Why AI Isn't the Devil and How It Can Save Your Business

Full transcript

The ideal client

K. Welcome back to the podcast, guys. Today, we are joined by Daryl Sable, the senior director of sales and partner alliances at Bizmetric. Daryl, welcome to the podcast. Thank you for having me, Zach. I appreciate it. So why don't we start by you telling us a little bit about yourself and what do you guys do at Bizmetric? Well, for starters, I'm a believer in the Lord Jesus Christ, but I love AI as well. Oftentimes people tease me because the two are, know, people say AI is the devil, it's not the devil. It's a great tool for helping businesses get what they need out of their data, and that's what we do at Bizmetric, is we basically provide them with data ready AI applications that help them move forward in their business in a more cost effective manner. Everybody's, you know, moving AI. It's the buzzword of the day. And that's okay, there's nothing wrong. Technology I think has always had some kind of buzzword. Used to be cloud, know, then it was machine learning, now it's AI. AI has been around for a long time, it's just that now through generative AI and

large language models that have made it easier for, you know, just everybody to use in their workplace, I think that's accelerated the motion considerably. And so now everybody wants AI, you know. And I talk to people every day and they're getting lambasted by their c level executives. You know, what are we doing with AI? What are we doing with AI? You know, when are we gonna do something with AI? And you know, oftentimes they already are in some way shape or form, just didn't realize it. So we've made it easy to get those AI wins under their belt, and then if they wanna custom design something as well that's a little more intricate and it's gonna take more time, we could do that too. Are there any specific trends inside of AI that you are observing in the kind of data science and cloud migration industries that you are in? So for migration, and that's the first piece, a lot of folks, because they didn't do their data right, are finding out the hard way that we can't even do AI even if we want to simply because our data's not structured properly.

And so you're having to have that hard conversation with them about getting their data platform correctly and and ready for AI use because, you know, garbage in garbage out, that's the general rule with data. So if you haven't maintained and kept your data clean, you know, you're gonna have issues once you start to implement AI because that's where it initially starts to learn and then continues to learn from in addition to the prompting done by the user. So I often explain AI to people. As a four year old, you know, you have to give it very specific instructions and detailed as to what you want, you know, it to do. Otherwise, you know, it's gonna bring you back the wrong thing, know. That's you know, most four year olds are very smart. If you tell them specifically I need a 16 millimeter wrench from the toolbox, it will say 16 millimeter on the handle, It's red, know, bring it to dad, they will bring you that wrench. However, you just go give me a wrench,

you know, they're coming back with any old wrench, and they're gonna learn from that. And you know, if you don't if you don't continue to instruct them right just like AI, it will become an entitled teenager who basically, you know, disrespects you at every turn. Don't So want your AI turning into a disrespectful teenager, so you want the data, you want the prompting to be right, and you know, so that's kind of what we help companies do is platform that data correctly. I would say the biggest trend is data acceleration. There are a couple of folks out there, we're one of them, that have our own intellectual property that helps Microsoft, AWS, you know, large cloud platform users to accelerate their data motion. The biggest barrier to entry for for migration to the cloud is you know, I have all this data. Say you're Pepsi or Coke or whoever, you big company, you've been amassing data for a lot of years in your data center, and you're just not getting what you need out of it. The the cost to to replatform this across your own hardware is just insane,

know, tens of millions of dollars. And then that's only going to last you for a bit because the hardware is gonna become obsolete the minute you put it in. That's just the way hardware works. So you want to get that data over to the cloud, but it's gonna take you eighteen months, you know. That's huge, you know, eighteen months of your staff focused on one thing, and that's moving data while you're still accumulating data. These data accelerators that we've built literally take that data and move it in eighteen weeks. So you're talking, you know, a quarter of the time it wouldn't ordinarily take you, a quarter of the cost it would ordinarily take you. Plus when it gets there, it's already modernized. So as it's migrating the data, this accelerator will modernize, deduplicate, curate the data, you know, all these things to eliminate or reduce pipeline drift. So once you start to attach your AI applications to the data when it gets into your lake house. Then all of a sudden you're like, wow, this is very efficient data to use and my AI is running very quickly and effectively. So data accelerators

far and away biggest thing going in the cloud space. In regards to the AI piece itself, that's a little more spread because every company has a different challenge they're trying to overcome. You know, of course, if if you're doing a lot of customer service and you're at the consumer layer, you know, AI bots are just, you know, huge for your business, you know, because you can get we we have over a 100 AI bots that are already developed, data ready, you plug them in, you program them with a couple of key features and off and away they go From, you know, voice recognition bots to to, you know, customer service bots, you name it. Bots inside of agents, we've got man, I quit trying to keep up literally on the amount of bots these guys have thrown out on a daily basis. I'm like, you know, just point me to the menu, I'll go in there and find the bot. When a customer says, hey, I need this, I'll be like, we got a bot for that. Here you go. Boom. You know, let's let's try it out with your data and you're

talking seventy two hours to being ready to go in a lot of cases. So that's that's Right. Game changer for companies, you know, when you can do that in in such a short time. And so that's fun. That's fun going through and just talking to customers, seeing what their challenges are for their manufacturing. It's a lot of testing type applications that they need for quality control and things of that nature. We do a lot of oil and gas, so health and safety is huge. We have, you know, computer vision, you know, movement recognition applications that will send off alerts when somebody walks into a zone that's unauthorized for for, you know, human contact. And then, you know, boom, here comes the health safety police for that company, and kick them out of the zone. So yeah, there's so many different things you can do. We we we just did a Databricks event for oil and gas down in Houston last week, And it was a half day event and we couldn't touch on near enough of of the cases

that are out there. The customers were just like, hey, we we don't know where to start, you know, because we have so many challenges we'd love to overcome. Tell us where to start. And you know, these these are big oil and gas providers, the biggest in the industry, and you know, they're as confused as the next guy. So if you're a smaller company, you don't know what to do with AI, don't feel bad, neither does most of the major energy providers in our country, You know? What made you actually focus on developing these solutions at Bizmetric? Customer demand. You know, we're we're very customer responsive and relationship driven organization. That's just how we've always been. And you know, like I said, AI's been around a while, so you have some huge big box providers as I call them. You know, your sales forces of the world, you know, your Oracles folks like that that that you know, have huge AI offerings and platforms. ServiceNow is another one. You know, these solutions for a mid to large size, you know, company are gonna run you over a million dollars a year, you know, just to get,

you know, the majority of function out of their AI platforming. What we found is most companies don't use 80% of that. You know, so you're paying over a million dollars a year to use maybe 25% of the AI solutioning within one of these big box platforms, you know. We'll create one specific to your need because we're large enough to do anything a customer wants, but we're, you know, small and nimble enough to do it the way they need it. So they bring us, hey, this is what we need, we develop it for them very quickly, test it against their data, make sure it's running the way they want. You know, we'll charge you a $120 a year for that, you know. Huge savings, much more efficient for what you're trying to do. And and for the price of one platform you use 20% of, you know, we'll give you, you know, eight to 10 specific application solution solutions applications for challenges you specifically want to overcome that you, you know, that are a problem within your workspace. So workflow agents, you know, you name it, we we can develop it for you. If

you could describe your ideal client, what makes them a perfect fit for, Bizmetrics services? The ideal client I would say is the federal government because they print their own money, you know? They never run out of cash. But aside from the federal government, I would say that you know, customer with a challenge that they're trying to overcome, If they're a Databricks or or a Microsoft user, they're gonna have some financial advantages because we are approved for all of the funding programs within Databricks and Microsoft. So, you know, if you're wanting to get something done, Microsoft will literally give us money to help you do it, and that's because they you know, if you're cloud native for your data, they want you to tap into that and you know, it generates more consumption for their compute engines, which is more money for Microsoft. So of course they're they're happy to help you get down your AI journey. There's nothing wrong with that. That's just Microsoft and Databricks being good partners. AWS does a little of that as well, not as much because AWS will put hands on keyboards.

But there's a downside to that because when AWS is doing everything for you, then the people in your organization aren't doing it for you. So they're not learning, they're not growing. And probably the biggest hurdle to all of this, to the AI, to the machine learning, to the data platforming, to innovation as a whole across the the industrial space is scaling. That's the biggest challenge, hands down. People can't keep up on the innovation as fast as it's happening. So whether it's healthcare, oil and gas, manufacturing, retail, doesn't matter. You know, you're trying to run your business every day and stay on top of what's going on, and this is breaking, and how come people aren't buying it this way anymore. And at the same time innovation's just flowing. And you know, all of a sudden one day somebody asks you about AI, how come we haven't automated this process? And you're like, didn't even know we could automate this process. News to me, they're like, well why don't you know this? And it's like, because I've been working on this legacy system you gave me four years ago, and I'm trying to keep it running.

So bright guy, why don't you help me out with getting this innovation in my head, and so then I'll be happy to tool it. So that's where partners like us come in, at Microsoft giving us funding to come in and sit down with a department within an organization, or the entire organization, know, it's really relative to the problem at hand, and then we will work with them to say, hey, this is the innovation you need for your space. What's going on right now? What competitors are also looking to implement that are are in the space against you? And then, you know, we help them overcome that. Mhmm. And what strategies are you guys currently using to acquire these new clients? Oh, man. So some of them we don't even have to acquire, you know, because of what we do and They what we they come to us. We also have a great relationship with Microsoft sellers within their organization. So since they're a partner led organization and generally don't put hands on keyboards,

they they bring business to us as well. We develop great relationships with them. Sellers at Databricks, it's the same thing, know, we're we're partner approved for their funding programs, and so their sellers will will work with us. That's why we did the Databricks event that we just did, but you know, we're always looking to improve how we reach out to the market and and you know, how it responds to us as well. We we we're kind of famous for taking young sellers straight out of college and then teaching them how business really works. Because I don't know if you're familiar with our university system, but it's changed a lot over the last twenty to thirty years. So you you kinda gotta do the teaching as soon as they come out because the teaching didn't happen where they were for non STEM degrees like SALES. So that's my job is to work with these, you know, these folks coming out of college and get them going into building relationships and and helping people within their business challenges. Daryl, what are your aspirations with Bizmetric in the upcoming months? Dude,

definitely to win the lotto and leave Bizmetric, you know. That's my overall goal. I'm gonna hit the lotto, take my millions, and be out of here. But until that happens, what I'd like to focus on is essentially getting relationship driven relationships out there with folks who can help, you know, with our branding and we can help with their branding. That's that's really what the alliance piece of my job is, is to work with folks like Databricks, Microsoft, AWS, Oracle, and anybody else who's trying to partner in the data and AI space so that we can, you know, essentially help people run their businesses. That's, at the end of the day, you know, our our whole world thrives if businesses are thriving. You know, governments aren't going to save us. That's that's the realization, know, people can bad mouth businesses and you know, oh, capitalism is evil, this and that and the other, but guess where governments get their money? You know, they get it through taxation on development and and and capital gains, and so you want people winning in business. Otherwise, they're just gonna print money indiscriminately and they're going to crash our economies.

Because that's what happens. We saw it through COVID, it's no secret to how economies work. So the best way for all of us around the world to prevent from that catastrophe happening either in a more micro, you know, just singular country format, or a global format is for everybody to succeed in business. So if if you're putting a product out there, Zach, whether it's t shirts, or whatever your idea happens to be, I wanna help Zach make that a success. I want Zach to be successful. You know, and that's the same for Coca Cola who's been around for years, or Pepsi, know. They got great soft drinks, I want them both to win, and I think that's a common misconception in business today, you know, that Bill Gates odd guy over at Apple, who everybody says is crazy, has Steve Jobs. You know, that's something that they you know, when Apple was going under and Microsoft saved them, you know, literally gave them, you know, half $1,000,000,000 to keep the company afloat. That's when they kind of showed the world that Microsoft doesn't have to lose for Apple to win,

and vice versa. Apple doesn't have to lose for Microsoft to win, they can both win. Open source is created around that whole philosophy that we can all win, you know. We just have to be willing to dialogue and work with each other and and understand that you know, a good negotiation is one that ends in a win win scenario, not a win lose scenario. And and and unfortunately, for so long, so much of business has operated under that precept of the win lose negotiation versus that win win. So that's what we look to change. That's what we're constantly trying to do with the folks that we work with. And, you know, hopefully, by working with you and and what you're doing here in your podcast, we'll get to touch more people and get that message out there. Right. Well, thank you, Daryl, for this podcast. I will add links so people can check you out, and thank you guys for watching. We see you in the next one. Absolutely. Thanks so much for having me, Zach.