[00:00:00] Speaker A: How closely are you looking at your
[00:00:02] Speaker B: monthly P and L?
[00:00:03] Speaker A: Furthermore, how far do you drill down into your weekly or monthly payroll? Meaning do you know how much you spend on your hosts, your reservationists, your cashiers, the ones who answer the phones, give people directions, book reservations, take to go orders? Do you know how much you're spending on them? And do you know if they are generating as much money for you as they possibly can?
This is the part of the conversation where AI comes in. I'm chatting with one of the co founders of Lohman AI on today's episode. If you think we are not there yet, I felt the same way. But guess what? I believe we are there. All of that phone answering and what it can do for our industry on today's episode.
There's an old saying that goes something like this.
[00:00:49] Speaker B: You'll only find three kinds of people in the world.
[00:00:51] Speaker A: Those who see, those who will never see, and those who can see when shown.
This is Restaurant Strategy, a podcast with answers for anyone who's looking.
[00:01:18] Speaker B: Hey everyone, thanks for tuning in.
[00:01:19] Speaker A: My name is Chip Close. I am your host here of the Restaurant Strategy podcast. I put out two episodes every single week. The point has always been to help you build a more profitable, sustainable restaurant. I also run a coaching program.
[00:01:32] Speaker B: It's called the P3 mastermind.
[00:01:34] Speaker A: If you want to learn more about what we do in that program to help restaurant owners make more so they can ultimately work less, go to RSProfit.com you'll find the link as always in the show notes.
[00:01:49] Speaker B: So my guest on today's show is gentleman named Christian Wiens. He is the founder and CEO of of a company called Loman AI. He's building an industry leading voice AI agent or AI agents for restaurants that would answer the phone 24 7. Everything from answering questions, booking reservations and yes, taking orders. We're going to get into all of this. I didn't think we were there yet and I think we are finally there now. Christian, welcome to the show.
[00:02:16] Speaker C: Thanks for having me, Chip. Excited to be here.
[00:02:17] Speaker B: All right, so talk to me about Lohman AI. How long you been building it and why do you say that we are finally there there?
[00:02:24] Speaker C: Yeah, I would say so. Taking. Taking you back. We started LMAN AI in May, June of 2024.
So not too long ago. Right. But right at about the time where large language models started and voice AI technology started to be good enough at something called tool calling to really make this order taking process happen. Right. Prior to that I think it was really easy for an AI to sound good when it answered.
To even do reservations. Right. Reservations. And answering questions is pretty easy.
It's a pretty simple thing. Right. Like I was telling you before the show, I think you could build that yourself even, or at least build a demo of that. But when it comes to taking orders and which is a vast majority of the use case here, I think for restaurants that are struggling with phone calls, nothing really worked up until a couple years ago. And it's a really hard engineering problem. And so we started the company two years ago. Today we're serving, you know, over over a thousand restaurants.
We're growing incredibly fast. We added 200 restaurants last month.
People love Lohman because answering the phone is an incredibly hard problem. Right. And I think one of the reasons why is I was just reading this article literally 10 minutes ago about labor becoming so impossibly hard for restaurants to rely on.
[00:03:53] Speaker B: Yeah.
[00:03:53] Speaker C: So that's where I think we're at. I truly do think we're at.
We are there. And it's not so much that the whole industry is there because I think it's that Loman AI is there. We've done the technical work to ensure a 99.3% accuracy rate on our order taking agents. Like we can actually do the work of taking an order over the phone and also the important work of, you know, answering all the, all of the calls, answering multiple calls at once, taking reservations, answering questions, providing a human like experience all in one true industry leading voice agent.
[00:04:28] Speaker B: Because, and so like you said, so there are a couple of use cases for phone answering. So we know reservationists are expensive, we know they're unreliable because maybe they didn't show up today or maybe they didn't learn the correct answers to all of the questions. So when somebody asks for directions, we tell them this when they ask if we have valet, we tell them this if they ask where's the closest parking lot? Or you know, do you validate parking? Or you know, are you gluten free or all of this. We gotta make sure that a 16, 18, $20 an hour, maybe, you know, high school kid knows the answers to, you know, do we have gluten free pizza and do we have, you know, such and such made with or without, you know, shellfish or nuts or whatever. It's like we're trying to, you know, train all of these answers to the questions they may get or may not get.
So just from the easiest use case, right, the, you know, answering questions, when people call with questions, there was some friction there.
And then taking reservations which should be easy. So those are the two easy things. And I've seen phone answering, I've seen AI phone answering do those things. And what we're specifically talking about is the taking the order. Because taking the order, getting it right. You know, I want a cheeseburger, but no cheddar. Can we sub that with gruyere? And no pickles. I want extra barbecue sauce, like all of the modifiers, making sure that the AI agent gets it, receives it, hears it, recognizes the information and then successfully, basically successfully inputs all those modifiers and those substitutions into the computer charges appropriately for them, communicates to the individual who's going to be doing the actual cooking. That's what I felt wasn't there. And that's why we're having this conversation, because I think we are finally actually there.
[00:06:15] Speaker C: Yeah, I think honestly by happenstance too.
I can't speak to other companies, but like with Lohman, right? Like, we pride ourselves on building an AI agent. We built for that use case from the beginning and we happened to build for probably the most complex of that use case, which is pizza, from the beginning. Now, Lohman isn't. We're not a pizza phone answering solution, right?
It just so happened that was like our first set of customers. Now we answer phones for everything from two Michelin star restaurants to the food truck that's selling shawarma across from the office right now. Like, right, like we do every type of cuisine, every type of every type of restaurant, whether it's full service, you know, luxury dining, quick service, counter service, it doesn't matter.
But we started with pizza, right? Our first customer was a pizza customer and it just so happened that his menu was like a thousand items long and we didn't really know the difference, right? I started out, I was this person. I worked in a fast casual barbecue restaurant from the time I was in seventh grade when I was like, not even allowed to work. My sister managed the place and so I was able to get a job busting tables. And then I worked there all up until, actually I worked their freshman year of college summer up until that summer. And then I started doing other stuff after that.
And I remember so distinctly, literally just pulling the phone off of the wall because we thought it would just be much better to not answer to, not to have like a.
Make it sound like we weren't available than to leave the phone ringing or to get, to get an answering machine, right? And the metrics back it up. 40% of restaurant calls are either missed or put on hold. And I think one other thing that's really interesting to people is that 30%, according to the National Restaurant association, in 2025, 30% of restaurant revenue still comes from the phone. A lot of that's ordering. Yes, but a lot of that is just a lot of that. You know, I need to ask a question to make sure that I have some. One of my needs met before I come into the restaurant. Do you have something that's gluten free?
Do you have a high chair for my kid or whatever? Right. And then there's obviously reservations. I think cracking the ordering solution was just by our, you know, we had to walk through the fire by, you know, getting this crazy thousand items pizza menu in Philadelphia with this crazy owner. Honestly, it was just luck, like we, you know, and skill, like my, my co founders, Anita and Janssen are the two best engineers I've ever met in my life.
And so they figured out how to make this work after like just a million trial and error. But I think, you know, one of the really important things to talk about here is that it's. It's so easy to create a demo of this stuff that sounds like it works. And this is probably why you say it doesn't work. Right.
I think there was a lot of companies out there that created agents that sounded good. Right. And I was just telling you before this, like, I can go on Claude or ChatGPT and vibe, code something and give you a phone number that sounds really good. Like it sounds like it's taking your order correctly.
But I always tell people that demo is only 5% of the way there.
If I send you a phone number that takes an order but doesn't go anywhere, what's the point? So you have to get the direct integration with the point of sale system. You have to be able to take payment over the phone in a PCI compliant way. You need to be able to look up the guests, you need to be able to take delivery. You need to be able to correctly look at the modifiers, take the pricing correctly, insert that or, and then inject that order with the correct dining option with the correct pricing into the menu in a way that will then go and print in the kitchen. There's so much nuance to this workflow.
[00:10:04] Speaker B: Yes.
[00:10:04] Speaker C: That I think that's why, you know, you saw it before not working. And I think we just had to put so much effort into making it work. And we did that in a really complex environment in the beginning. And so now it's easy for us when we get somebody that's got 20, 30 items on their menu.
[00:10:21] Speaker B: It's so funny when we talk about consumers not wanting to talk to, you know, a computer, so to speak. And I think, I think I felt that way two, three, four years ago. I say nobody wants to do it because it's not a smooth interface yet. There's just the user experience isn't good.
And I'll never forget, it was about eight months ago, I had to call my, my home security company and I was having issues with it and I needed to schedule an appointment and I had an AI agent literally answer the phone and says, hi, you know, I'm an AI agent, but I could take care of anything. Speak to me in full sentences and ask me anything you want. And it was about an 11 minute call, give or take. And she, I say she because it was a female voice. She walked me through everything and at
[00:11:05] Speaker A: the end she was like, great, yep,
[00:11:06] Speaker B: let's get a technician out here.
[00:11:07] Speaker A: It was so smooth.
[00:11:09] Speaker B: She got the tech, she's like, you know, the next available date is this. Does this work? No, it doesn't really work. Can you give me my next three options? Yeah, let me give you this. So later, literally it was this 11 minute conversation with a computer and I went, everything was sort of like resolved by the end of that 11 minutes. And I hung up and went, oh, it's the first time I really felt now to your point, it's sort of an easy use case, but she was troubleshooting the panel in my home and was asking me questions and was looking at the technician schedule and was looking at like, what sort of service package I have. And you know, all of that's just data in a computer. But it was so seamless and I was just like, oh, it was like. And it was so seamless and it worked so well.
[00:11:50] Speaker A: And I think it was better.
[00:11:53] Speaker B: And I really mean this, I think it was better than having some sassy individual at a call center. Or what I think drives a lot of people crazy is when your call gets punted overseas and there's a language barrier or a thick accent and all of that. And it's like. And I think that's driven a lot of people crazy over the last 15, let's say 15 years. And I was like, oh, we're there. Like, it's just, it's so good and clean.
So it's so easy. Especially in restaurants now, we bring it back to what we do is that oftentimes the workforce is unreliable, unpredictable, both in, you know, are they going to show up and are they fully trained and are they remembering all the thing we taught them and, you know, are they saying the things that they're meant to say in the way that we want them to say? All of that and the fact that you can just teach a program to say exactly what you want them to say, and they're going to say it right the entire, you know, every single time, no matter how many calls, and they're going to field, you know, 10 calls, you know, at a time, you know, even if your reservations can only handle one and put the next three on hold. Yeah, I just thought that was, I thought that was.
That's what I've been looking forward to.
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[00:14:02] Speaker C: Yeah, I think it's, it's so fun. It's interesting because I bring this up a lot as well. Like, we had an uphill climb from the beginning because people were like, consumers are so biased to robots on the phone. Right? And like, I was too. You have no idea.
Actually, you do, I'm sure. Like, think about how mad you get when you call Capital One or you call cvs, right? I remember recently I called CVS still to this day, and, right, it's been the same way for the last five, 10 years.
But I called CVS. I was trying to get an update on a prescription and I went through their IVR phone tree. That took, I think it was probably like seven different paths of like, say this one or press this if you want option A or press this if you want option B.
I got all the way to the point and I kept saying, like, please can I speak to a Human.
And like, it just ignores the commands. I got all the way to the end where it said like, okay, like we're going to send you to, you know, speak to the restaurant or to the, to the pharmacy. And immediately it was a voicemail that was like, unfortunately we don't take calls. You're gonna have to leave a voicemail and we'll call you back. And like, that experience is the experience of consumers every day when they call these businesses that like. And it's not the business's fault. The businesses don't have the money to hire low skilled employees for rising minimum wage to answer the phone. Right. For you're hiring some high school kid that just broke up with his boyfriend or girlfriend, is pissed off, you know, half the time, probably partied the night before is sleeping on the job. Like, I was that person, by the way. Like, I know how bad I was at that. And so it's not like it's, it was, it's an unsolved, it was an unsolvable problem until recently, I think. And like, there's like, it's been such a, it's, it's been such a fun experience trying to, when you see people's reactions kind of break through after, like, they initially are like, oh, whoa, this is an AI. And then they're like, oh my God. And they start talking like in the background to their friends. Like, this is crazy. Like, you know, they're answering question, all my questions. And so we see that stuff and it's, it's like, really, we have to, to shift public sentiment on this stuff. Right? We're not a phone robot, we're not an ivr. We are not somebody overseas that, you know, really can't do anything for you. This is a voice AI that is going, that is built specifically. And at least in Lohman's case, like there's other voice AIs that aren't. But it's built to get a job done and do it end to end. It's not, hey, I want to place an order. Okay, I'm going to send you a link to do that online yourself. That makes no sense. Like, I always thought that was so ridiculous from the very beginning. I was like, what's the point? Just turn the phone off. Just tell people to go online or don't have a phone if you're gonna do that.
Yeah, anyways, I thought that was just the most ridiculous. And so anyways, shifting public sentiment has definitely been one of the most important pieces of this whole puzzle. And I think we're getting there. I mean, there's definitely still a lot of work to do though.
[00:17:06] Speaker B: I really do believe, I don't think people actually care. And so whatever prejudice I had against the robots, again, that ADT call was like, oh, actually I realize I don't care as long as it gets done. Friction, you know, frictionlessly and goes all through that. Like I could just, I could just see it. All the times I've called AppleCare, all the times I've called, you know, my mechanic, it's like, oh, we're just there. I could see it all in front of us. But restaurants, right? Again, we got people calling like, hey, where's the closest parking? Hey, do you have gluten free? Hey, can I place an order? Hey, can I make a reservation?
All of that makes a lot of sense because you can only answer one call at a time. And for me. And so I want to get into like exactly what you guys do, how it's different, how it's better. But for me, we're talking a lot about the over the phone experience. But I think deeply about the in store experience because the number of times I've walked into a restaurant and had somebody on the phone and they put a finger up in my face and say, you know, hang on one second. It's like not a good first look, Not a great first impression.
Heisman 100%. I spent, I spent the better part of a decade as a maitre d in New York City running, you know, the front door of, you know, Michelin starred restaurants.
And I would tell all my hosts, I said in my reservationist, I said, I don't answer the phone. There has to be somebody there in a suit welcoming these people because they're about to spend 2, 3, $400 per head minimum. And so what they deserve is not have a phone jammed in my face, like just, they deserve a handshake and a warm welcome. So I will never answer the phone. The phone rings, you guys answer the phones. It was, it was one of those things. And I had people like, on the surface, they were like, oh, you know, they felt I was being lazy or whatever. And I was like, no, no, no. It's just that, that's why, that's why you.
Because when somebody comes in, they want to see, they want to see me. I run the front door. I'm the one who helped them get them that, that reservation. So talk to me. I mean, we're talking about missed calls, talking about missed revenue, talking about like people getting pissed, getting put on hold and not Wanting to wait anymore. So, so talk to me about how, how the voice AI helps solve all that.
[00:19:12] Speaker C: Yeah, I mean it's two sided, helping the consumer and more importantly the restaurant. And the restaurant operator who's overwhelmed, can't hire fast enough. So Lohman is what I think is the industry leading AI phone agent for restaurants. What it does is it answers 100% of the calls you're going to get, never puts anybody on hold. It can answer multiple calls at once. It can speak in 15 different languages, it can take orders in a bunch of different languages. Right. It can take orders end to end with complex menus and modifiers. It doesn't matter whether it's catering or regular order. It can take a reservation, it can cancel a reservation, it can change your reservation, it can answer questions about the restaurant that anybody might have based on information it's given.
And it integrates with the systems that you already use, right? It integrates with the top, it's like the top 30 point of sale systems or something like that. Definitely toast, you know, spot on. Clover Square shift for olo, all of the big POS systems. Aloha, ncr. It integrates with the point of sale systems, the reservation management systems, the open table, the resi, the seven rooms. Right.
So your phones can be handled 100% of the time and you're in store. You know, your front of house people can focus on the people in the front of house that are in your restaurant. The idea is take this job away from, you know, you're probably not hiring somebody to just answer the phone or you are, right? And then you're paying, you know, 20, 15 to $20 an hour to do so.
So it's a conundrum either way. And so that was taking, you know, 20, 30% of their, their, their time and a lot of the phone calls specifically are coming in in these four hour or three hour rush periods, right. For lunch or dinner. And so you're just missing a humongous amount of the calls. And so what Loman does is we completely alleviate that piece of the job for the front of house employee and allow them to focus on providing a better in person experience to the people that are walking up to your counter that you're seating. Right. That you're handing out food, you know, at a busy takeout place. Like you can focus the work on coordinating the million Uber delivery drivers that are coming in and the people that are walking in to pick up their orders or, or pay for stuff. Right.
It also takes payment in a PCI compliant Way over the phone in the native rails of the point of sale system, right? So that's really important too.
It could take an order for delivery or pickup, right? So the idea is that we can do anything that a front of house employee can do and a lot more, right? Like with the exception of like, hey, I need to speak to, I need you to tell me, you know, like something like there's small situations like, I don't know, like can you hand the phone to your boss? Like, oh sure, we can transfer the call to the boss. But like I can't, you know, I'm not. The AI is not in the restaurant viewing the people right now. There's, there's maybe a few small use cases it can't do. But for the most part the idea is that it can do 100% of the things that the front of house person can do and more, right? It knows the menu with 100% accuracy every single time, right. It can, it can transfer calls if it needs to. Like if you don't want it to take catering orders, it could transfer to a catering department. It can send SMS links, right? If somebody does say, hey, I want you to send a link to this rewards program when somebody says these, you know, potential or talks about it, right? It can give information, it can provide directions to somebody that's like lost getting to the store.
All of these kind of things are things that Loman can do and it can do them for all calls that come in without ever putting anybody on hold. I think that's a really big one. There's this place here in Austin, Modi's, that like, it's just like a pretty good Tex Mex place, but really popular. There's like five or six of them. And it's always crazy, like always, like at dinner time. And a few nights ago my wife was like, we were tired because our baby's teething right now and we wanted to get food there and we called. I called four times and that's more than most people call. 90% of people drop off after the second call that nobody answers.
And I got put on hold for 10 minutes and they still didn't answer the phone. So I finally hung up and I drove there myself and I went and did the thing and you know, you know how aggravating that is for a consumer?
[00:23:56] Speaker B: Yeah, I do.
[00:23:57] Speaker C: If you're not gonna, yeah, if you're not gonna do it, if you're not gonna answer the phone, just don't answer the phone and don't have a phone or you can get this solution and have something that can take over that, that those missed calls and that, that missed opportunity you have to connect with your customers.
[00:24:15] Speaker B: Yeah. So talk to me about, so what's the, you know, what's the uptime? What's the, like, what's required from the operator to get this all, you know, up and running? Because if we're bringing on a reservationist or bringing on a host to answer the phones, you know, we got to train them. Okay, here's our website. When people ask about parking, we ought to do this. When people ask about valet, we do this. If they ask about gluten free options or shellfish or nut allergies, we got to do that. Like we have to give them the sort of bank of answers and we need to make sure that they're learning all these things. And so I assume all that information's
[00:24:45] Speaker A: gotta be fed to the system.
[00:24:47] Speaker B: So talk to me about how that process works because I'm sure that's what anyone listening is naturally thinking.
[00:24:52] Speaker C: Yeah, on average, we get people up and running in under seven days.
And the, the difference between hiring lowmen to answer your phone and hiring a high school kid to answer your phone is you will teach Lowman something once and it will remember it forever and will always remember and will only get better at understanding it with all the context that it gets from all the phone calls a high school kid.
It's also going to take you about 100 times less to train Lowman on the amount of information that you're training it on versus the high school kid. So it's really simple. It's get, you know, you come to us and say, hey, I'm really interested in using the service.
We'll take you through it. You know, if you have a point of sale system or reservation system that we work with, like, great, we hook up the integration between Lohman and that system. We then get the information we need from it.
You provide any extra context you want to Lohman before the call starts. So hey, you know, we have a patio. We show the NFL games on Sunday, whatever, and Loman remembers all of that stuff. And then moving forward, Lohman will actually start listening to the conversations that you're having with your guests. And if questions come up frequently, we'll isolate and prop those up and we will learn what the answers are to those questions and then be able to answer them in the future. So it really takes about seven, you know, to 14 days of. And that's mostly because of the operator. Like we, we, we can get people up in 24 hours in the same day if you really want. Like, it's pretty easy for us to do because we've built so much infrastructure. Most of the time restaurant owners are pretty busy and like we need them to like give us access to the menu and POS and stuff. So that's really the holdup. But it's going to take 10x less time than it will be to train the, you know that you're about to train. It's only going to be there for six months anyway. Loman can be there for life. You can train it in 10 1, 10 of the time and it's going to be 100 times more accurate. And here's the best part about this whole thing, Chip. It's only getting better. Like it's only getting smarter. And it's scary because like, think way past restaurants. Like everything this is happening everywhere, it's just getting so much better. And.
But in restaurants, right, it's solving this problem for operators and for managers.
[00:27:14] Speaker B: Talk to me. So I mean, I love that you talked about. Because I've, I am upped my ears in this stuff now. So this conversation comes at a fun time for me because of where I'm at with this. So talk to me about specifically restaurants. But you know, phone answering is here, but extrapolate out. Talk to me about the future and how you see AI employees, AI agents. You know, how all of that that is going to play out in the, in the sort of the future of restaurants.
[00:27:41] Speaker C: Yeah, I mean, we built Voice AI, you know, as our first AI agent. Right. But that's not the first. That's not where we're stopping. Right. We're going to continue to improve it and make it better and add and, and like I said, like it's getting better over time. Right.
But I think there's a lot of jobs in the front of house and back of house and that the operator does on a daily basis that can be automated with AI agents.
Right. And so we're already building the next phase of that. What that looks like is any place where an operator or a manager is spending a lot of time doing something manually that can be done by an AI agent. Think inventory management, staffing, social media management, DM automation. Right. Like we are planning to build an AI agent for it. We plan to be the AI workforce for restaurants. Right? Ultimately, ultimately. But, but we saw, we went in to solve the highest leverage, highest ROI problem that we could find first. And we thought that was Voice AI. And now we're here so tell me
[00:28:47] Speaker B: if I'm wrong, because I've been in restaurants for a very long time and I've hired and run payroll for a very, very long time. I mean, this is six figures. This is six figures off the payroll when this thing's integrated.
[00:28:57] Speaker A: Right.
[00:28:57] Speaker B: I mean, conservatively. I'm not exaggerating that number. Right.
[00:29:01] Speaker C: Easily. I mean, it depends on the size of the operation, obviously. Right. If it's 20 locations, easily six figures off the.
[00:29:08] Speaker B: Let's talk about just a single unit, 2 million. You know, when I look at, you know, the amount of money that I spend on host reservationists. Right. The people that are just specifically there to answer the phones.
Yeah. There's. Sometimes we still need people at the front door to say hello and welcome to a table. But there's also other people that we've got we over staff because we need. Okay, well, while this person's taking to the table, we need somebody to be able to cover the phones or we got to put somebody up in the office to answer the phones and all that. Just. Single unit, 2 million. $3 Million Dollar Restaurant. I mean, I think it's. I think it's easily six figures in savings.
[00:29:40] Speaker C: It's easily six figures in savings, but it's also, you know, we're showing. I mean, we have a. You just go to our website and look at the case studies and listen to what people say. Like, you know, we've got a guy in Texas that did the math. We're making him over $200,000 extra a year just by.
From the calls he was missing previously.
[00:30:00] Speaker B: Yeah.
[00:30:01] Speaker C: Like, he's a total AI nerd and he wanted to find the numbers. And we're like, go for it. He's like, we increased revenue over $200,000 with loan on the phone. And so it's just like the ROI is so obvious.
[00:30:12] Speaker B: Yeah.
[00:30:13] Speaker C: And it's all about. But it's only obvious if it works.
[00:30:16] Speaker B: Yeah. So on that $2 million restaurant, to the point, if it's $2 million restaurant, that's a, you know, 10% lift in revenue. And I think cutting labor by, you know, 100K even conservatively, you know, you guys, I think anybody here can do the math. I think it's. I think it's a meaningful number at the, at the end of the year.
[00:30:35] Speaker C: It's humongous. Right. Restaurants who are already running on thin margins, like, they need all the help they can get when they come to this stuff. And I actually think AI it's not, not just in restaurants, but we're talking about restaurants right now is going to help turn what is a traditionally low margin business into something that they can, you know, where the margins start getting really interesting when you're running a restaurant.
And, and that's by automating away a lot of the labor that traditionally just literally wasn't possible to automate. So it's exciting.
[00:31:08] Speaker B: Yep. I totally agree.
Any last words of wisdom for the folks listening in? Any advice, insights? Look in your crystal ball, tell us what we should be looking at.
[00:31:17] Speaker C: I would say that if you are an operator, operators are so busy and they don't always have time to take advantage of the tools. But if you are running any sort of business, and specifically a restaurant in this case, don't do yourself the disservice of being one of those people that's like, I hate AI. Like, AI is this horrible thing, like, give it a shot. And I'm not talking about Lowman. Like, yes, it could be low, but it could be our voice. AI, go use chat GPT. See how much of your, you know, put your menu in it and say, where can I optimize? You know, what am I doing wrong here? Here's my reports from Toast. You know, what should I get rid of? Right, You. If you're not embracing AI as an operator, you are going to fall severely behind. And now is the time. We're in the golden age of this stuff. Or not even I would say we're in the very first inning, you know, the very first pitch of the very first inning. So get on board.
[00:32:16] Speaker B: Yeah, I agree. I think the future is going to be divided between, between people who were scared of it, didn't understand it, did they? Was going to be here for a while and the other people who have learned it and are using it, bending it to their will. I completely agree. Yes, I am very excited in these areas because at the end of the day, I'm an operator at heart. I spent, you know, two decades, you know, working in restaurants on the floor, and I'm very excited for the tasks that I can take off our plate so that we can just do our jobs better.
The amount of time I've got to, you know, spend on the phones, the amount of time I've got to spend in the back office.
Right. So to your point, you know, reconciling inventory or running payroll, double checking this, doing the schedule, you know, running my forecasts, you know, building my budgets for the following month or the following quarter, you know, all of that, I'm very excited to see a tool be my partner again as an operator, so that I can just be super friendly and, you know, with the guests and for the guests and all of that. So I think that's where we're going.
But only the operators that see that as an opportunity and see that as.
As a win, win, I think are
[00:33:27] Speaker C: going to win 100%. If you don't. If you don't give the tools a shot, you're going to really miss out this time, that's for sure.
[00:33:35] Speaker B: I think the cost of inaction is so great and so deep, and I probably consume 10 to 15 hours of content just on this subject every single week, to say nothing of the time that I'm putting in to Claude code and, you know, building apps and tools for me, my team, my clients and other businesses. And listen, and I'm an entrepreneur at heart. So the other businesses that I'm gearing up to launch in the coming six months or so, it's like. And it's impossible for me to see it any other way. I think they're the people who know how to. Who are learning how to leverage this stuff and the people who are just burying their head in the sand. And I think it's very scary for the people who are burying their head in the sand.
[00:34:20] Speaker C: Yep, agreed. I think it's, you know, the. The biggest. I mean, it's hard to say because, like, the Internet was such a big kind of evolution in the way that we do things, but this might even be bigger than that. I think it probably is.
The way you can explain that is, like, tools that we used to use, like, helped helped you as the human, do the job a little bit faster.
AI does the job for you. Right? Like, that's how you can think about these things. And so it's. There's never been a more exciting time.
[00:34:49] Speaker B: I completely agree. Listen, Christian, I've appreciated your time. Thank you so much for carving time out of your schedule. Where do we send people for. To folks who want to go check out Lohman. Want to try the demo? What are the next steps?
[00:35:03] Speaker C: Yeah, absolutely. Come visit us on our website. Grab a, you know, set up a demo or just call our phone number. It's www.loman.AI. that's L.
You could try out our demo right then and there. You can call or text it. Right. There's a text agent there as well, and you can set up time to speak with us, get started. We could truly get you up and running in less than a couple of days if that's. If you're willing to do the work with us and it's time to start kind of, you know feeling those benefits. As a restaurant owner I guarantee call your restaurant right now a few times. You'll be probably get put on hold or not answered and it's time to time to check out Lemon.
[00:35:45] Speaker B: I love it. Christian, thank you very much. Enjoy the rest of your day.
[00:35:47] Speaker C: You too, Chip. Thanks.
[00:35:50] Speaker B: Once again I want to thank Christian
[00:35:51] Speaker A: for taking time out of his day to sit and chat with us again. I told you I don't think we were there yet but I think we are there now. Lohman AI is creating something really compelling. I think it's saving operators money and I think it's also generating previously unrealized revenue. Go through the demo. You're going to find the link in the show notes. Make sure to come back next time. I appreciate you guys making this show part of your week.
[00:36:16] Speaker B: I will see you later.
