But now we're spending a lot more time with the clients, >> making sure we understand their needs. >> Yeah. >> And uh a lot less time doing paperwork. >> Yeah. >> Right. So we can And you know, we're able to package better deals together by using the AI. >> It's always the same. >> Correct. >> Correct. That doesn't require decision making. An AI agent is really powerful when it comes to decision making. If if a decision

needs to be made AI agent if no decision needs to be made and it's always the same code. How much time could be spent could be saved if you had this sort of software right now in your hands? >> I spent about 45 minutes to an hour with each client just discussing pricing. It's so so with each client and at least and that's over the loan process. You got to know how to ask a question. >>

Because the answers are out there. >> Yeah. >> You just got to know how to ask a question. >> Yeah. >> And so, you know, I, you know, the Bible says, "Ask and you shall receive, right?" I think with AI, you could ask just about anything. You can receive just about anything. You just need to know what questions to ask. Welcome to another episode of Pick Up the Phone podcast. I am your host, Toshu Jiannis. I'm

the founder of Gets You.AI. I have the first emotionally intelligent voice AI for real estate investors and real estate mortgage lenders. Uh it's not artificial intelligence, it's emotional intelligence. Today's guest is Josh Farard. Josh Farard is the owner of FNF Mortgage. >> Yes. First Nation Financial Corp. >> for First Nation Financial Corp. And today we're going to be talking a lot about incorporating AI into the mortgage lending brokerage industry. So Josh, thank you for being here,

man. >> Thank you. Thank you for having me on. >> Absolutely. Absolutely. So um man, why don't we get started by just kind of uh we've already done a podcast before, so anyone that's watching, I'll I'll include the uh show links to the first one. If anyone wants to get to know you and your story, they can go and watch that video. Um, but in this in this episode, what I really want to talk about is

AI in particular. Um, and specifically how people can use AI to incorporate um different AI tools into their business and essentially start start working a lot more effectively, productively, and faster than ever before. >> Absolutely. >> Yeah. >> Yeah. It's it's everything right now. Everything's moving with AI in the direction of AI. Everything we do as even as mortgage brokers has >> completely the dynamic has changed drastically um in regards to you know how much time

how much energy uh how much stuff can be automated um the amount of time that we need to spend putting a deal together >> is um substantially less than the time we have to actually spend with the client. Yeah. >> So, that transition has always been the exact opposite, but now we're spending a lot more time with the clients, >> making sure we understand their needs, >> and uh a lot less time doing paperwork. >> Yeah.

>> Right. So, we can and you know, we're able to package better deals together by using the AI. >> Yeah. >> And I'm really excited to like actually get into it in in terms of learning the actual workflows. I think whenever you talk about AI, um, I I think you need to start thinking in terms of workflows, >> right? And so what I'd like to do in this episode is break down some of the workflows that

you're having in your business. And we're already working together, right? So you hired our company. We are building out your GoHigh level. >> Um, so we're building out your GoHigh level. uh >> redoing the whole thing, >> redoing everything from um you know custom fields to pipeline stages um to different workflows and automations that are built inside of Gohigh level. >> Yeah. >> So I think that all of that's extremely exciting um >> and implementing the

AI >> and emotional AI >> well implementing uh emotionally intelligent voice AI. So, I think uh my biggest breakthrough was when I saw that most voice AI sound monotonic. >> Yes. Horrible. >> They sound horrible. >> Yeah. >> Hello, this is blah blah blah blah. And it's completely monotonic. >> It sounds like a computer. It makes you want to shoot yourself. >> Yeah. It sounds >> Why am I talking to a computer again? >> It sounds

like a robot. No one wants to talk to a robot. So when I stumbled across some technology that has voice that can uh that can materially change or dynamically change its tonality based on the users's emotions. That's when I realized that this is something special. >> Yeah. >> And I went all in and I developed it and we have uh something out for the market that uh >> you're still developing it. >> Well, >> it gets

better and better daily. Well, it's it's already it's already operational. We have um we have about 12 clients right now and it is pumping appointments like crazy. >> Excellent. I am 13. >> You are the 13th. Yeah, >> 13 is my lucky number. So, >> yeah, there you go. >> Good. Good deal. So, let's talk about um let's talk about workflows, man. Let's talk about um let's first let's start with your business. Would you be able

to would you mind breaking down and I think this would be really exciting for anyone that's watching this. Like >> this is my thought process after building a SAS an entire SAS platform. See a lot of >> a lot of companies out there, a lot of people that are promoting different AI things are using something called N8N. Okay. And this is something that anyone can go and look up. It's basically um it's basically glorified workflows like

a glorified kind of sapier. Are you familiar with sapier? >> No. >> I'm not the tech guy. I'll come to you. >> Absolutely. I got you. So sapier. Sapier and N8N are is this technology that simplifies or not simplifies but it's like connectors between different tools that normally wouldn't be able to talk to each other and they talk to each other based on APIs and web hooks. >> Okay. >> So think of like what I just

said is basically just computer talk, right? It's just how computers talk. >> Yeah. >> Okay. So but in order to get to that point, first you need to understand what part of the business needs to be automated. >> Okay. >> Right. And then even to go further on that, not only what part of the business needs to be automated, but what part of the business needs to be coded out and what part of the business can

be developed or automated using an AI agent. So a lot of a lot of people are like, have you heard of Open Claw? >> Yes, absolutely. >> Have you ventured into it at all? >> No, we haven't gotten into it. >> Okay. I I I developed my my uh built up my open claw. It's uh open source. Um there's a lot of security vulnerabilities with it. A ton. Um it so many things that could could go

wrong with uh with OpenClaw. Um so I think whenever Claude or Anthropic came out with AI agents that are managed on their servers, they're a lot more safe and secure, also a little bit more expensive. Um which is super important in our line of work. The security is is we're dealing with people's private information. Right. >> Right. >> So we have to be very vigilant about security and we use special high level encryptions just to just

to get just to be able to take somebody a picture of the driver's license, you know. >> So there's a lot of that that's super important. >> Yeah. So open cloud definitely wouldn't work out at all for you. >> No. >> We have to have heavy heavy encryption just to be able to take somebody's driver's license in. Yeah. you know, it's it's a big deal. >> It's it's a sounds like a pretty huge deal. So, >>

yeah. >> Um Josh, can you tell me a little bit about your business, man? How does uh let let's break down your your business in terms of how uh leads come to you, you know, how how you operate through them and then um and then we'll talk about what parts of your business. I know, you know, we're building out your GoHigh level. So obviously your marketing, your lead flow, your lead intake, um automations with sales uh

are going to be completely automated using GoHigh level and also the voice AI is going to be calling a lot of folks >> especially followup followup that's going to be huge with the voice AI. >> Yeah. Yeah. Yeah. Yeah. So, we'll we'll talk about all that and then we'll go deeper into it and then talk a lot about what other parts can be automated and then I'll talk about um I'll talk about what needs to be

automated with software versus with an AI agent and I'll tell you the difference why software is, let's say there's a process in your business that is always the exact same way. We take in the file. We fill out this information on this form. We hit submit. Something simple, right? >> Yeah. >> If something >> We have a lot of that. >> You have a lot of that. So those kinds of processes is something that doesn't change.

It's always the same. >> Correct. >> Correct. That doesn't require decision making. An AI agent is really powerful when it comes to decision making. If if a decision needs to be made, AI agent if no decision needs to be made and it's always the same code. >> Yeah. >> That should be everyone that's watching at home that should be kind of like their thought process. Right. >> Right. >> And the reason why is again AI agent

expensive code nothing. >> Yeah. >> You do it one time and that's it. >> Yeah. >> You run it on your server and that's it. And you can do it all with cloud code. You can do it with other tools. >> There's something called vibe coding. It's a whole ordeal. We we'll get into all that. So let's break down your business, bro. >> So let's talk about let's start off with the leads, right? And how do

we generate leads and how do we do the intake of each lead, right? >> That part of it is >> really has been the most difficult part, right? Uh our old business model when I first started doing loans was I mean we would buy leads by the dozen like just you know regular leads, information,formational leads like title leads and we would you know just cocoa. We had 60 people in the office and everybody was just dialing

all day long, >> right? >> In today's market, it's completely different. First of all, you can't just dial anybody's phone number. Yeah. >> Um >> there's so many regulations and restrictions that just don't allow us to get into that. But the main the main thing for us to generate leads is that we have to reach out to clients, right? So the clients need to see an advertisement and come to us. >> Mhm. Otherwise, we don't have

the ability to call or text or anything like that. They have to have opted in, right? Yeah. >> So, what we're doing now is creating any type of plat on any platform available. Creating a funnel for them to be able to, hey, click on this, learn more. This is what I'm interested here. This is what this is an area of conversation that I'm interested in. We're going to retarget you based on that. So, you can see

our ads and from all different types of platforms, we're bringing in leads. So you can go Facebook, Instagram, Google ads, YouTube, uh, Tik Tok. We're everywhere and all we're doing is going out to people and and on each platform, you have to have a whole other campaign set up that caters to that specific platform's guidelines, right? And and to get the best results from each one of those those platforms. So, it's been a pretty difficult process

getting the leads together and then figuring out how to get them into our system, which is where you've come in right now, you know. um all of these imagine having like five or six different platforms where you're getting information from and you have no home for them all to go to one solid home so it can lay out leads you know for everybody all the employees and all. >> Yeah. Yeah. Yeah. I think um having that

central hub of lead intake is I mean it's crucial bro you know huge. >> Not only that but I think what that adds is the ability to track where leads are coming from. >> Yes. And then you could have uh different key KPIs. KPIs are key performance indicators. So you want to have key performance indicators because what gets measured starts growing. >> Yes. >> Right. Where energy uh goes, what is it? Where where focus goes, energy

flows. And so you need to focus on the numbers that are working so you can pour more money into that. Also, it gives you the ability to scale. Like if you don't have all those KPIs, you're not going to know where to which which platform is giving you the mo the best results. So you say to yourself, "Hey, let me throw another I don't know $100 there or another $1,000 there and let's see how it comes

out, you know?" >> Yeah. >> So that's a big part of it. >> Absolutely. >> Okay. So you have different funnels. >> Yeah. >> Right. And so the funnels come in and now they're going to be coming into your GoHigh level. We'll have different automations there. Um, one of the my one of my favorite automations is speed to lead. Yes. >> So, someone uh fills out a form. >> Statistically speaking, most people within 5 minutes of

filling out a form will forget >> Yeah. >> that they filled out a form. >> Yeah. >> Within 5 minutes. >> So, that means that if you don't call them within those five minutes, ideally you want to call them maybe within 2 minutes. You know, I would, you know, I would test out, we'll test out like calling them between instantly or 2 minutes. I think that'd be kind of like the sweet spot. >> Yeah. >> Also,

it depends on the time of day, right? >> It depends on time of day there are TCPA laws. So, if uh I believe uh TCPA doesn't allow uh AI calling after 8:00 p.m. >> Yeah. So, if it's after 8 PM, uh, my software has a globalwide blockage that doesn't allow any sort of phone calls after 8 PM. You know, >> for us, the funny thing is that most of our leads come in in the evening when

guys are doom scrolling the internet and, you know, like women are doom scrolling. They they they come across our leads and, you know, the information and they're like, "Oh my god." You know, and that's when we get a lot of our leads throughout the day. It doesn't happen too often, but we do we do get quite a few throughout the day >> through our Google ads actually, which is really great. >> Yeah. >> Yeah. That's surprising.

>> I'm pretty sure I a text a sing a a simple text could be sent out whenever they fill out a form. >> Yeah. >> Yeah. Absolutely. >> So, >> but I I would I don't know if I would send the text after >> either way. Not even after that. Okay. I mean, email definitely email. >> Definitely an email and a follow-up text the following morning. >> But the technology handles all of that. That's what the

best part about it is. >> Yeah. Absolutely. >> Yeah. >> So, all of that can be automated inside of GoHigh level um and also with uh get you.ai. Let's um let's move on after we get the lead. What happens after that? >> So, after we get the lead um back to the words speed to lead, you know, we got to make a call. We got to get people on the line. Um and then we convert them.

We find out what their wants are, what their needs are, what their what they're looking to do, what their focus is, you know, what what their what their two year, three year, five year goals are with that specific asset that they're trying to refinance or purchase or or whatever it may be, >> you know. >> So, that's our entire focus is let's figure out what the client needs and what the client wants and how we could

service them. >> Yeah. >> Right. So, that's that's that's phase two, right? >> Yeah. >> From that point, um it gets we're doing intake, right? Now we're doing an full intake of the client. Um we have online systems that we use right to take applications. Uh we either do one of two things. We either log in and create the account for the client >> Mhm. >> in our system online and then go through the loan application

over the phone with them or um you know for some of the clients that you know uh want to want to do everything themselves or as much as they can by themselves. Yeah. they they just go online and do the applications themselves. >> Okay. >> So, um they set up their accounts. The one thing we don't do that's very different than most companies is we don't we don't start with a credit pool. >> Yeah. >> Right.

Um our our pools are hards and I don't want our clients having those issues down the line. So, we wait until we've received all of their documentation to even run a credit report. >> Okay. >> Yeah. We want to make sure the client outside of the credit report the client's viable because most people know what their credit is. >> Yeah. especially you know our primary client base are investors and those those investors have a very good

grasp. >> So normally who's responsible for collecting the documents right now? >> Right now there's online system. >> Okay. >> And uh our our VAS are the ones who are following up to make sure we got all the documents. >> Okay. >> When it does finally pass over to processing processing follows up to make sure that they get the documents. So it might be something that you know in an updated bank statement or an updated payub

or whatever it may be the the processing department follows up on those documents. >> Okay. >> Yeah. >> And how are they normally being reached out to? Is it by text? Is it by call? >> I mean we do everything. All right. We're emailing, we're texting, we're calling. We're calling again. We're texting again. We're emailing again. We're kind of all over the place. And we don't we don't we're relentless. We don't stop. >> Yeah. >> I

got you. >> But that's the way, you know, that's the way we get it. You know, it's the same idea of retargeting. >> Mhm. >> Um and so like if a lead dies like in the if a lead dies in the phase from a lead to intake, right? Um we let it sit for a week, two weeks, right? And then we retarget that same client over and over and over again until we get to go away.

>> Yeah. >> Yeah. Or you convert them. >> Yeah. Or we convert them. >> Yeah. Okay, cool. So the document collection process seems like um do do you feel like that process could be automated maybe with an AI agent? >> It is possible. It is possible. Human nature is an issue, >> right? Uh because people >> a lot of the clients say, "Hey, I sent that in. I sent that in." You're like, "Guys, I don't brother,

I don't have it. We got to here's a copy of your file. You have a copy. We have a link to your drive. The whole nine just take a look at it. look at the system, you didn't upload that document, >> right? >> You know, and then they're like, "Oh, I want to email it to you." And a lot of the times I'm very hesitant to even take an email. I was like, "Look, I really want

you to stick to the format so everything could be secure. If you email it to me, I'm still going to upload it to that stuff." Yeah. >> You know, so yeah. >> Okay. So, I I mean, it kind of sounds like it could be automated either way. >> I think it could be. The intake process could be automated, but >> the the user needs to be the borrower. The user needs to be compliant, right? >> Complant

and >> in the sense that they're willing to do that, you know, willing to use the system. >> Mhm. >> Does that make sense? >> But the AI can do the followup. >> Yeah. >> Can most definitely do the followup. >> Okay. I mean, man, you'd be surprised. Like >> sometimes I try to trip up the AI and I I end up being the one that gets tripped up by the AI. It is powerful. >> Yeah.

>> I mean, it it just like it just stays on track always. It doesn't veer off the goal. It knows how to handle object objections extremely effectively. I mean, you you can try to throw a curveball at it and say just something completely outlandish and it'll like say something like brushing it off and then ask you a question. You're like, >> shoots right back in >> and then you're like, "Wait, what happened?" it the the the

programming on uh these AI agents are pretty powerful. >> It's removing the sales out of the salesperson. >> Yeah. Yeah. Yeah. It's pretty powerful. >> Yeah. >> So, uh maybe like a document collection agent could even be >> Yeah. >> incorporated there. >> Yeah. Yeah. >> Yeah. >> You know, some sort of you know the the the good thing about the software is that even if I'm not calling the client every day, it's updating them on

what's going on. Yeah. >> They got an idea of what we're looking at, what we're doing, how it's working, all that stuff. >> Yeah. Absolutely. So, let me break down a little bit real quick before we start going into like different AI agents that you can build. >> Um, what needs to happen here is Gohigh levels software, right? So, it's a it's an infrastructure already that's completely been built out. But when you're talking about something like

uh something like creating AI agents, um these AI agents need to be kicked off by us, call it an event. So when a person submits a form and then they go through that process and then who calls them? Is it you? Is it someone else on your team? >> It's either I'm calling them. Generally, it's it's the the VAS are the ones making the initial phone call and setting up a an appointment, making sure they get

like the basic needs done, the basic questions done, so that when we get on the call, when I get on a call, right, we're out there trying to find solutions to the issue at hand. Yeah. >> Right. whatever the the mortgage problem could be, whether it's, you know, my interest rate is too high, I need some cash out, I want to buy another property, um, whatever it is, our entire focus is to find a solution for

the problem that we already know exists. Yeah. >> Right. So that the process can be much more streamlined and faster. But it takes a lot of um I don't want to say massaging but it takes a lot you need you need to understand the the landscape of the lending business to be able to place a loan correctly. >> Right. A lot of the times um 90% of the times the loan does not fit into the box.

Okay. 90% of the loans that come to us I should say. >> Yeah. >> Right. Are not loans that fit in the box. It's people have gotten rejected from like regular invest investment banks or they've gotten rejected from um you know uh Rocket Mortgage and they couldn't put it together. I mean we've done deals, we've done loans where you know it went through the Rocket underwriting system which is pretty much it kind of handles itself, right?

>> Um and it's come back to us and we've >> sold the loan, we've underwritten the loan ourselves and then presented it to Rocket Mortgage and the loan's been approved. >> Got it. >> Right. So some of the stuff is, you know, a lot of that portion of it cannot be automated, right? >> Um, but the rest of it can. The rest of it can. >> Yeah. Okay, cool. So I, you know, I know you're not

very technical, but I think I I think it'd be really important for you to at least have a surface level understanding of how things will work. So >> the way that I see it is, let's say it is Gohan level, right? This is where your lead is. And you've seen already the different stages in you you grab and d drop drop a contact and first it's a new lead then it's uh you know lead intake >>

um >> followup all yeah all of those right >> ones. Yeah. >> Okay. So let's say there's one that uh let's call it maybe a document collection stage, right? We can we can do some sort of automation that says if a lead is in the document collection stage for more than a day, kick off this automation. It'll fire a web hook that will send to get you.ai that will call the the lead and say, "Hey, it's

been a day." Um, we were trying to collect your documents. Is there anything holding you back from you submitting the documents into the portal? >> Yeah, absolutely. >> Right. And then after the call, what happens is after the call, it takes all these notes and it saves it inside of the platform inside of gets you.AI and it sends it via API back to GoHigh level. So then in your contact, you're going to have all of the

information on the right side. >> The whole log of everything that's happened is going to be >> the transcription. >> Oh wow. the summary, the action items, the next steps, everything is going to be right there on the right side. And it'll uh it'll give you and anyone else that's using go high level >> a full a full kind of bird's eye view of that contact just by looking at that note section, everything that's happening. And

then obviously the goal is that the person now goes and submits their documents and then we could have another automation if if three days you know passed by and they still don't upload the documents kick off the automation again send the web hook call the person >> what we should do is try to figure out how we can make this uh you know because our intake form is that that you know that all the documents go

to >> somehow maybe the AI can speak with that and be like yo hey these are the five things that you're missing. You got the other eight in, but you have five more that you got to get in for us. >> Yeah. >> Right. So, and then one of the other things that I think we need to actually add to it is because the different types of loans have different documentations that that is needed for each

one. Right. >> So, one you'll need a W2 pay and tax returns. Another one you're going to need um just a lease agreement and you know credit report and a couple other things for the DSCR loans >> which are fantastic and easy, right? >> And they don't care about your tax returns. they care about your credit score, the property's income, right? U which is great. It's helping out a lot of investors. And then what we can

do is, you know, kind of use that information >> um you know, and to have them or at least use the systems to speak to each other so the AI can say, "Well, I know what's missing. You got to send me these things. Don't forget." >> Yeah. Yeah. And so the beautiful thing when you're using AI is that >> you can have different stages in in the lead cycle. Yeah. >> And have agents that are responsible

for their particular uh stage in the life cycle of that client. And then each one is supposed to communicate with the next agent. So the lead intake agent will take all the information and then communicate that over to the document collection agent that's going to say, "Okay, well we're missing this, this, and that." send it to the next person so that so that the next agent has full context as far as where that where that lead

is in terms of documentation, have they filled out the form, have they filled out the application, etc., etc. Does that make sense? >> Yeah, absolutely. >> Yeah. So, communication between agents is extremely possible and that's something that just needs to be coded in. >> Absolutely. Yeah. you know, I mean, even with what's going on, like I we're doing we're doing less volume of loans right now, but higher dollar amounts is what we're seeing. And um the

client databases are are are a mess, right? Uh overall, when it comes to the the the higher volume, uh we're able to keep our databases in intact because, you know, we're doing we're doing high dollar volume, but we're not doing, you know, high volume loans. >> You know what I'm saying? Um, so that's that's a big part of it for us because you know we're still is I mean we're still now we're just like 10 agents,

you know. Um, but we're hoping we're hoping with this, you know, implementing the AI and setting up our infrastructure, which is what we're discussing right now, that we could we could pick up another five to 10 agents before before the end of the year. >> Yeah. >> Yeah. That's our focus. >> Nice. That's a great goal. >> Need more MLOS's. >> Absolutely. Absolutely. Okay. So, um, we spoke a little bit about, uh, lead intake document collection.

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phone number is 936-4428486. Natalie Bass with Black Label title. >> All right. So, I want to hear about your uh your the next step in the process. Uh the lead intake, document collection. >> Yeah. >> What is the next step? Loan application. >> Uh lead intake, document collection. No, the application comes with the the doc collection. Okay. So, um it's processing that that now it goes off to the our in-house processing team. >> Is that like

an underwriter? >> Yeah. >> Okay. >> Our underwriters in house processing. It goes off to them and then from there uh they are the ones who you know load every loan into our um official system. It's we use a system called encompass. um we have to use that because we we do or some of our some of the loans that we do are a little bit more integrated and it requires an elevated platform to be able

to use it. Um there's deficiencies in the other ones that um make it impossible to use for commercial use, right? Um so so we do a lot of commercial loans as well. So the so we go into the the loan application process, right? M >> and then the loan submission that's what I call that the underwriting and loan submission that's the next step right >> that needs to be reviewed by a pro right to understand what's

going on what the paperwork is calculate the income correctly make sure it drives with what the lender would calculate it for whether we're doing a full documentation loan 12-month bank statement loan or you know just calculating 1099s and expenses schedule C check where the depreciation is all this fun stuff that goes on in the processing Yeah. >> Cannot be done without without an eye. Right. >> Yeah. >> So like you have to like pull tax transcripts

and stuff like that to be able to make it work. But even then it doesn't work. >> Yeah. >> Right. >> So is this the part that you're responsible for primarily? >> This is where I do most of the work. Yeah. >> Right. This is where I I start off with the initial client um the client conversation and the solution session, right? Figuring out that needs that needs a meeting. And then this is where I come

in. Uh this is probably one of the most difficult parts of doing a loan. Yeah, >> getting the lead is tough to set up, but once the leads are in, that's that's kind of the, you know, >> you find out the client, you know what they need, you get the paperwork together, but presenting the right paperwork to the lender for each loan is extremely difficult. There's some lenders that, for example, on a full dock loan, you

don't need to send the tax returns. >> Mhm. >> Right. They just want W2s. Well, if you're just doing W2s, then what? You know, you don't even want to have the tax returns in the file. >> Yeah. Right? Because all it's going to do is ruin your loan. Right? So, you pull the tax returns out of the file and you just submit without, you know, and the lender is not asking for anything else. That's what they

want and that's what we're giving them. Exactly what we're giving them. >> You lost me. >> Okay. So, there's certain there's certain items that the reason the processing needs to be done by hand, right? And it's not something that we could sub out is because some of the some of the items that are supposed to be submitted with a loan, right? Um there's some items that are supposed to be submitted with the loan depending on the

different loan type. Yeah. Right. And then they're documents that you're just not supposed to send in. Okay. >> Generally speaking, when you're doing a fully documented loan, right, they're asking for payubs, W2s, year-end payubs, tax returns, right? 1099 forms, whatever it may be, K1s that come to your personal, right, from other entities that you want. But but sometimes the lender doesn't want all of those documents. >> Okay. >> They only want the W2 and the payubs.

>> Yeah. >> So we only send the W2 and the pay stops >> even though you have everything else. >> The guideline for that one specifically is designed for the guy who makes money but he hasn't filed tax returns in 2 years. >> Yeah. >> Right. So that's what that loan program is designed for. So the processor needs to sit and be the person along with me that makes that determination and submits that specific loan. >>

Okay. >> Yeah. >> So that that I guess this is kind of like where the the loan broker part comes in. Right. Right. >> It's kind of dictating >> all right. We have this information from the client, >> but we're not going to just take all that information raw and just like submit it to every single lender out there. >> Correct. >> You're going to pick and choose what files you need. >> Yes. Okay. Got it.

Got it. >> Yes. And that's where the automation um falls apart cuz automation can't decide. The automation could you could code it. I think you could put it together to make the right decision if this then that right that type of scenario. But I don't think it's going to allow you I don't think it's going to give you the ability to you know it's that one's going to be a very very tough build. I I think

that with enough data it can be built meaning with enough scenarios right yeah now that's not to say that that's it's you know the once you build it you can just set it and forget it >> you know I think more more importantly what you need to understand about working with AI is that >> AI just makes things faster and so because it makes things faster it surfaces problems faster >> and so a lot of things

can start breaking even quicker, which in my opinion, you know, I I see that as a good thing, right? Let me start breaking things apart faster so I can fix them and then get to a point where I'm constantly now improving now what I've built so it can get better and better and better over time. >> Yeah. >> And not even just better, but I you know um whenever so I have you know my SAS platform,

>> I look at the reliability of the platform, right? And so the goal is to every day have my uh percentage of reliability just go up higher and higher, you know, from 90 95% 99% is really the goal that you always want to be at. And uh even most softwares out there never say never claim 100% reliability because inherently code has issues. Yeah. >> It has bugs. It has things that are breaking on in the back

end or different things that are firing off that can break. But in theory, isn't it supposed to like get to a point where it's perfect? >> You know, I I think that um even AI I mean even AI makes mistakes. You know, the like most AI platforms right now whenever you log on at the very bottom it'll have a disclosure. This is AI and AI can make mistakes. >> Don't don't believe what like don't believe don't

take it as face value. Don't believe it 100%. >> But the whole idea is that it's constantly learning, right? And it's constantly building itself up and higher and better. Yeah. >> Right. I mean, just like a human, >> right? >> But but that would like the claim to that would be that humans are perfect then too, right? >> We are. I am absolutely perfect. I don't know about everybody else. >> You But that aside, you know,

but that aside, >> we cannot all be Josh Farard. >> We cannot We cannot, you know, my wife seems to love it and hate it at the same time, but you know, we can't all be Josh fart. >> Yeah. Yeah. If your wife loves it and hates it at the same time, does not sound like perfection. the truth comes out. So, inherently there's going to be issues in in code and so >> yeah, >> the goal

is always to just continuously improve the process to make it more effective. >> Yeah. >> More efficient. Um what happens after this decision making tree of getting finding out who to submit the loan to? >> So here here's another part of that that makes it a little bit difficult to automate, right? is different lenders have different guidelines, different programs. Uh for example, one of the lenders we work with um when we're doing a short-term rental doesn't

require for you to have short-term rental history on the property >> to be able to fund the loan, >> right? They need a short-term rental survey that'll show that the property will be able to make that much rent. >> Right? This is just one example. >> So, one says this, the other says that. Well, you can't qualify on this one, right? But you can qualify on this one. So, what are you going to do? You're going

to submit the loan to the right lender, the one on the right, not the one on the left, because that one's guidelines are more lax. The problem is, okay, for each lender with shifting guidelines, you to be able to have a system that decides which lender you send it to for you, you'd have to be constantly every time there's a guideline change uploading new conditions. You'd have to have entire team of, you know, uh, software engineers

just to be able to upload that information all the time. Why is it so complex to get that information? >> Because it's constantly changing, right? Constantly changing. >> Where do you normally normally where do you normally get that information from? >> From the lenders. They give us their guidelines. >> And how do how does a lender send you the guidelines? >> So, they have them posted online. Okay. >> Okay. Easy. >> Some >> Okay. Some >>

some have them post them online. Others that do not >> email. >> They can email you copies of the guidelines. >> Okay. However, um guideline guidelines, understanding guidelines and how to work around the requirements or lack of requirements is what makes it possible for you to get deals done. You really have to know what's going on there. And the AI can figure it out for you, right? But they they I can't submit the loan to all

of those lenders unless you have okay Jose developed a system right which will make you a billionaire my friend. Uh but if you could develop a system that it it it goes to uh mortgage lenders, mortgage brokers, right? Hard money lenders, uh hard money brokers, right? It'll tell you exactly which investor will take your loan and exactly which lender has the right guidelines for it. Now, this is a system that you have to have that uploads

guidelines from all of the different lenders all of the time. And we have thousands of lenders across the country, >> right? And then there's different applications. Well, there's different guidelines for residential than there are for commercial than there is for multif family than there is for industrial, than there is for retail, right? So, all of these different ideas and office, right? You know, like there's so many different guidelines and half the time half the time the

lenders don't understand the guidelines. Even the lender reps don't understand the guidelines, >> you know, and every once in a while there's a contradicting guidelines. You know, it's a little difficult. It's a little difficult. >> Yeah, >> it's not impossible. >> It it doesn't sound impossible, but it definitely sounds like a big challenge for sure. >> It is a huge challenge. I think the biggest problem comes down to data, you know, because once you have the

data, then you can you can program AI to do just about anything. >> Yeah. >> Right. And so if you have the right set of information from all the different lenders, then you can just take it into a decision matrix and say, you know, if this, then that. >> Yeah. >> On all these different all these different lenders. You know, I that's I don't think that's the hard part. The hard part is sourcing all the data

consistently from each lender. >> Yeah. And you know, I I think evidently, you know, some if lenders don't make it easy to gather the data um to put it into your software, then that's where kind of the chain breaks, you know. >> Yeah. >> Yeah. But it's definitely it's definitely still doable, you know. >> I kind of feel like we're getting ready to develop uh a different type of uh loan processing software here. >> Sounds like

it. >> Yeah. >> Think that the next idea was just born here. >> Yeah. Yeah. See, you know, another thing that I've realized, Josh, is with AI, you can build out just about anything that you can dream of. Just about anything. And I I truly say that not with a grain of salt, but like understanding it and using it and creating things. I've created, for example, I've created a loan matching system. >> Mhm. So, um I

have um a another broker that I know and he came to me and he said, "Hey, listen. I have um I have all of these different lenders that I'm using, right? >> And I would like to spit out a uh it's a hard money lender, so I would like to spit out a PDF that has >> uh the best terms for that borrower without me having to go and submit all of this information into a bunch

of different lenders. I have the matrices of all of the different let's say let's call it just 10 different lenders. >> Yeah. >> And it's uh it's the term sheet, right? I wanted to print out a term sheet for that borrower with the best terms out in the marketplace right now using all of the information from these 10 different lenders. He's gathering the information from each lender. And then I created a dashboard uh and I think

I coded it using Python or was it Python or TypeScript? I'm not sure. let's develop this for me as well. >> Yeah. >> Yeah, we could do that. >> I mean, the guidelines are a little bit crazier, but still we can definitely do it. >> It's a So, it's a loan matching system, right? And so, it's meant not to not to fully It's not like a full application that you're sending to the to the lender. It's

basically we reverse engineered it and the lender said these are our terms. if you have a FICO score of this amount and you have a income of this amount and blah blah blah blah blah and these are the guidelines, right? And it's it's a matrix and it's a it's a lot of different information. >> Yeah. >> And now we get this borrower. The borrower fills out an application on my loan matching system that I created. It'll

instantly compare it across the 10 lenders based on their specific situation and bust out a term sheet. It'll give you the the top three lenders based on the rate and terms and blah blah blah of each different lender. And you press a button, it'll spit out a term sheet immediately. And then that's something that that hard money lender can send to that borrower to say, "Boom, here you go." >> He can do it on his cell

phone. >> He can do it on his cell phone, too. He can do it on a cell phone. He can print it out. send the PDF right from his phone. >> I want to develop that with you for my business. >> We can do it. >> Yeah. Yeah. We'll get through the go high level and then we'll start that too. >> Yeah. >> We got a lot to do. >> It's a loan matching system and so

>> we're kind of falling into a place where we're getting all kinds of new technologies for our friends over at First Nation. >> Yeah. We're going to make something nice happen here. >> So, um that saves a lot of time for them, right? Because in the past they had to it was mainly a senior um senior loan officer that had to go through the whole process. >> Our biggest so by the way our biggest issue and

when we're pricing out loans is the pricing engines all suck, right? So it it this this if I could upload like rate sheets on a regular basis or have the system go in and pull the information and the rate sheets from each one of the lenders individually. >> I could have constantly not have to do anything except for hit a few buttons on my phone and I could price out deals left and right. How much time

could be spent could be saved if you had this sort of software right now in your hands? >> I spend about 45 minutes an hour with each client just discussing pricing. It's so so with each client and at least and that's over the loan process. So we we visited two to three times pricing before we actually finally lock a rate. >> Um because you know markets are always shifting up and down or rates drop you know

we we want to we want to wait just in case the rates drop. Like for example, right now if the ceasefire in the Middle East holds, right, the rates are going to drop even further and we're going to be able to lock a rate for my client, you know, maybe a half% less than what we got last >> last month that we did a loan for. >> Wow. >> Yeah. >> So, 45 minutes to an hour.

>> Yeah. >> On each client. So, and then if you're how many clients are you normally helping out in a month? >> 40 50 something like that. >> So, something like 50 hours could be saved minimum. >> One one week. One week of work. >> One week. An entire week of work. Yeah. >> And based on your current income, that's a that's a lot of money. Like >> times 12. >> We're going back to the time

value calculation from the last podcast. That's what's happening. >> Yeah. >> It's uh it's just the way my brain works here. >> Always time value of money. >> Time value of money is so important, right? I think if you >> And so back to what I was originally saying with AI, it's not it's not what you can build. is is this the right thing that I need to be building right now? That's that's where the question

now for me is changing in terms of man dude I have these conversations with people all day long Josh you know like this is the first time that we're doing it here on camera and like talking specifically about AI >> this is our dinner spitball >> but I'm I'm having a conversation like this with people every day and people are like man can you do this and I go and look it up and I can do

it well can you do this I go and look it up I can do it and so like literally nothing's off the table and so the problem then becomes not Can I build it? But it doesn't make sense for me, for my vision, for what we're trying to accomplish together, right? That's that that has been and so that has been the most difficult thing to shift my focus from, can I build it to this? Does this

make sense right now? >> Does it make sense for Yeah. I got a lot to do. Can I afford the time to do this? >> Yeah. Yeah. >> Yeah. And so, >> um, I I think it makes me look at time differently now, right? And and I think we're even having a conversation about even dinner tonight, man. Like I'm like like every waking minute that I have like I want to just be developing something that fits

into my vision of what I want the future to be. Right. >> Well, that's what the true definition of insanity and an entrepreneur is. >> I think I'm insane. >> Okay, go for it. That's what's going to do us. That's that's the right way to look at it. You know, >> very very crazy. When we first started out, how many hours a you know, a day were you working? >> Yeah. >> You know, I would show

up when I first started working, I would show up before anybody and I would leave after everybody. They were like kicking me out of the office. But that's what I did when I wanted to make money. >> That's what you have to do. >> Yeah. And more time in the office means more dollars in my pocket. >> Yeah. Absolutely. >> Yeah. Um so I think that it is time to shift a little bit of gears here

and start talking more about implementation because uh we're talking a little bit about you know kind of >> um >> systems you know processes um but I think let's talk about how people could actually implement it into their business today. Um but before we do that let's uh take another quick commercial break. All right, >> guys. If you're doing business in Houston and you don't have a great title company, I highly recommend you guys to use

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Make sure you mention Josuanas with Pickup the Phone Podcast. If you're a real estate investor anywhere in the United States you need to listen up, get hardmoney.com is a free platform for real estate investors. You can find local hard money, connect with the lender directly, request term sheets, and chat all in one single place. What I really like about the website is that they have free tools. They have built-in AI comping. They can they have flip

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thing is a no-brainer. There's no cost to sign up. It's just free value, free connections to any real estate lender out there. So get go sign up get hardmoney.com. >> All right. And we are back Josh. So we were talking about implementation but um I just realized we just spoke about implementation 20 minutes. >> So anyone that's watching this uh go back in 20 minutes and watch everything about implementation. I think >> excuse me. What what's

really interesting would be to talk about the future of AI. >> Yeah. >> Where do you see the future of AI? uh specific to my industry. I think uh AI is going to kind of take everything over. >> Yeah. >> Uh I think it's going to remove me as a service provider. >> Yeah. >> Uh there's going to be much fewer opportunities uh to have brokers available to massage deals and stuff like that. I just think

guidelines are going to change. >> Um >> yeah, and what I see is a lot of layoffs. That's how I think uh that's that's how I think it's going to affect the industry. >> Yeah. >> You know, lender lenders develop guideline AI systems to handle underwriting. Lenders develop AI systems to be able to uh you know, do the the creative intake, right? Um there there's there's so many different ways the technology could take over >> and

obviously you're make us obsolete. You're you're talking right now maybe like you know maybe what five years down the line 10 years >> I mean like being generous I give 20 like it's like the maximum I just can't it it's it's not only growing it's intelligence is growing at an exponential rate >> I think the biggest problem is bureaucracy there's all these just like in realtors right there's uh um like MLS boards >> right >> um

I'm sure there are some sort governing bodies for mortgage lenders as well. >> Yeah. Yeah. Of course. Of course. We have a lot of regulations >> and so but but the governing the governing bodies normally have a lot of say when it comes to policies that are being developed and and policies and laws that are being written in Congress. And so wouldn't wouldn't there wouldn't these folks maybe develop some sort of law that prevents underwriters and

prevents loan brokers from becoming obsolete? >> Yeah, it's possible. Um but you know I think I think with as the technology grows the industries uh gets stronger, right? And um >> no matter what you do, it's going to pull people out of the industry. Mhm. >> People aren't going to be able to do what the AI can do. I can't do what the technology does. >> I'm very good at what I do and I can't do

what the technology does. >> Yeah. >> So, we're talking about just like sometime in the future. I mean, there's no way to predicting like when it's going to happen. >> No, I don't think so. But I could say this that, you know, it's not only this industry, it's across all industries. Take farming or home building or or, you know, we're here in Texas, oil and gas pipelines. When you look at these different industries, there's nothing that's

happening there that, for example, AI can't take care of or like we were discussing earlier, an AI robot can't take care of. >> Yeah. >> All right. That's a huge that's that's a huge deal. I mean, that's going to take a lot of people out of the workforce, >> right? If you could remove uh a human being from being in a in an environment that could be dangerous, then why would companies not do that, right? Look,

as a whole, employees are liabilities, >> right? >> Right. Um, you could be working in an office >> or you can be working on an oil field, right? >> Right. >> You're a liability to the owner of the company. However, okay, that liability, you know, there's a there's a riskreward, you know, process that you go through and and uh you know, you you take the risk of the having that person as a liability versus the amount

of uh money that they can make you by being in that position that you hired them to do, right? So, you when you weigh these things against each other, you say, "Oh, okay. Well, what if I could just remove the risk?" Well, in in in industries where people, you know, they they they're very dangerous places to to work, right? If I could get a an AI powered robot to do the job that, you know, I don't

know, um, you know, an oil field manager does, right? Uh, or a technician does, right? And not have the risk of him dying on the job site and then having to get the insurance claim put in and then my insurance costs go up and all of these different things. If I could put a third party agent in there that that has zero liability or substantially lower liability, why would I not do that as a business owner?

>> Yeah. Yeah. >> Mitigate my risk, >> right? Yeah. I think inherently people are just going to, you know, eventually move to using AI for just about anything. Even um you know like there's a lot of uh there's a lot of talks in terms of what are the safest jobs out there, >> right? something like plumbing, electricians, HVAC technicians, and I agree and I think those jobs are going to stick around for a long long time.

>> Yeah. >> But what happens, you know, like 20, 30, 40, 50 years down the line when Tesla has these ro walking robots just walking around, you know, >> imagine just go as simple as cleaning your house. >> Yeah. >> If you could have a robot clean your windows, wouldn't you rather do that? >> Yeah, absolutely. >> Yeah. I think I think um then we shift into well what are human beings going to do? >> Yeah.

>> What are we going to do? >> Yeah. >> A great question. >> Yeah. >> You know >> uh it's it's hilarious. I I imagine like I just told you, you know, this movie Idiocracy is one of the funniest movies I've seen. But at the same time, it like puts this like glazing, you know, like beam right on human existence and how technology will ruin could ruin our lives and make us just gone from being a

productive, you know, driven society to just being a bunch of idiots waiting for the government to send us our check and our food vouchers. >> Yeah. >> Right. It's ridiculous. Um >> hopefully it doesn't get that. Hopefully it doesn't get there. we're able to manage. I think, you know, as time goes on, our our we don't know what the future holds either. And I think that we don't know how we're going to evolve with AI as

as AI is getting smarter and we're learning how to work with AI. I think that we're going to shift our perspectives also on a lot of things. And so, I don't know. I just I just think that like the future is completely unimaginable right now. >> Yeah. >> You know what I mean? There's too many moving factors. And >> I was even listening to um to another podcast earlier uh the coffee hour. >> Mhm. >> And

uh I think their guest was talking about AI and one of the main things that they said was uh right now there's a lot of market volatility. >> You know, we have like wild market swings going up, you know, points and going down and there's just it's completely volatile. There's no predicting it. >> Every industry every industry. Yeah. S&P 500's going up and down every day. And so, not every day, but >> a new high right

now. >> Yeah. Exactly. And then there's a new low several next days. So, what's happening is that everyone's trying to predict what's going to happen, but there's no way to predict the future here. >> Yeah. >> There's absolutely no way. There's so many unknown variables um that I think uh I think that for me I'm just I'm just so excited for the new generation of people that are going to come in and just uh clean up

house, man. And >> I'm planning on being one of them. >> We're all praying. >> Yeah. So, in terms of being able to >> just make sure you invite me on that, you know, big 50th birthday. I want to be there. Oh, >> of course. Oh yeah. >> I Well, I think you know I think the most important thing is just bring being able to find problems, finding the biggest problems that you can find and then

creating a solution with AI. I think that is the future is held in the in the people that solve the biggest problems. >> Well, let's talk about those robots again, man. >> Yeah. >> Honestly, take a think about it. How crazy is that? There's gonna be a robot that can do everything you can do, >> right? >> That's pretty nuts, huh? >> That's pretty nuts. What What What can the robot not do, right? Just you as

a man. >> Nothing. >> I mean, what? You can't think critically? Of course you can. That's what the AI is designed for, >> right? >> Right. You can do anything from washing your car to driving you around town to building. >> Well, I think I think what's going to be more important than is like things like art, you know, and creativity, right? >> Yeah. >> Human design, things that bring out the human spirit. I think those

things are going to be extremely valuable. >> I could see that, >> you know. >> Yeah. Yeah. >> What makes us human? >> I mean, we bleed. >> Yeah. That's that's one thing. >> I think that's what it is. I think it's that we bleed because all our human traits are being taken up by artificial intelligence. Dude, >> we're definitely going to be bleeding. >> Yeah. That's the only thing we're going to be doing, right? >>

Um Yeah. I think >> I mean even surgery doctors are going to go out. Surgeons are going to be gone because the robot could be more precise. >> Yeah. Eventually, you know. Um, I think that, and this is something that I realized when just like working with AI back and forth, man. Just I I've I've spent a lot of time working with AI. And one of the big like one of the biggest epiphany moments that I

had was that I learned that the future is held in the people that know how to prompt the best. >> Okay. Yes, I agree with that. You got to know how to ask a question. >> Because the answers are out there. >> Yeah. >> You just got to know how to ask the question. >> Yeah. >> And so, you know, I you know, the Bible says, "Ask and you shall receive." Right. I think with AI, you

could ask just about anything. You can receive just about anything. You just need to know what questions to ask. >> Yeah. >> Right. >> I think that's I think that's where we're going to that's where we're going to be. Okay. >> Yeah. >> We're going to know which questions to ask. >> Yeah. >> I think that's where that's what the difference going to be. And so critically thinking right now is the right time to get ahead

so that um so that people that are watching this, listening to this can take advantage by taking the time to talk to AI and then figuring out what problems they can solve um and figure out what solutions can be done right now. Um, and I want to talk and actually like bring value to anyone that's watching this, you know, >> because I think it's important to learn how to actually work with AI. >> So, there's a

lot of different AIS, right? There is Open AI, there's Enthropic, which is Claude, uh, Perplexity, um, there's Manis, Manis Pro, and I'll tell you a little bit about what I use each one for, right? >> Open AAI um, is really good at creating infrastructure, right? And so, I use, uh, some of their tools to do that. Anthropic is really good for actually uh writing code. And so they have actually they have so many different um platforms

out there, different service uh service models that they've come out with, but they even just came out with something called Claude Design that basically you know you know what Canva is. >> Yeah. Yeah. Yeah. >> Well, Claude Design now basically makes um Canva obsolete. >> Oh wow. You can >> also just put this over here and do that over there. >> You can create an entire design brand with claw design and choose your colors, see them

on screen, prompt back and forth and then you have the whole design of something. If you want to create a graphic, you want to create a flyer, a banner, a create, anything claw design. Boom. >> What's cool about it, >> can you automate it to constantly be creating new ones on a on like a weekly basis? Well, you can, but you would use an actual AI agent for that. But, um, I haven't tried plugging it into

the cloud design. And normally I just have actually like just claw make actual graphics for me. And I mean, it makes some fantastic graphics, >> pitch decks, um, presentations, um, yeah, graphics, creatives, anything. >> Yeah. And then I what I do is I I tied in my cloud code with different APIs um that uh I think there's one called FAL uh foul.ai >> and it's a video generator that can create creatives for you completely automated. >>

Wow. >> Yeah. So and then you can have something called a cron job. A cron c o n. A cron job is like an automation that says at 3 p.m. every day, turn on. That's all a cron is. >> Okay. >> Why it's useful is that if at every day you say, "Hey, at 3 p.m. every day, trigger that cron job to start the automation to create a new creative for our team." So then cron job

turns on. Boom. It does the API call, calls FAL.AI, AI. It creates a graphic. It sends it back over to you and now you have a nice creative on your dashboard. >> I need this. >> All completely automated. >> I need this. I absolutely need this. >> We all do, Josh. >> Yeah, that that's the one I need more than anything right now. >> Yeah, please. >> Yeah, absolutely. The system will do it automatically for a

lot of ourformational posts. >> Yeah, >> we'll just, you know, update. Hey, >> create here's some information. Make a creative for this. Yeah. >> Right. And we can take that and put it on our Instagram or wherever it is that we're posting. Yeah, >> that's huge for us. >> Yeah, >> it's a lot of time saving. >> There's I mean again like there's so many there's you can do anything with with AI. It's just like what

is the most important thing that I have to focus on right now? That's a question you should always be asking yourself is what part of my business needs to be automated? Which part of the business needs to be automated right now? Right? What what are the you know maybe create a list and then just write down a list and then look at the list and say one two three right here that's it. let's focus on that

right now. >> Yeah. You know, and that's I think how everyone should be working on things. I think, you know, if you look at some of the most um successful athletes out there is because they learned how to prioritize. >> Yeah. >> And so that's one lesson that I've taken to focus in focus on the right things today. Anyway, so cloud code, okay, that's what I use in thropic. Uh, Perplexity is fantastic for doing research. It

is incredible for doing research. It can go online and find out just about any um medically um peer-reviewed journals um factual information. So when it comes if you ever think I need to know the facts about this topic about topic XYZ perplexity. >> Okay. >> Incredible. when I was developing this emotionally intelligent voice AI and the reason why I say it's the first one is because there are emotionally intelligence um there is emotionally intelligent AIs out

there but nothing that's specifically designed together as a package for real estate for the real estate industry >> every single voice AI out there is advertised as just voice AI and so you know yeah there's no no one else out there when I started doing the research and this is back in February uh what was it no January 30th 2026 I looked at all the cuz I was already working with voice AI for a while but

then when I found this and I was like all right January 30th 2026 no one else is out advertising this I went to work we developed it we have it on market and so that's why I say it's the first voice AI for uh real estate for the real estate industry uh first emotionally intelligent voice AI for the real estate industry Um, Perplexity is the one that uh, and I asked all of them. Gemini Open AAI,

>> but that's the one that gave you all the information, the real information, the >> one that the one that I would call factual, you know, and I mean it makes mistakes too, you know, but I after I cross referenced them with >> with every uh with most not I don't want to say every because there's so many LLMs out there now, you know, like um Google even has like something called Gemma, there's something called Quen,

there's something called Kimmy. Um so the owners of I believe Alibaba uh created their own large language model >> which which large language model basically is your open AI your chat GBT your claude that's an LLM >> okay >> it's a large language model I think the owners of Alibaba created um uh this LLM that runs locally on a computer what that means is that if you've ever used flot for an extended amount time you run

out of usage and then you have to pay 20 bucks a month. >> Yeah. Yeah. >> So these guys created your own LLM that can run on your desktop, on your computer, on your machine, whatever it is >> and you don't have to pay any tokens. You don't have to pay anything. >> That's nice. >> The only thing you pay is for the electricity, >> right? >> So now the cost goes down significantly. Now you can

just spin up agents to do just about anything, >> right? >> You have you have to have the the hardware to be able to handle it. But if you do this, the computer just stays on and it just keeps rolling. >> Then it just goes back to having an initial large investment and then boom, now you have all of the computing power that you need to run about just about anything >> in your business >> and

and it's not out on the internet then it's really just doing it on its own. Yeah. It's all local. >> Yeah. So it's faster too. >> Yeah. >> It's faster your servers on your computer, you know, and you can serve clients a lot more efficiently. Um anyway, so those are some of the Oh, let me talk about Manis. Manis Pro is really great at transcribing videos. So, um what I do is I I entered YouTube videos

into Manis and I ask it to transcribe it and then give me some insights on it. So, if I ever, let's say I have someone like Alex Herosi or um, you know, what's another, >> you know, what's what's another someone else that you look up to on YouTube? >> Well, me and myself, I really it's all about me. Yeah. But no, generally, I don't know, you know, other other Tony Robbins. Tony Robbins. >> I like Tony

Robbins quite a bit. I like uh, you know, I like Kevin Ori. I think he's hilarious. >> Yeah. So you can you can you can go and look at their YouTube channels and then just basically transcribe just about any videos, get their insights without having to watch an hourong video, >> right? >> You know what I mean? So >> uh but I use it to create SEO for my own YouTube videos actually for for the podcast,

you know? I create it all with AI. I create uh the SEO, the hashtags, um the uh the tags, everything. Everything on MadnessPro. >> So Madness Pro. >> Yeah. Write it down. Yeah, write it down. SEO girl, write it down. >> Um, and then cloud code of course is what actually writes code. And I think, you know, I think it would benefit a lot of people if they started working with cloud code sooner rather than later

because uh if you learn how to automate processes in your business using cloud code, then you know uh then you can get a lot more productive a lot faster. >> Yeah. >> Absolutely. >> But of course it's or or you don't have to do that at all. You can just hire me and >> we can me and my team can do it for you. No problem. >> Absolutely. Great team. Great team of people. >> Absolutely. >>

Yeah. >> Um but man, what is the last thing that we need to talk about here, Josh? >> Well, one thing I want to bring up is that um I'm I'm fairly impressed by you. >> Uh it's, you know, we've known each other for quite a few years, but you getting engaged and not saying anything is kind of a big deal. So, that's something we should talk about. >> Getting engaged. Yeah. Yeah. >> Yeah. >> Kind

of kept that quiet. >> Kept it quiet. Um, you know, we >> was a great great surprise. >> It's a fantastic surprise. Well, >> big congratulations, Steve. >> Thank you so much. I appreciate it. I think for me it was um I wanted to have all the photos back and we finally got them back. I think by the time that this uh episode gets aired, the photos will be online. But uh >> man, it's just a

huge blessing. You know, I had um I had just about given up on love, man. And you know this this girl comes by and sweeps me off my feet. >> You know, I always thought I always thought it was really cliche whenever people say when you know, you know. >> Yeah. >> I I hear that all the time and I'm like, dude, what a load of BS is that, right? >> Right. >> Literally literally saying that

about a year ago and then here comes Emily and >> Yeah. >> When I knew I knew, >> you knew you knew. >> Well, congratulations. She's a great person, great girl. >> Absolutely. >> We're wishing you guys a lot of health and happiness. >> Thank you so much. I really appreciate that, bro. >> Yeah, absolutely. >> Um, >> what is the last thing that we need to talk about? Maybe a 60-day 60 90day strategy. >> So,

yeah. Um, strategies that we definitely need. We have we have a so far we have like a 30-day strategy you and I put together. >> Yeah. >> And that's, uh, just getting the AI up, getting it initial development done, and, you know, getting the the phone systems attached to it and all that stuff. Second step is going to be finding out how we can make that uh CRM with the AI uh work together for phone and

text application. How we can implement them together and make sure they're >> they're cohesive. >> Mhm. >> That I think is going to take us another 30 days. >> Yeah. >> So, um on the 90 on the 90, I'm thinking that we have to find ways to um make the AI system talk to the other technologies that we're using. Yeah. and kind of be the go-to for for bringing everything together. So, from coming coming from our

intake uh our intake technology where we take all the documents and the loan application, all of that stuff, then going into the you know um you know the information transferring from the CRM to that system and then from that system going into our um our processing software. >> So, we have a three-step process that's going to take us quite a bit of time, I think. Um, so, so I guess >> then then you didn't even hit

on the uh loan matching system. >> Oh, that's going to be I think that's going to come after. >> And then also the uh the content generation. >> We could we could call that about 120 then 150. >> Yeah. >> And then 180. >> Yeah. >> Yeah. We got we got quite a bit. That's a great road map. >> Yeah. >> So let's write it down. Let's write down our 30day. >> You want to write this

down? Yeah. Yeah. Just send it over >> here. Go ahead. You can write this down. >> Yeah. So, uh 0 to 30 develop the CRM, right? >> Mhm. We're working on that now. >> Yes. And then 30 to 60 I said um integ uh make sure that the integrate the AI >> voice AI. >> Yeah. Integrate voice AI. >> Mhm. >> All right. And then day 60 to 90 is um how what making the the softwares

collaborate. Okay. Okay. Go high level talking to your um what is it your mortgage softwares high >> level >> loansify we use >> loans supply okay >> it's great for taking applications and then the um and then encompass which is what we're using now which I want to change >> okay >> but it's really good um and then so our 90 to >> 120 >> 120 90 to 120 is going to E >> loan matching system.

>> The loan No, we were going to do something else before the loan matching system. >> Okay. >> Roll back the tape. >> Yeah, we'll roll it back. Loan matching system. >> Yeah. >> Okay. >> Content generation. >> Yeah. Content. That's the That was right. >> Okay. >> We can flip them. No problem. >> To 150 content gen. Okay. These are going to be our road map, our initial road map. >> Yeah. >> So that's really

great because in in the I mean we're making some killer progress right on the CRM. >> So then once we integrate the voice AI to it, I think it's going to be a great test phase on how to develop these things together. >> Right. >> Right. Yeah. >> Um and then you know the go high level loans of encompass integration is going to be huge. Uh, and then, you know, obviously the loan matching system is going

to make um >> it's going to save a lot of time. >> It's going to save me a lot of time. >> Yeah. >> Uh, yeah. It's going to save a lot of time. >> Absolutely. >> Yeah. I think that's a great way to put it together. >> Yep. Absolutely. Well, >> yeah, >> Josh, I hope that uh anyone that's, you know, watching this podcast or on YouTube or listening to it online uh took some some

golden nuggets out of it and uh hopefully starts investing their time and energy in learning AI and >> solving problems for businesses because uh I think the next year is >> going to be the new gold rush >> and absolutely >> and it's the gold rush of of of uh AI. It's a gold rush of software creating software for solving issues for businesses. Um, so I think if people jump on board and start uh solving a

lot of these problems, I think they're going to be okay in the new in the new era of uh whatever, >> you know, there's there's a lot. >> Yeah. I mean, there's so much happening. There's so much new technology coming out. And the thing is, it doesn't matter what industry you're in. We're mortgage brokers, right? We're very vulnerable to the technology advancements of AI. But that being said, right, you need to make yourself, it doesn't matter

the industry. You need to know what's going on, how you can use it to continue to be successful or to be more successful or to phase out what you're doing, >> but you need to know what's going on, right? You have to be up to date with everything. So for us developing these softwares and these systems and everything and taking advantage of the AI and the different systems so we can continue to develop these softwares that

we need and the integrations that we need and all that stuff. And this coming from a guy who knows nothing about computers or technology, right? I I barely know how to use my iPhone, but I know enough to say, "Hey, I know there's something that I don't understand. I know there's something I need, and this is how we're going to go get it." >> Yeah. >> Right. >> Absolutely. >> So, yeah. I mean, I I this

this partnership you and I have is is is a great place for us to start. >> Absolutely. Well, I can't wait, man. I'm really looking forward to it. So, you know, in closing, I would just say that uh I'm really excited about the future. And uh man, I think, you know, priorities, that's it, right? >> Let's prioritize what's important. Let's focus on that. Let's execute. Let's go out there and crush it, bro. >> Absolutely. >> Yeah.

>> All right. >> All right, Josh. Thank you again for being here, man. Um, before we before we uh end, the only last thing is uh if anyone wants to >> get in contact with you, maybe to talk about, you know, mortgages or maybe I I know you mentioned you wanted to get some new MLOs's onto your business. >> Yes. Yes. >> If you're an MLO out there >> and you're looking for a productive uh forward-facing

mortgage uh broker that is incorporating AI into his business, >> how can people reach out to you? Well, you guys can always reach out to me on my cell 8329559255 or always our website fnfloone.com. >> Uh we're FirstN Nation Financial Corp. again been in business since 2004. We have a killer team of underwriters in our office and processors. Uh the beauty about what we do is that we work nationally. So we're not looking at, you know,

you know, we can only do California or we can only do Texas. We do loans nationwide primarily for investors. The beauty about working with investors for us is that it's a constant repeat business. So, we're, you know, we're kind of trying to push that agenda. The first-time home buyers, we do a lot of uh cash out, refinance, residential, we do a lot of. However, you know, the investors are where the money's at. Yeah. >> So, give

us a call >> anytime you want. I'm always available, right? Um and if I'm not available, shoot me a text. >> Yeah. >> You can you can send me a text past 8:00. >> Yeah. >> Cool. Thanks again for being here, Josh. Really appreciate it. >> Thanks for having me on.