[00:00:00] Betsy Cerulo: Welcome to Room at the Table, an opportunity for you to join me, Betsy Cerulo and my guests for conversations about creating equitable and inclusive workplaces where leaders rise above mediocrity and our teams thrive. Pull up a chair. There's always room at the table. Welcome to another Meaningful Conversation on Room at the table.

[00:00:26] I am Betsy Cerulo, your host, and welcome to my guest today, Gabriel Legend, CEO of Visionaire it. Today we are talking about how to wisely use ai. From a business standpoint and understand what risks may present themselves. So pull up a chair, enjoy your favorite beverage, and let's get started. Gabriel, welcome.

[00:00:51] Gavriel Legynd: It is so, so good to see you. Great to see you too. Thank you so much for having me. 

[00:00:56] Betsy Cerulo: Absolutely. You know, with, uh, with so much of AI in the space now there's, there's so many. I think questions, fears, myths, embracing, and I couldn't think of a better person to come on the show to, to really talk about it. And, uh, and it's such a, it's such a big conversation.

[00:01:20] So I know that we're really only gonna scratch the, uh, tip of the iceberg today. 

[00:01:25] Gavriel Legynd: I'll do my best to help you all. Opportunity.

[00:01:39] Right. You know, one of the biggest things that I see leaders trying to do everything at once. They wanna do all the things. And I guess because AI is the new shiny thing, they wanna figure it out. Right. And I, and I get that right, but. They get very excited about AI and then all of a sudden wanna implement it across the whole entire organization.

[00:02:01] Marketing, uh, operations, customer service, finance, all of it, right? And honestly, that's just really setting themselves up for failure. You're, you're gonna set yourself up for failure. So what actually works is taking a, a, a real focused, phased approach and picking one thing, just one, and running an experiment.

[00:02:24] To see what happens, your successes, right, and then measure the impact, not just the hype, you know? Then it iterate and improve upon where you started. Once you've got all that dialed in, then you're gonna move to the next area. We actually normally start most of our clients out with focusing in on their marketing workflows because it's a great place to learn without breaking anything critical within the organization.

[00:02:54] And I think everybody's trying to better market themselves online. I, I, I know we are. Right. And so maybe it's, it's, it's helping with content creation or analyzing campaign performance or, or something where you can see quick results. And get people excited about the possibilities and where we're going, where you're going as an organization.

[00:03:18] But here's the thing that's really important, is you've got to design with the end in mind. We, we tell everybody that design that's mapped this whole entire thing out, and design with the end in mind from the start. So before you start implementing anything, really think through the data sources. What integrations are you going to need to integrate?

[00:03:40] How is this gonna be connected to any other systems that are running some of the critical, uh, technology that you have? And, and probably most important, where are the humans going to be in the loop? Right? Humans in the loop here. Right? So because that's gonna be the place where. There's gonna be a lot of rub, especially with there being lots of conversations within organizations.

[00:04:07] Is AI gonna take over my job and all of that? We don't wanna do that. So the other piece of this is making sure, now that you have your team on board, they understand that we are moving forward, that you now have a person. That is going to be your champion in all of this. You gotta find somebody in the organization who's naturally curious, understands the technology, understands our game plan, where we're going, 'cause that's gonna help the whole team really get on board as well.

[00:04:39] Um, it's, it's, it, it's again, shifting the mindset. It, it, it starts there. It really does start there. The whole reframe is really about stopping this idea of just thinking that it's an AI transformation and thinking more about it being AI integration, one process at a time. Building a little bit of confidence with some small wins and then scaling with, um, based on those successes, 

[00:05:05] Betsy Cerulo: you know, from, um, from my organization. We use it at different times, so my work is staffing. You can't replace the nurturing of a con of, of a relationship with ai. You can do the framework, you can find resumes, you can, you know, look at different things. Uh, but what we are really clear about the, the strength of our work is in the relationships, and that's built with trust and that's built with human interaction.

[00:05:38] So I, you know, I certainly hear a lot of. Feedback, pushback about is it gonna replace my job now, you know, in the, in the work of human resources, it's human resources. So you can't throw everything out and think that AI is going to be this, um, you know, this shiny new car that's gonna save everything.

[00:06:04] Right? And, you know, so, so with your work in, in, in your company, um. When you come across companies that may have some of what I'm sharing with you, what's your perspective on that with the, with the human factor and AI? 

[00:06:22] Gavriel Legynd: So again, it goes back to people feeling reassured that from a leadership perspective, that you're giving them peace and confidence and that.

[00:06:37] Again, you're not going anywhere. Correct. You're going to be bringing on a co-pilot, right? AI is your co-pilot. It is your friend. You're still gonna be the orchestrator of that. And I'm gonna talk a little bit more about that in a few moments. But it, it's a, it's a mindset shift and I think the attitude, attitude within an organization is reflective of the leadership.

[00:07:02] And it sounds like within your organization, you understand that you're in the game of relationships. Relationships, absolutely. With your, with your employees, your team members relationships. With your customers and then your employees, relationships with customers, and creating this ecosystem of understanding that we all need each other, but we also need to leverage technology so that we can go faster.

[00:07:28] Further, we're all needing to do more with less. Yes. And, and that's okay. Um, but again, understanding how to use these tools as part of your competitive advantage and to also help you make more data-driven decisions. 

[00:07:49] Betsy Cerulo: And, you know, that's a good point when you said AI as a copilot, because from what I see internally with, uh, different, different programs that we have, AI is an add-on.

[00:08:03] To whatever we're using to help enhance it. So, um, I, I, I like that way you're framing it as it's a copilot. It's not everything. Maybe there are some instances where it is, but you know, as we know technology there, it's not a hundred percent, just like humans aren't a hundred percent. So, so you have to find a way to balance it, 

[00:08:26] Gavriel Legynd: right?

[00:08:27] I think. Yeah, I think, and to be your partner. Uh, in crime or copilot, however you, wanna frame it. But again, uh, people are really scared now. I know. And it's, it's, it's unfortunate, but it, I think it's a real opportunity for us as business owners, for us as individuals, is the way of the future.

[00:08:50] The workforce is changing, um, as it should, you know, it's, it's innovation. Um, and, and again, I think it's a real opportunity for all of us to. Continue to grow and expand our, our companies. And there's so many wonderful tools out here. I don't tend to get into talking a whole lot about specific tools, but there's a lot of things, there's a lot of shiny things that are available to us, and so I, I think it's a, a great time for us to start investing in our people by providing them with the best co-pilots.

[00:09:27] That we can, that we can integrate within our organization sooner rather than later. 

[00:09:32] Betsy Cerulo: Yep. I couldn't agree with you more. So, when adopting ai, what security risk or compliance pitfalls should businesses be most aware of? 

[00:09:43] Gavriel Legynd: You know what keeps me up at. It's not some sci-fi scenario, it's, it's what's happening right now in our offices everywhere.

[00:09:53] Everyone's trying to move faster again, doing more with less, and they're just not thinking through what these AI tools actually mean in their business. So I bet you if you walked through some offices right now, you'd find people, unfortunately copying customer data into chat, GPD. To get help with emails, we're throwing financial projections to analyze the data and to get quick summaries.

[00:10:21] I understand. Right. But that's, that's part of the problem, realizing that that information might end up in training models that they have zero control over. So that's a huge vulner, a huge vulnerability. And here's the scariest part, is this rush to use AI everywhere without even thinking it through and thinking about those vulnerabilities.

[00:10:47] Your proprietary information is basically walking out the door and you're opening yourself up to data breaches. Your brand reputation is on the line. Your competitors. You know, have access to some of this information, but most companies have absolutely no idea what's actually happening with their people and how they're interacting with these tools.

[00:11:09] And that's why you really need to have an, an well having in your, your tech stat, some type of technology that's watching that. Right. Um. Not just looking at policies that people sign and say, oh, I'm not going to put information into chat bt, or, I'm not gonna do that if that's just the policy that they're signing off.

[00:11:30] Right? But I'm talking about using something that, uh, can see when someone's about to share sensitive data and stop it in real time, automatically redacting what's. What should be protected and giving your security team actual visibility into what's happening across all of these different AI tools that are available at the browser level, browser level, and even um, custom built, right?

[00:11:58] So data leakage, huge problem. We see it all the time. We get a lot of calls about that. What, what do we do, right? And so you need to have those guardrails in place from day one. Very, very early on. This is part of that strategic planning, so approving those tools, right? What is it, what, what, what do we need to do as an organization to get these particular tools, whether it's chat, GBT or any of those things on the list approved lists that when an A laptop is issued, et cetera, that these are the tools that are approved.

[00:12:32] Um, and, and, and that's it. 

[00:12:35] Betsy Cerulo: Well, you know, let me, let me ask you a question about chat, GPT. 'cause I've heard various conversations about it. I certainly see the value of it, but I've heard that chat, chat GPT is like almost like a people pleaser. It's spitting back what it thinks you want to hear. Yet. So once I heard that, then of course I was like, okay, so then wondering what percentage of the data information that I'm receiving back is accurate and what's just framing it based on what they think I wanna hear.

[00:13:10] So is, is there any kind of data that shows. What's, you know, a percentage of what's accurate and what might not not be accurate? 

[00:13:22] Gavriel Legynd: That's an interesting question, and I think it's continuing to change and evolve. 'cause again, the models, you know, we've got 2, 3, 4, 5, they're, they're continuing to be rolled out.

[00:13:35] They're, they're, they're training on a lot of this, the, the data. Right? And so the thing is, is yes. AI is going to hallucinate, perhaps it is going to tell you what you want to hear in you understanding more about how to use these tools. It is about learning how to best prompt, right? So as you're building out a prompt and you're asking it some type of question, um, that you know you need to have facts behind it.

[00:14:09] If you make that part of your actual prompt that it has to cite the source, so then you can go and verify it right? Then you have an opportunity to go and again, human in the loop. Verify, trust, but verify and make sure, maybe not always trust, but just verify. I'll say that, go and verify that this is actually true.

[00:14:35] Right, but now it's aggregating that data a lot easier for you so that as you do the prompt, it's giving you the, the output, but it's also giving you the source. You can go check it and say, yes, no, this makes sense, or perhaps it took it out of context. Those things do happen. 

[00:14:53] Betsy Cerulo: And that, you know, that makes sense because when I would use it periodically for some research, I would think, okay, well this looks good.

[00:15:01] You know, it came up really quick. Let me go over to this website that I know is as trusted as it can be to see if it's the same. So I would see maybe what looked good, what, what didn't feel right. Um, but you know, then I wanna ask the question 'cause we see. We see lately that there's lots of, um, what's the best way to put it?

[00:15:26] Questioning about data that gets released, um, that is not, not necessarily has anything to do with what we're talking about, but you wonder the data that gets released from sources that we think are trusted is not necessarily, or it's. Or it's, uh, either embellished or it's massage to serve another purpose.

[00:15:52] Does AI pick that up or is it extracting it, even if it's a website? Uh, what you would think is a, is a legitimate website or reliable? Does it pick but the data's not accurate? Does it pick, still pick it up if the accurate, if the data is inaccurate, of course. 

[00:16:13] Gavriel Legynd: Yeah, it's going to, to pick that up. But again, going back to verifying and validating that data to ensure that it, it is true.

[00:16:26] I think there's a ton of, there's a ton of websites that, again, again, we, we think the data is correct, but it, it isn't. And so these models, Chad, CT, quad, et cetera, are going out here and searching for. Data and then now you have to wonder, well, where did it really come from? Again, validating that source because if it rep references a website that you know is not reputable, then of course now it's, it's not right.

[00:16:58] But again, it human in the loop. The person who is building the prompt should know enough about what the best output should look like. 

[00:17:10] Betsy Cerulo: Mm-hmm. 

[00:17:11] Gavriel Legynd: Right, because we're not asking it to crunch numbers and financial data. I think it's great at those things, but if we're trying to conduct research to determine.

[00:17:21] Um, you know, I don't know where should I send my college? My, my, my student to college that wants to major in biology. It must be a top 10 school, whatever, right? You understand where I'm going with, but if you're, you're asking it to go out there and search and understand more about, uh, what school is better than another school and things like that.

[00:17:41] Of course, all of those schools are gonna say, oh, we're the top 10 school, one of the top 10 schools for biology. Okay, but is that true? What makes that true? Let's look at the data and the numbers to understand. So if the school. Uh, those top 10 schools are not providing the best data. I don't know, maybe they're tweaking the numbers up a little bit.

[00:18:02] Who knows right now that model, sorry. Now chat. GPT is gonna pull back that information and now you can go and verify and again, check the information to validate it. 

[00:18:12] Betsy Cerulo: You know, when you, when you bring up college, I have a grandchild that's in college, so. Um, I'm sure she'll listen to this. So my question is, so if, if you take it like when kids are writing papers in school mm-hmm.

[00:18:28] Is there also a way that teachers are able to find out, is this, this sounds good, it's it, you know, it looks like a good paper, but is, is there, um. I guess are there, is there software out there or something that, lets say a teacher know if their student is basically plagiarizing and pulling it right off a chat, GPT or, or, or another resource?

[00:18:58] Gavriel Legynd: Absolutely. There's quite a few AI checkers available on the market right now, even, even free ones, uh, that you can copy and paste that information into, um, the platform and it will say, uh, 20% of this paper or 20% of this blog, et cetera, um, or content. I'll just say content is AI generated. Right. So I, I think that that is important for professors, teachers, et cetera, even even parents, um, to, as they're looking at, at papers and, and you can look at it and say, this looks my, like my kid's writing, or it just doesn't, it's, it is just not their voice that you're leveraging these tools to make sure that the students are using AI responsibly.

[00:19:53] Again, it is a tool I think that as, as part of children or, or young adults growing up in today's society and us wanting to make sure that they're prepared for the workforce of the future, that they understand how to use these tools and that it is not used in a way that they, um, are not. Adding their own energy, their own voice, their own thoughts to it.

[00:20:24] It should help them. It should be their copilot. Right. Going back to this copilot model. Mm-hmm. It should be a copilot for them. That, again, it's used as a tool, but it is not to be used in the absence of, you know, them not. Wanting to think and process and truly learn. So again, it's a, it's a great tool. But, um, to your question, yes, there are quite a few pieces of software available on the market that can help professors and, and, and even parents to make sure that their students are, um, actually using it responsibly.

[00:21:04] Betsy Cerulo: Well, you know, that's, that's a lead in to my next question, you know, in business. So how can companies, and you've alluded to some of it, mm-hmm. How can companies train their teams to use AI responsibly and confidently without fear of replacement? 

[00:21:19] Gavriel Legynd: Great. If you're rolling out AI tools and at the same time you're talking about cutting costs and you know, getting more efficient, your team's really gonna put two and two together and, um, it could or couldn't go the way you want it to go.

[00:21:34] So what I always tell leaders is to think about, um, AI is again being their their copilot, right? It's your partner. That's it. It's not about replacing anyone, it's about making sure everybody's able to. Move the, the needle forward and improve productivity. The companies that are really winning right now are the ones that are using AI to drive sales, marketing, cutting down on mistakes, speeding up things, but the humans are still running the show.

[00:22:03] They're the ones who are orchestrating these efforts. So on top of copi, of, of ai, baker copilot, humans now have to put on a new hat of understanding that they're the. Conductor and or the orchestrator of all of this technology. That's why it's so important to have an AI ambassador as part of your strategic AI rollout plan.

[00:22:26] So now it really does shift their mindsets. Instead of getting people scared, they're actually excited. So when you bring your team to the conversation early and often, where they're able to see where AI can actually improve their job satisfaction. So that's, that is possible. Mm-hmm. So perhaps it takes over that boring thing that they didn't wanna do, or the repetitive stuff that they, they they just didn't like.

[00:22:57] Right. So now they're able to spend time on more interesting work. So if I could take the form of str strategic. Planning, um, building out real relationships with customers and clients, going to events, shaking hands, kissing babies, doing those things that, that human work, um, that's, that's so critical to, to our, our businesses.
[00:23:19] And that's the stuff that humans do well. And so we should be encouraging our team to continue to do those things. But the biggest thing here is, is just being honest about where you're trying to accomplish, what you're trying to accomplish with your team. Getting their buy-in and commitment early, and if you tell people you wanna train them up instead of replacing, we're training you.

[00:23:38] Right? This is part of, this is our commitment to make to, to you as being a team member, is we want to train you on how to use. These, these pieces of technology, giving them promotions, um, every, everybody appreciates that, right? Um, incentivizing them to, again, adopt it, adapt to it, and now the buy-in is, is all along the way.

[00:24:03] And so nobody's shuffling and, you know, slow walking. It's like, no, that's just really not going to, to help us move the needle. 

[00:24:11] Betsy Cerulo: So from a proposal standpoint, 'cause I've had this conversation with quite a number of people and we don't do it be simply because of this piece of information. So if we were to take one of our concepts and put it into AI chat, GPT we're to, to make sure, uh, I guess to get a better read on it.

[00:24:33] If we are giving over proprietary information into that tool, it then becomes. Public information, correct?

 
[00:24:43] Gavriel Legynd: Yes. 

[00:24:44] Betsy Cerulo: Okay. So it's best when it's, if you are wanting to frame something that's more general, that's where it's probably a better tool. So you're not giving away the secret sauce. 

[00:24:58] Gavriel Legynd: Well, there's, there's different ways to really, going back to the proposal question really quick.

[00:25:04] Um, there are several different. Platforms that you're able to use where you have essentially a closed system, right? So your data, your information is not part of the training model on any other platform, right? But you're able to make the best use of the platform, again, to refine text or to say it in a better way, tho those things, right?

[00:25:32] Even maybe to crunch some of your numbers. So there are options available. Obviously, chat, because chat you can t is, is is the first tool readily available, uh, for people to, to, to consume and use. But it is not the end all, be all when we're talking about, again, proprietary information. And needing the team to now move a lot faster using it, but then realizing that we don't want to have our competitors having access to that information too.

[00:26:06] So again, there's, there's, there's other, uh, ways in which you can leverage a, as an example, Microsoft Copilot, right? Mm-hmm. Yep. You can use that, right? So there's, there's different ways in order to do that where now you're in a closed system and your data is protected. 

[00:26:23] Betsy Cerulo: You know, and, uh, because we have copilot as, as part of utilizing the, uh, teams, and that was something that I would, you know, think about.

[00:26:34] Okay, well there's gotta be a way to protect the data. So when you use the term a closed system, that makes it more, uh, understandable, where it's almost like, um, what's the word I want? It's almost like a firewall for your, your data. 

[00:26:51] Gavriel Legynd: Exactly. Exactly. And again, going back to something I mentioned before is if you, or if your team members are, are, uh, actually, let me, let me take that back.

[00:27:06] I was about to say something, um, that wouldn't make that much sense, but essentially if you said, I'm going to make sure that copilot. Is available and accessible to my team so that they don't have to use chat GBT or things like that. 'cause there's a a, a short, short window. Short deadline, right? Because again, people gotta get it done and obviously chat, GBT is one of those ways, or coll, et cetera, is one of those ways.

[00:27:37] But essentially if there's, there's a cost of you to you and to, to weigh and to the way that your team is working, where if you don't adopt it. Then they're gonna find a way to do it. 

[00:27:48] Betsy Cerulo: Mm-hmm. 

[00:27:49] Gavriel Legynd: And so now we have to figure out as leaders, Hmm. You know what? How about we adopt a closed system? This is the process, this is the procedure.

[00:28:00] Yes. We want you to use AI a thousand percent. 'cause now from a proposal perspective, we can roll out more. Better, faster if they're not allowed to use chat GBT, but still or any other tool. Um, but they still have the same deadline. The odds are that people are gonna still try to use and meet the deadline using these other tools, right?

[00:28:26] Unfortunately. And so, as I was mentioning before. We do have a, a piece of our, our piece of software that has a wall that, that pops up and says, Hey, Betsy, it looks like you're trying to put in here proprietary information or a social security number or anything. That you shouldn't be doing, and it will not allow them to move forward.

[00:28:51] So now you're putting guardrails on even at the browser level, how they're operating. But again, there's so many different options out here and, and, and I, and I try to tell, uh, leaders that are trying to figure it out. That there is a way that you can do this. You can be both innovative and secure at the same time, um, and continue to provide your team members with the tools and access to things, to, to really show up in a totally different way.

[00:29:20] Betsy Cerulo: So if you were advising a CEO today, perhaps me, what, what phased roadmap would you recommend for adopting AI while designing? With the end in mind. 

[00:29:36] Gavriel Legynd: So phase one is really about looking at how can we get quick wins and just learning how this stuff really works. But then here's what a lot of people tend to miss, is before you go buying AI tools and looking at, you know, paying for something else, look at what you already have.

[00:29:54] We just talked about copilot, but Salesforce has AI built in. Um, your marketing automation platform probably already has some AI features that you really haven't even touched. So why not start there where you already are and figure out. You know, how can we better utilize these features within our current products that we're, again, already paying for?

[00:30:18] And it isn't another tool that your team has to learn, it's just now turning on that feature. It might cost a couple of more bucks per month per user, but at least they're already familiar with the tool that, that they're already using. And now it's just an additional feature that's that's turned on. So phase two is really where we're gonna start to connect some of those dots and, and take a look at what's, what's really working and expanding on that.

[00:30:44] But. Now you have to think about how can we get these tools to talk to each other. Mm-hmm. Maybe your customer service AI agent starts talking and feeding, uh, insights into maybe your sales team or your marketing bot is helping inform product development as an example. But essentially you're building these, this data infrastructure and developing an expertise also within the, the company.

[00:31:12] In that next phase, phase three is really where things get interesting and you can get a lot more creative, and this is where now you can think about AI agents, right? I'm sure everybody's probably talked, uh, heard about AI agents and agent AI and things like that, but we're really talking about AI that can take actions on your behalf, not just give you insights that's totally different.

[00:31:38] So now you have an agent, um, that is running 20 or can run 24 7. Imagine having, uh, your whole entire on onboard customer onboarding process be. Automated and coordinate different things between different teams, or they can even make outbound phone calls mm-hmm. As example to, to customers, customer satisfaction, et cetera.

[00:32:02] A form fills happens on your website in a, in a, in a, in a call takes place. So those things are actually possible and you can create some very complex workflows that are again, going to now, uh, supplement. Your human capital, your humans that are actually doing that work. And so now when they come in, in the morning, that agent has been working all day, all night, and now they can look at maybe the reports or the output of the prior days.

[00:32:31] Walk. 

[00:32:32] Betsy Cerulo: Makes sense, makes sense. Let, let me ask you, so do you go into companies and assess, like if they wanna say, okay, I want to enhance my current systems with some form of ai, do you go in and and look at assess, here's what they have, here's what we recommend? 

[00:32:51] Gavriel Legynd: Absolutely. So that is what we call workshopping.

[00:32:55] Okay. An audit slash workshop. So if you, Betsy, will just. Take, take you as an example. You said, Hey, we're, we're using AI in these ways. Okay. I'd say, well, what is it that we're looking to accomplish? What do you believe is possible and what do you want to see happen? If you know best case scenario, and let's just say you said, Hey, it's taking us, um, three weeks to complete a proposal as an example.

[00:33:24] I'd say, okay, great. How many proposals do you want to. Create, have your team create in a month. If you say, Hey, I want it to be five. Okay, great. So now we've got the end. The end is five in 30 days. We also look at other areas, and again, that's just for proposals, but we look at other areas in the business where maybe there's some inefficiencies and come up with a, a, a, a roadmap, but also a workshop.

[00:33:54] Right, because we are, we're not gonna, we're not gonna build anything. We're still in design mode. We're still designing and understanding how your business operates, what are your, your, your goals for each of the different departments? What is your goal as a company? Is there a certain revenue goal that you're trying to meet?

[00:34:12] That if we integrate AI into one of these areas, we're gonna start to kind of see how Wow. Um, there we've, we're, we're really seeing more efficiency happening within the team. Our team is way more productive again, in looking at the data, but we have to design with the end in mind. We have to leverage data acro all along the way because we can't improve what we don't measure.

[00:34:38] So that's why true. When I was saying if we take piece by piece, design, develop, look at the data tweak, all right, move to the next phase. But again. It starts with, with workshopping. So yes, we do do that. Um, that's, that's how we actually get into a lot of a larger, more complex build, and it allows our, our, our clients to really see how we think about their business, how we think about technology assessing risk.

[00:35:11] Right. That's a huge piece of this, right? Assessing risk, looking at the security impacts. Is there vulnerabilities just because you wanna buy a piece of technology because it's mm-hmm. The, you know, the, the new shiny thing does not always mean that we should, and it does not mean that it is going to be the most, uh, viable.

[00:35:32] Sustainable piece of technology that helps us meet those business goals. 

[00:35:36] Betsy Cerulo: Now, is there a certain size company or certain industry that, that your company typically focuses on? 

[00:35:46] Gavriel Legynd: So since we're also in the government contracting space, we support a lot of folks in the GovCon suite. So that's expansive. Right.

[00:35:52] But historically we've supported a lot of folks in the architectural engineering, construction, manufacturing, uh, more the industrial kinds of companies. But again, over the last, I'd say two years, we've had a ton of different types of companies we've been supporting, um, proposal writing companies, which is interesting.

[00:36:11] Even brought up proposals because we, we do support several of those because they understand workflow and process and procedure is critical to cranking out. These proposals for their end customers who are also government contractors. Because again, um, with there being so many changes in administration and with proposals and contracts, et cetera, that now they're realizing that we've gotta do, we, we've gotta again, do more with less.

[00:36:40] And how can we use and leverage these tools, um, to, to do that? 

[00:36:47] Betsy Cerulo: So. As we're, as we're bringing our conversation to a close, tell our listeners what's your primary work? What type of, I, I'd say what are you most proud of in your company and how you've supported your customers? 

[00:37:07] Gavriel Legynd: Yeah, so what we're, we're really most proud of is just the fact that we have.

[00:37:13] Supported companies who are trying to understand more about innovation and its risks and visionary it. If we draw a circle for innovation and technology and security visionary, it sits right in this center there, right in that sweet spot because we do believe you can be both innovative and secure at the same time.

[00:37:37] And so because. The world has, has, has been changing so much, especially over, you know, since 2025, um, that they're trying to figure those things out. There's tons of businesses, unfortunately, that have gone out of business or, or lost a significant, significant amount of, of contracts. And so us being part of their go-to team that helps them not just.

[00:38:08] Stay in business. Mm-hmm. But really thrive. Mm-hmm. There's tons, again, of, of, of opportunities here, whether it's federal work, state and local, et cetera. But now having a way, having a technology team like us that understands how critical it is, how, how critical time is not just, you know, getting the proposal in on time, but your, your employees having their time too, that.

[00:38:35] Bringing us in, we can help solve a lot of those problems, and we understand where you're going. We understand how to really secure your data and be part of your growth. 

[00:38:47] Betsy Cerulo: Well, you know what I see, and I'm, and I'm sure you do as a business owner, we've had to really work smarter and wiser on staying. Ahead because there are so many rapid fire changes this year and whether or not we like those changes, this seems to be a, a typical theme that I share.

[00:39:11] Whether or not we like the changes. As leaders, you have to keep looking down the road because if you just say, well, we did it that way, you know what? What we did a year ago, it does not matter. Now, as far as customer service, integrity, all the foundational things that, that we have built our companies on, yes, those all stay intact and we enhance them.

[00:39:35] But to be, um, to be ahead of the game. And cutting edge. It doesn't mean that we have to invest millions and millions of dollars 'cause the small businesses, we don't have that, but we have to be ahead of the curve. Right.

 
[00:39:52] Gavriel Legynd: I agree with you, and it goes back to something I was saying about you're paying for some of these tools already.

[00:39:59] Mm-hmm. Cloud, Salesforce, HubSpot, any of these pieces is a tool. I mean, there's, there's tons of them. It isn't gonna cost you more to get the best squeeze out of those lemons. It's just not. Right. Looking at what you already have. 'cause again, there's always gonna be something that pops up that, you know, it's like a squirrel and you go head off to go catch it.

[00:40:22] And, and, and, and that's not the best way for us to, again, stay cutting edge, to stay nimble. Mm-hmm. Uh, and, and support our, our employees and continue to grow our, our company. 

[00:40:36] Betsy Cerulo: Yeah, absolutely. Well, Gabriel, I just, I appreciate your approach to this topic. It definitely has more of my attention and I know that for many of our listeners who are small business owners, probably medium sized businesses and, and work with companies, we want to make sure that we stay really relevant.

[00:40:57] And you've made a really good case how you don't have to be. Afraid of replacing, you have being replaced. You have to understand the tools to see how you can even leverage your role into more of a position of strength. And I think the more information that we all have on technology and how to use it, right versus racing to get it done, I think we're gonna get people's attention more when we stay on that path of how to improve.

[00:41:29] Gavriel Legynd: Exactly. Yeah. Thank you so much for having me, Betsy. 

[00:41:32] Betsy Cerulo: Oh, Gabriel, absolutely. I just really appreciate what you've given us today and appreciate the conversation and as always, your work is, is so filled with integrity that it, it's, you are the kind of co-pilot I would recommend for my own company and to, and to our listeners out there.

[00:41:51] So I just wanna say thank you so much for today. 

[00:41:55] Gavriel Legynd: Thank you so much, Betsy. It's been a pleasure to be here, uh, with you. Deep bow of gratitude and I look forward to, uh, supporting you and or your listeners in the very near future. 

[00:42:07] Betsy Cerulo: Wonderful. Thank you so much. And listeners, uh, please make sure you listen intently to this conversation.

[00:42:15] Seek out Gabriel and Gabriel, how should people get in touch with you, should they be interested in your support? 

[00:42:21] Gavriel Legynd: So you can reach out to me via LinkedIn. I'm always on LinkedIn. Uh, they can also send me an email, uh, at Gabriel.legend@visioneeringit.com. 

[00:42:35] Betsy Cerulo: Wonderful. Thank you so much, and I wish for all of our listeners much success and more wisdom as you thrive and grow your businesses.

[00:42:47] Gavriel Legynd: Thank you. 

[00:42:48] Narrator: Thanks for listening to Room at the Table. If you've enjoyed this episode, follow us on your favorite listening platform and share this episode with a colleague or two or three.