customer. And, like, let’s be let’s be honest.

There are some things that we do that we have to lean on other vendors too as well. Nobody knows everything about everything, and so we love working with with other vendors. Even if there’s some overlap and some potential competition, we try to we try to deal with that honestly and, upfront.

Yeah. No. I appreciate that. And and you are strictly with Telarus still. Correct?

Correct.

Yep. Yeah. So this is an exclusive partner. This is someone, again, that really is focused on the space that is lacking in in AI and the AI conversation right now.

So I just wanna drive that home that, you know, we we have a lot of enterprise solutions. We have a lot of upper mid market solutions. But the focus here in the conversations that I’ve had specifically with the team that presented today is to bring something to market that is not in the market right now, period. And I think it’s something that is, really something that is necessary, and it’s something that has been lacking as I’ve mentioned numerous times.

So I really appreciate Preston, Aaron, Jay, your time today, your ability to really kinda go over what’s what is available and and how you go to market and how you’ll work with existing partners, and not work around them. I think that’s really, really key. So appreciate you, driving that that point home at the end here. You are a channel based company, so, you know, that’s something as as well.

So you understand the channel. You’ve been in the channel for years and years now, and it’s something that that we are really proud of this relationship between Telarus and Keystone. You lean into us. We lean into you, and we really thank you for not only presenting today, but also the product set that you’re you’re bringing to market in a in a very, necessary and timely fashion.

So thank you.