Artificial Intelligence is no longer a future concept for the mortgage industry—it’s becoming a competitive advantage in real time. In tomorrow’s LinkedIn Live, David Lykken sits down with Garrett Locklear, founder of Candid and one of the industry’s most innovative loan originators, for a fascinating conversation about how AI agents, workflow automation, and hyper-personalized marketing are transforming mortgage sales and operations. From replacing repetitive administrative tasks with AI-powered automation to creating market-specific newsletters and blogs that dramatically increase engagement, Garrett shares practical examples of how lenders can use AI thoughtfully to improve efficiency, reduce costs, and deepen client relationships. The discussion also tackles one of the industry’s biggest challenges—data silos—and why solving that issue may determine which companies truly benefit from AI in the years ahead. If you want to understand where mortgage technology is heading and how to position yourself ahead of the curve, this is a conversation you won’t want to miss.
[David] Listeners. I want to let you in on a conversation that I have with someone every week. This individual is as innovative as anyone I’ve found. He is using AI in ways that quite frankly, I’ve never heard anybody using. He’s having success. It’s not surprising that he’s a tech guru. He knows he has his own tech company, it’s Candid and we’ve talked about him. He’s a regular sponsor and a dear friend. I have the privilege of being involved in his business, coaching him and being a consultant to his business and he’s also an outrageously successful loan originator. And I’m talking about the one and only Garrett Locklear. Good to have you back, Garrett.
[Garrett] Thanks for having me, David. What an intro.
[David] Yeah, well, it’s one of the things I thoroughly, thoroughly enjoy is our conversations when we get on every week, we talk about what’s going on and you have an outstanding platform. I want to make sure everyone checks it out. Go to candid.inc folks and learn about this system. You got to see it. You got to take a look at it. He keeps the website up to date. It is so innovative, but we’re going to be talking a little bit about that. But more importantly, I want to get Garrett to talk to you, our audience about what’s how he’s using AI so effectively in everything he does. So Garrett, where is AI currently making the most impact in your business?
[Garrett] That’s a great question, David. And I come from several different perspectives as a loan originator, as a guy who runs a startup, a small company, it’s becoming a mid-sized one.
[David] That’s fast coming in mid side years to having a lot of success.
[Garrett] Yeah. And so I love the different perspectives that I come from though. You know, one is sales. You can think operations as well as someone who’s running a company and there’s lots of great applications for AI and all of that. So, a couple of examples to give you and think of this as like you’re a business owner. You’re running a business. One thing that caught my eye is we were spending, you know, $800 to $1,500 an hour to have a lawyer just read through a pretty standard non-disclosure agreement or our standard subscription agreement with Candid that had maybe a couple of lines of red line and so I thought to myself, rather than pay someone $1,500 an hour to do that, why don’t, since the contract’s already been written by one of the top SAS,
[David] Probably one of the top attorneys already. Yeah.
[Garrett] Same enterprise that works with Salesforce. And we’re only looking at updating a couple of lines in it to meet a customer in the middle. Why not just have AI analyze that, provide a quick analysis and make sure it’s okay and so it took about 15, maybe 20 minutes, but for the first time I created a custom GPT with Chat GPT. I didn’t have time to write all of the things you have to write for it. So, rather than type everything out, I had ChatGPT type the prompts to create the custom GPT for what I call our general counsel.
[David] Your general counselor, GPT, that’s amazing.
[Garrett] And our general counsel, which we got the cost reduced from $1,500 an hour to $20 a month. That’s pretty good.
[David] Wow, pretty, pretty significant. Yes.
[Garrett] If you’re in Chat GPT, you can go to more GPTs in the top right hand corner. It says create, I think is what it says. And then you get hit with a big form and it’s like, what do you want to create? have to fill out all the things and so instead of doing that, you just copy paste that into ChatGPT. It walks you to exactly what you want to do. You can even go to a different ChatGPT to really curate your idea and essentially what you want to do is you want to create a general counsel that would be on the same level as a general counsel that would work for the top fortune 500 companies in the world. How would they look at the contract? How would they respond? How would they advise you? and then you’re done, it’s literally about five to seven minutes. You can pin that as like one of your, your chats, your custom chat to be teased. now when you get an NDA and most NDAs are pretty standardized, but it’s good to read through them. Have Chat GPT do that instead, it’ll catch if there’s something a little weird in there and then that’s sort of your first layer. If you do need to escalate it to a person, then get the expensive lawyer involved.
[David] But you get a lot of it comes in asking the right question is prompting Chat GPT. And I think a lot of people, you know what you want. I mean, a lot of people are working with me and having me review their agreements. I use chat GPT and they say, well, I’ll use that too. Why do I need a higher consultant or attorney? it’s the knowledge that I bring in reviewing agreements is the questions to ask when looking at this. you and so that talk about that because I don’t want it’s not a simple panacea. It’s one of those things where you got to ask the right questions.
[Garrett] Correct. And I think the most valuable currency in the future will be those who can ask the best questions and you are hitting the nail on the head. When you get a terrible experience with ChatGPT, 100% of the time it’s because of the inputs. And so in this simple example, maybe you’re struggling with like, okay, well, how do I prompt this AI to get the best out of it? I struggle with that as well but you don’t have to sit down and think about it. Instead, you go back to AI and you ask the questions we’re asking. Hey, ChatGPT, I want to create a general counsel, but I want it to be Ivy League elite level, Fortune 500 company type of general counsel for my financial technology firm. I want you to write out a prompt for that, that I can copy and paste into my custom GPT to create the custom GPT. You don’t even have to think about it. All you have to do is know how to navigate the experience of building the Custom GPT. And if you’re not sure what question to ask it, then ask it that question. I’m not sure what questions to ask you. Give me three questions to help clarify what I’m trying to do. Ask three clarifying questions. I do that a lot. Have it ask me the clarified questions so it can really dial in what you’re looking for. But you don’t have to become a prompt expert. All you have to do is become really a communications expert.
[David] It’s really good.
[Garrett] Communicate back to it where you’re struggling, it’ll help you through that.
[David] So and it, yeah, you don’t have to come with it all. It’ll help you get there. That’s so real good. Another application that we talked about was accounts payable and accounts receivable. I mean, that is, that was brilliant. Talk about that and how your hand, how you’re using AI in that application.
[Garrett] Yeah, well, it was a couple of months ago, maybe three, our accounts payable, accounts receivable, I’ll call them like reporting sort of administrator left for another company and man, I loved working with her. She did so much and so hated to see her go. But when she left, we had an option. I had a choice to make. Do I hire someone else, spend four to six weeks to train them, get them up to speed or is what they’re doing. Like, is that something I can replicate with the technology that’s out there? A little bit of AI, a little bit of workflow automation, that kind of thing and so I went with the second option. And honestly, like the first couple of weeks was a little painful, just like training someone is like, just was, it wasn’t fun and you set it up and you’re like, great, it’s good to go and then you’re like, Oh, didn’t think about that scenario. And so it’s a little back and forth for a few weeks of that. But in my mind, I’m thinking I’d probably do the same thing if I hired someone too, right? And so what we did was for accounts payable, accounts receivable, so think like creating invoices. At Candid, we have a bunch of different, we’ll call them SKUs. So it’s not just like a user seat, but we have like credit reporting where we can monitor credits, like trigger leads. We have a point of sale, like that could be a different SKU and we have all these different components that we can offer as a service. And so it’s not as simple as like, 10, 100, a thousand users, someone charged them X amount per user per month. We have a couple dozen SKUs and like the different types of how each are handled in billing. So it’s a little complex and so with that, what I did was a lot of its workflow automation is a good amount of AI to help me build the workflow automation, but we have completely automated accounts payable and receivable when someone emails billing at Candid.inc. AI is handling that communication, has access to our accounts payable and accounts receivable software, has access to our customer success software. So it’s able to go in and answer really well, different questions that come in through billing and in reporting, this was one that blew me away. Because every month with our LOS partners, to think like Calix, Meridian Link, EnCompass, a lot of them, we have to generate a report, like a volume report, or like a revenue report and we take that report and then we go to the website, we do a form fill, and then we submit that report in and that was something like the person that had left the company was doing and right around the time, like this was just good timing. Who was it? Claude had announced a new product called Cowork. I’m not sure if you heard this, but this is sort of the next iteration of AI. It gives you a good insight. like, wonder where it’s going. This is where it’s going. Claude released Cowork. And think of Cowork as like a personal assistant who sits beside you at work and can navigate your computer in most of the same ways you can. So, Claude is part of the Anthropic family. Anthropic is one of the competitors of ChatGPT, just like Gemini, just like all these other different models and so Claude releases, and a few others have released something similar to it in the past, but it just didn’t really move the needle, to be honest. And so what you do is you install this as application on your desktop. And you need the chrome extension as well, because it literally can surf the web. How does it do that through a Chrome extension? And so I set this up and I put it the instructions and I’m like, hey, every month on the first of every month, I need you to go over here into our Salesforce instance. I need you to grab some data and then I need you to apply that data to this form fill for this LOS provider to submit on the first of every month. so this is the first time I’m ever using it. So I just sit back and I watch it to see like, You know, basically, is it going to break? And so it does that. It opens up Salesforce. It’s like, don’t forget to log in. I logged in. It pulls the data and then takes the data, opens up another tab in Chrome. goes to Chrome and it goes to this form field and it fills out the form. Well, I had, I had never personally filled out this form. So I just thought it was just the form, like, you know, like put in your name, put in your phone, put in your email and whatever else they need. So it gets to the bottom and I’m watching it. It gets to the bottom and it’s like, says, it looks like you need to submit an Excel spreadsheet as part of this form. And I’m like, man, like great. Now I’m actually going to have to do this on my own every month and then it says, essentially, no worries. I’ll create the spreadsheet for you, including the exact columns and tabs that you need on it, the data inside of it, and I’ll submit it. And I’m like, no way. And so I watched, it’s just like doing all these things. I have no idea what it’s doing, but it creates the Excel spreadsheet in real time. It nails the columns because the columns at the top have to be specific. So it nails the columns. I think there’s like seven or eight of them and then it pauses because I hadn’t told it to do any of this. So it paused and said, hey, review this to make sure it’s right. I looked at it. It nailed it. I was like, yeah, it’s 100 % right. And I said, submit it. So, it takes the spreadsheet. I don’t even know where the spreadsheet is. It’s just like in the cloud somewhere. It takes the spreadsheet, submits it to this page, and then stops again and says, do you want me to submit this? And I said, yeah, go for it. And it submitted it and the rest is history and so then I just told it, you just nailed this. I don’t even need to do this or hire someone to do it. So at the first of every month, I want you to do the exact same thing except don’t ask me to look at the spreadsheet and don’t ask me if you need to submit it, just do it. And for three months in a row now, it has submitted six different reports to six different LOS providers that they need to do the reporting on.
[David] Wow. You sit and looking at what a time saver that is also a cost saver. You have it doing it and as much as we love our humans that work with us and for us, it’s so consistently performing. It’s pretty amazing. I’m so excited to get into Claude and all of that, but let’s talk about how to be thoughtful with AI to produce the greatest ROI. You spent a lot of time really being thoughtful about it rather than emotionally reactive and I think that’s an important part of your makeup and why you’re having such success at it.
[Garrett] Yeah, I think it’s really natural. you kind of put, take off like the operations hat, put on maybe like a sales hat, like a lone originators hat. I think it’s pretty natural to see sort of the next cool technology innovation. We’ll call it a shiny toy and think, I gotta have that. But before looking at it, exploring it, signing up for it and implementing it, I think there’s some really important questions, very thoughtful ones to ask. Having a lot of discernment, let’s say that’s probably the best word to have, discernment, is this actually going to move the needle or is it just another piece I’m putting into a tech stack that is producing a lackluster ROI? And if you put an incredible tool on top of a lackluster tech stack, You’re not going to get any different response or results than you’re used to getting the past five or 10 or 15 years. The trick, and we talked about it before, but with AI, the inputs will determine the quality of your outputs. there’s, and a lot of mortgage executives are talking about this now and have known about the problem for years. It just wasn’t. It didn’t rise to a level high enough to care about too much. But in the mortgage technology space as a whole, and this goes for loan originators all the way to operations and beyond, there’s always been a problem of what they call data islands or data silos. And you know what? Like we just, integrated with it. We worked around it. We worked through it, but we never addressed the core issue, which was the data, I’m talking sales, fulfillment operations and beyond is spread across dozens of different desperate systems. And we are sold the idea of they integrate, but not really, let’s be honest. Data is everywhere. And so as a loan originator, as a micro example, if you think, you know, my clients look at a home value report over here, but all that data doesn’t communicate with my CRM, and my CRM doesn’t communicate all the data with my online reputational management platform, because they’re all different systems, then I try and layer AI on top of one of those and it sounds like an idiot because my clients looked at their home value report 19 times, but my AI is talking about them refinancing and really what they’re trying to do is buy another home and so that’s where you get into like in cells, especially that’s where you get into the, the walking away with that feeling of like, man, I’ve heard so many great things about AI. was a terrible result that it produced. And so you talk about like, I talk about like discernment. Where do you put AI right now where it makes the most sense to me, it’s nowhere near the relationship. It’s, you really start, if you want to figure out like perhaps.
[David] That’s really good. That’s really a good point to bring out.
[Garrett] Yeah, if you want to, if you want to sort of have sort of a litmus test, like, okay, I’m ready to deploy AI is so cool. It’s going to change my, my company. It’s going to change my organization. It’s going to change my team. Where’d start first, go as far away from the relationship as you can and work your way slowly toward it. So we talked about like accounts payable accounts, receive a general counsel, no relationships there. and, then as you work your way towards the relationship, think honestly, the last stop you should make is having AI directly engage with people. It’s still just not there because of the data problem, honestly. I think AI as a technology is there, but in the mortgage industry, we still have the data problem. There’s no way to give it the context because data is over 12 different systems. If today you could give it all access to all 12 different systems, It’s all in structured data. It’s somehow miraculously pulled all that together into one. And then you layered AI on top of it, you would get a really great result. But until you fix the underlying issue, which is the data silos issue, you’re not going to get a really a needle moving result out of AI.
[David] Do you think that’s coming though, based on what you’ve seen in the developments of it?
[Garrett] There’s literally billions of dollars being spent to solve this problem. This isn’t necessarily a mortgage specific problem. This is a company problem. But in the mortgage industry, it’s an unusually large problem because of the sort of technology buying behaviors that have happened in the last 30 years. No one was really thinking about consolidation. They were just thinking about bolting on little small bits here and there. And all of a sudden you have this big cluster that we call a tech stack. And so that’s one of the problems that, that Candid actually directly addressed this. And we weren’t even trying when Candid was founded about five years ago, AI wasn’t a thing. We weren’t talking about, you know, AI is coming in order to take full advantage of it. need your data in less places, not more. It just so happened that the vision of Candid was consolidation from a loan originator standpoint. A loan originator doesn’t need to be managing 17 different username and passwords to do their job. They need as few as possible. so the vision of Candid was everything from first time you talk to a lead point of sale, CRM, client retention management, online reputational management, websites, like the whole gamut, anything a loan originator needs for sales and marketing, all in one place, all one login, no integrations needed because all the tools are natively built. And by doing that, all of the data is in one place. That client who looks at their home value report, we know. Cross-reference with the reviews they left us, we know. Cross-reference with how many times they logged into their portal to complete their annual morjoo, like we know. So we can take all of that data, it in really good context, and now you’re getting a pretty cool response with AI.
[David] That’s pretty exciting. Let’s see. I’m amazed at how you’re using this AI agents. You’re using CoWork, Open Claw. And every time there’s a latest development, you seem to lock onto it. I know you just have an aptitude that I think listeners, when you’re listening to this, go, yeah, but he’s a tech guy. He understands this stuff. I think it just takes a curious mind and a willingness to play around with things. A lot of the stuff you come up with, man, maybe because you do think in a creative mode. As a, you know, you’re a musician, by the way, I’d love to have a podcast on that are a musician. Yeah. I mean, you are a musician. We should have you start by playing the guitar when you start in, you know, we can have you cranky. That would be pretty comfortable. Maybe that’s what we’ll do in the next one. Yeah. Well, we’ll try. We’ll see. We’ll see. the point of it is you’re utilizing all of this and in the most innovative ways. Let’s talk about AI agents and how are you using it? And I want to just talk about one of the things you were showing me one time. We were talking about going to the conference. I think it was the annual MBA. No, I’m not really going to go, but I’m to create it. I’m to create a booth like a fake booth and I was blown away with what you created. I mean, it’s these kinds of things where I think there’s so many opportunities to look at how to use these applications, these AI agents that are not being used or even thought about. That’s what you, that’s, that’s the creative side of your brain.
[Garrett] Yeah. I mean, we’ve talked about operations. We’ve talked about sales. We haven’t even talked about like marketing teams, but what are you talking about is marketing. The idea of being able to create a really cool looking booth at a conference that you’re not going through too, but you post the video on LinkedIn and you get a bunch of responses from it. Two years ago, that had been like a three month project and honestly, that took like about 60 minutes to like do it nowadays to create something like that. So there’s a tremendous opportunity for marketing teams as well. And I think the initial reaction in a lot of people has fear. Like, oh my gosh, I’m to be without a job. And I would say probably if you don’t adopt these amazing technologies, that’s nice, but, but, also like there’s a, there’s a story. I think it was back in the sixties when you wanted to make a call internationally, you had to call a person, the operator and the operator would literally like pull your call through a wire, plug in the wire to a switchboard. And now you’re connected to an international option to call and I think it was Bell who invented or really put into mass production, the electronic switchboard. Think of the electronic switchboard in the sixties and seventies as AI today. What happened? Like people freaked out. There are 800,000 switchboard operators in the United States back in those days and what do you think they were feeling? They were 100% feeling how people are today about AI and marketing departments and maybe loan originators and just operations as a whole. Like my job is toast and in the sixties and seventies, that actually was correct. There wasn’t like, you just need to be a better switchboard operator. Their job was to 800,000 people over about a five year period lost their job and you think, my gosh, that sounds terrible. But because of the electronic switchboard, what happened was it made international calls essentially free. They are free today and guess what happened? Over 5 million jobs were created in something that never existed before called a call center. So yes, job loss, but also an exponential job gain because the new technology came.
[David] And that’s what’s happening with this, we’re gonna have new jobs, but it’s for those who are thinking out of the mind.
[Garrett] But that AI agents is another fascinating category. I would say with all of this stuff, the sort of hype has always gotten a little bit ahead of what could actually happen. And now, now we’re sort of catching up to the hype and the hype sort of dying down a little bit. And so it’s not that the technology hasn’t has stopped evolving. Quite the contrary. Now you have AI actually building AI and so the speed and of deployment. Claude is an example. They released a new update like probably every two hours. I mean, just fascinating the possibilities. But with, so we mentioned Claude and CoWork, I would call that an AI agent. And that’s a personal AI agent that you can have. Whatever you’re doing that’s redundant and maybe not even redundant, but whatever you’re doing is taking a lot of time. Think reporting and stuff like that. It could probably handle. I wouldn’t give it access to PII for obvious reasons, but for all of the mundane stuff, Claude Cowork can absolutely handle. You mentioned Open Claw. This is a new one. It’s very hot topic right now. Think of Open Claw as sort of an unchecked, completely unrestrained version of CoWork. So, CoWork by Anthropic. Anthropic is known for being more thoughtful with their security and things of that nature. OpenClaw completely open source. If you give it your credit card and you say, spend, go max it out, it will do it.
[David] Yeah. Yeah, that’s scary. What what that can do it brings
[Garrett] You have to understand what you’re getting into before you get into it to your point. But the power of these, another really interesting one is perplexity. Perplexity really started out as think of like, you know, the AI meets Google, if you will. Really cool tool and you can go to perplexity.com. think it’s free. You can do some searches and see, but now they have something called computer, which is kind of perplexities tape on CoWork or Open Claw. But with perplexity, their computer, it can use any model. It’s not, so you have some model lock in with cowork, be right. It cowork uses claw, all the clods model. Perplexity, it’ll use ChatGPT, it’ll use claw, it’ll use Gemini. So whatever the task is that you’re asking it to do, it’ll think to itself, okay, I want to create a video, Claude’s not great at that. and I is pretty good. And so is ChatGPT. So I’m going to go to Gemini and ChatGPT and figure out which one is the best for this project. So now you’re getting sort of some cross large language model functionality out of, we’ll call it mainstream AI.
[David] Right. It’s almost like that’s the best definition of an agent out there because it’s looking at the various options that are there and it’s like airfares the old days we used to talk call to a travel agent. Yeah.
[Garrett] Yes. Yeah. Yeah, exactly. But back to discernment, when it comes to marketing, you’re like, what should we sort of tackle first in our marketing department? I would say it’s really easy to tell. But if you think like, what’s the hardest piece of marketing to create, know, video and images are really still difficult to create with AI. That’s where I think having a graphic designer still maybe one who uses AI to shortcut the process is still really smart. But what’s, what’s a marketing type that is pretty easy to replace now, newsletters and blocks and not just replace. say replace and it’s a very like neutral word, significantly enhanced. We release, we call it AI newsletters, but on Candid, we really say AI newsletters. And the problem we were trying to solve for was we love newsletters, but we hate national generic fill in with a couple of merge field newsletters. I consider that noise at this point because of where technology is. So the problem you’re trying to solve is how do we do newsletters but make it personal to the person, not the market even, not like Tennessee, not Nashville. I mean, to the realtor who’s working in East Nashville who loves to renovate historic homes and flip them. How do we make a newsletter personal to that?
[David] See, I mean, we were, yeah, yeah. I mean, that’s the value of what you’re talking about. Give that, go into that example really well, because we spent some time talking about that one other time. I really want to have, that is when you can send out.
[Garrett] I was blown away with the results and my bar is pretty high, David. It takes a lot to impress me. I was blown away with the results. I’m reading through these newsletters. I’m reading through a newsletter of a real estate agent in Birmingham, Alabama. Never been. Again, it all has to do with the prompt. How are you setting up this newsletter? How are you prompting? Also, how are you delivering it? You can’t deliver a million unique newsletters and expect not to get sunk with cost. So delivery is just as important as well. But think of this like the example of that. was reading through a newsletter of a realtor in Birmingham. I have no idea about the Birmingham market as a loan originator. 95% of my stuff is in Nashville or middle Tennessee, but I’m reading through this newsletter and the way that you want to prompt it is you want to think beyond a newsletter, right? So, you start off with your very market specific information to create some legitimacy. But then you want to move into business tips for the real estate agent in the voice of one of the leading realtor coaches in the country. Pick a name, doesn’t matter. If they have a lot of content online, you can put it in their voice and then move into maybe a call to action or something like that. But this newsletter to this realtor in Birmingham, it goes into the business tips and it talks about two different price points in their market aand they’re only about 20 or $30,000 apart. But it recognized that this realtor was listing heavy, so they love to do a lot of listings. That was their business model. They recognized that and so the business tips were written for a Birmingham realtor who’s listing heavy. And it even went into a script they can use in their next listing appointment when the seller wanted to list their home higher than they should. And it broke it down. It knew the number that they could list their home at and it would move in 35 to 45 days. And if they went over this number, it knew that if they went over the number, the home would sit for 90 days and it worked that into the script. I mean, it was just mind blowing. This is a newsletter. So, you can think about like the level of value that offers compared with what we’re used to in newsletters. And that is a really good example of how to use AI. top to bottom. You think about like open rates, you think about the level of value delivering as a lender partner. I mean, just really mind blowing stuff, but that’s an example of like when you think about marketing as a whole, what do you tackle first? You want to, you want to tackle this stuff that you can really move the needle. it’s not too difficult. There is some logistics you have to think about and, and you want to leave sort of like video and maybe, images and things like that. Leave that for another day until you’ve really honed in on newsletters and blogs. Blogs is another one. We know with large language models, everyone wants to be the lender that ChatGPT mentions. Right? Who’s the best lender in Los Angeles? And you want your name to appear preferably with a nice headshot. But how do you, how do you get that? know that large language models are looking for very recent hyper local content. They consider you an expert in your market. If you’re constantly posting super high hyper local type of content, think blogs. But again, like if I’m, if I’m a mortgage executive, company and I have 500 LOs. Well, I’m essentially saying you need to provide one, two, maybe three times a month, a hyper local blog for every one of your LOs. That’s crazy. Can you imagine the copyright department? But back to what we’re doing with newsletters, we released AI blogs and it’s the same concept you pick out, it’s part of our ecosystem. But you pick, you know, do I want this monthly? Don’t want a couple of times a month. And it will go, it’ll research the top three things, the top three things that are most talked about in the real estate world in that market on social media. So it knows what are people talking about? What’s going viral? What’s getting the most mentions? It knows the top three. It’ll pick what it’s thinking is the most relevant and then I’ll write an entire blog from it, insert a couple of relevant images, put the hashtags, put the title, put the date published and done. Completely automated.
[David] And you’re offering this inside of Candid right now.
[Garrett] Yeah, we just released it a couple of weeks ago. It’s in, in beta. And I have been again, like really intrigued with the result. I mean, it’s just, it, it takes what again, a blog, what is it right now? It’s a national generic sort of merge field in type of, you know, the five most common types of mortgages, but large language models aren’t attracted to that. What they are attracted to is the significant tax hike that just happened in Davidson County, Tennessee, and an entire blog about that. Because then that large language model looks like it knows exactly what’s going on. And so in turn, loan officers can piggyback off that, who’s the best lender in my neighborhood? Well, the one who’s posting consistent, hyper local content.
[David] Yeah. Man. It’s so fun to see, these developments and see what it could do for us. it, takes an old man like me just wants, makes an old man like me want to stay involved, stay involved in business because it’s so we’re learning so much. It’s fun to have you here, Garrett. How can people learn more about you and this amazing product you’ve created?
[Garrett] Yeah, check, feel free to connect with me on LinkedIn. Shoot me an email, Garrett at Candid.inc or it’s Candid.inc.inc on the web. I’m on LinkedIn, ⁓ shoot me an email. Love connecting with people. I love sharing great ideas. There’s a lot of amazing opportunities out there that can really impact a loan originator’s life. And people are working at mortgage companies and it’s such an exciting time.
[David] Yeah. Very exciting time. Thank you so much, Garrett, for taking time to be with us today again. And congratulations on your success. Check out candid.inc. I N C it’s a powerful product. Part that I like it is being adopted by top loan originators. You, I think you just had the number one loan originator in the United States.
[Garrett] David, no one knows that yet. Here we go again. No, that’s fantastic. It’s signed signed yesterday or the day before, but the number one loan originator in the U.S. is now a Candid customer and last month we signed up CMG and Lower is another great customer as well. We have, it’s really exciting time and it’s great affirmation of what we’ve been building the last five years. I think it’s exactly what the mortgage industry needs to move the needle forward.
[David] Yeah, that is it is. And it’s affordable. That’s the best part. Created by a brilliant guy. And it’s a guy who’s originating himself still to this day. Good stuff. I love it. So good to have you here, Friend. Appreciate you. Thank you.
[Garrett] Thanks, David.