Genetica is the Future for Business! Meet Sarah Kabakoff | Biz To Biz Podcast

Welcome to the Biz to Biz Podcast, your number one source for all business news.

Hey everybody, welcome to B2B Vault, the Biz to Biz Podcast, and I'm your host Allen Kopelman. B2B Vault is sponsored by Nationwide Payment Systems. Watch out for our new launch which is coming up, our NPS1 platform. And today we have a special guest on the show. All guests are special because it's always great to talk to other business people, entrepreneurs that come up with especially like all the cool products that we see coming out today that are using AI and technology that can help business owners streamline their operations. And today's guest, Sarah Kabakov, created a product called Genetica, and we hopped on a Zoom call a couple of weeks ago and I was like, man, this is a really cool product. And we need to tell people about it and get you on the podcast. So welcome to the podcast.

Thanks for having me. Glad to be here.

All right, so tell us a little bit about like the company and like why you started this, um, product and a little bit about the product.

Sure. Uh, yeah, Genetica is an AI company. Obviously we're in, you know, in the AI space, but unlike so many other AI companies. We're not just an LLM wrapped up in a wrapper and shipped off as AI. We actually have a lot of our own AI products. We specialize in ontologies, which— an ontology is like a system of knowledge. It's how the machine learns, essentially, right? It's, it's the structure of the data to explain the relationships. So it really helps the machine to understand what it's looking at, not just generalizations like a typical, your ChatGPT or your Claude, these large language models. And ontology actually gives a large language model context for the data that it's looking at. And, you know, we started Genetica, obviously, you know, to be on the cutting edge of what's coming in AI. In my career, I have very much worked on the cutting edge of technology and have enjoyed it. And, you know, AI, as most people don't even realize how much it's changed our lives. Some people do, but most people just don't understand the differences and the way the world's going to look in as short as 3 to 5 years.

So AI is like the biggest thing going. Anything, you know, you— everything about AI, you hear about AI every day, you know. So things are moving quickly in that technology world.

Yeah, 100%. It's been really fun and challenging to, you know, learn all these new technologies, and you feel like you're learning something, and then, you know, the next day, it feels outdated almost because the machine has leapfrogged you already. So it's been very, it's been a very fun adventure so far.

But I know when we were talking, you worked for a very large point of sale company before you launched this, right?

Sure. Yeah. My entire background has really been restaurants, point of sale. I was an owner-operator early in my career. I owned a bar from 2003 to 2006. It was a big nightclub. And then I left that business to go open a bunch of sports bars, did that, and then left that business to actually go start from the ground up in the point of sale business. And I started working for Aloha back in the day when it was still owned by Radiant Systems. And I worked for a reseller. And then we went through the whole NCR acquisition, became an NCR employee, was there for a long time, and then left for a little startup called Toast, uh, which was one of the greatest adventures of my life. So much fun. I was a very early Toast employee, spent a ton of time working with the product team to help design. Features and functionality inside Toast while also being, you know, first boots on the ground for the enterprise space and, you know, working Denver West for Toast. And I remember when everyone would tell us, how do I even know Toast is going to be around? You know, and of course now Toast is the largest restaurant tech platform in the world and happy to have that been part of my journey. And then most recently, I helped build another point of sale company called Dutchie, which is basically, you know, the largest that the toast of the cannabis industry. It is the largest point-of-sale, um, company in the cannabis industry. And now I left, uh, Dutchie to come over to Genetica, uh, because I really think AI is the future. I actually met Genetica in the partner channel of Dutchie because I ran the partner channel there, and what they were doing was just so impressive that I needed to be on the team. So I came over as a, you know, an early executive here, and, um, You know, we really specialize now in working with point-of-sale data both across cannabis and hospitality.

Yeah, it's interesting, we both share that— the fact that we both come from the restaurant business, because that was my background for 20 years before I got into payments. I was involved in food and beverage. I was a chef, executive chef, corporate chef, owned a restaurant. So it's always interesting, like, to talk, see how many people go from, like, hospitality industry industry and then end up in tech because there's just so much going on in hospitality. And then tech seems to attract a lot of people.

Yeah. I got to tell you, I really miss my restaurant days at times. It's hard work. It's really, really hard work. So hats off to everyone who is grinding in the restaurants today. But it was some of the funnest times of my life getting behind that line and just getting absolutely crushed with a rush. And that was some of my favorite times. I really enjoyed all the jobs that I've worked in restaurants all the way from dishwasher up to district manager. It was some of the most rewarding work I've done in my career.

Listen, the hardest working people come from the restaurant industry. When you work in that industry, restaurant, hotel, bar, nightclub, whatever it is, those people know the meaning of hard work and a long day. Yeah, it's, it's definitely interesting. So tell us, like, I know you mentioned also we don't get too much in there. We can get into like cannabis and restaurant, but specifically, like, how does this software help these businesses? So let's dive into that. Like, so how does, how does, how does Genetica help these business owners with their business?

Yeah, so I think it actually we can actually step back before the AI even gets involved and we start seeing value. Today, even really advanced enterprise customers struggle with getting all of their data into one place and making it easily accessible. And even if you do manage to get all of your data into one centralized location, you can't just run reports off of it. You typically have to have an analyst that you go and you ask for this report, they have to go search the data, run a bunch of joins, figure that stuff out. It takes a day. Sometimes it might be the same day turnaround. Most of the time it's a 3-day turnaround to get those type of reports. So even with the most advanced companies, just centralizing your data into one place is such a value. So before we even add and layer in the AI, one of the things that Genetica does is we take all of your data and we put it into a central location. And the real differentiation between like your typical data lake and something that's AI ready is the type of data, the type of format that the data goes into. So in our world, we're putting it into a graph, right? And that graph allows the data to sit a little bit differently than it would in a typical like rows and columns type format. So it allows you to really have a good understanding of how that data sits in multi-dimensions because the data's attached to each other and it all kind of sits in the same place in a graph. So you're not saying I'm going to go to this line and this column and I'm going to get this piece of data and then I'm going to go to this line and this column and I'm going to join these two pieces of data. They just exist together in the graph. So when we start thinking about ingesting data, not only are we taking, you know, maybe your POS data, but maybe it's also your OpenTable data and then it's weather data, it's census data, it's traffic data, it's events data. And so when a transaction happens, Most data lakes that you think of today can tell you that a transaction happened at this point in time, but it's not going to tell you why that transaction happened and what was going on around that transaction that might have influenced that transaction. So, you know, when we pull in the data and we prepare it to be ready for AI, we're setting it into a different format that just inherently changes the nature of that data to allow AI to understand it. And then you start adding in the ontology to help the AI understand who is asking the question, what's the context for their job, right? Because we want to ingest all of your SOPs, we want to ingest your job descriptions, we want to understand those things so that we're giving a full picture of what the data looks like to a CMO versus a CFO versus the CEO, because they all want to look at data a little bit differently. And a typical data lake that people think of today doesn't provide that. It just doesn't give that inherently. So you have to have a human in the loop that then goes in and decodes that data and says, okay, what might this person want? What can it learn from you? It can learn about you, and then it can start presenting data to you in the way that you want to understand the data. So it's really interesting.

It's interesting, you know, how, you know, you want to get like— we were meeting with a point-of-sale company yesterday, and they were the person who was doing the demo. The people who were getting the demo were like, oh, the owner wants this kind of report, the CFO wants this this kind of report. The manager needs this kind of report. So that's really interesting. And you mentioned weather, you know, and that's kind of crazy because, you know, when you think about it, I remember making budgets for hotels, and we would make a budget for the hotel, and, you know, we were sitting down, and then, you know, after they put, you know, everything together, like, okay, now we got to mark in all these holidays, and then we got to mark in this holiday, and then we got to go Okay, the weather. And I was like, the weather? What are these guys talking about, the weather? And I was— I couldn't understand. They're like, well, you know, it's going to be cold outside from here to here, so there's nobody going to sit on the patio. You know, people don't think about like that deep into like, oh, why did we only serve 300 people this day and this other day 3 months later was 500? Oh, well, there was— with the patio open. You know, and it's crazy how all of that plays into, you know, what's going on in a business.

Yeah, when I was running restaurants, you know, one of the very first things that I would do anytime I was writing a schedule is I'd pull up the Red Book from last year and I would go look and see, you know, what, what happened last year. Was it rainy outside? Was it warm? You know, was there a busload of people that pulled in? So I would need to understand the context of what's happened, and then I would need to look in the area to understand, like, Hey, Friday night, is there a high school football game? Because if there is and I'm close to a high school in this location, I likely need more people on staff. And not only that, knowing that schedule would help me to go and work with the local high school to market to those people to come to the location that I was running afterwards to come grab some wings or run a Friday night special. Right. But that took me being very active and diligent to understand what was happening around me in order to properly build those schedules. And then if the forecast changes, is I'm building the schedule and now it's going to rain. I now need to cut servers. What's the right combo of servers I should have on to maximize my value? Like, all of these things are things that I would have to be very aware of in order to accomplish. With AI, it gives you the suggestions, you know, it'll say, hey, there's an event coming up that's within a certain proximity, and historically when you see these type of events, we see this type of rise in foot traffic. Oh, and by the way, it's going to be really nice. And so typically when the temperature is above a certain threshold, you start to see this increased foot traffic. So you might want to pay attention and adjust your schedule based on these things. And it takes the data, it reads it, and it gives you an actionable way to make the data work for you. It's not just, oh, I have to think about this. I've got to spend time doing this. I've got to hire a person who specifically goes and looks at all these factors. No. Now you have the AI 5x-ing your workforce and doing that work for you and helping you understand. And then you take it a step further and understand competitive pricing on happy hour or your menu items.

And you can— I thought that was really cool when you showed me that in the demo. I was like, wow, we used to have to send people around to the different restaurants and collect the menus, you know. So that's like amazing to get that information.

Yeah, I used to do the same thing. I would, you know, on a slow night, I'd send my managers around like, hey, here's $20, go down to the bar and, you know, check out what's going on down the street, see who's down there, you know, are some of our dealers down there? Are they running a better special? You know, how do I understand that stuff? And, and now with so much data available online and so much data available because we as humans create all this data and publish it online, we can now go and scrape that stuff. We can understand based on social media who the influencers are and where they're driving people to, what cuisines are hot, what seasonal flavors are hot, all of that stuff. Just really amazing tool.

Yeah, restaurant, you know, restaurant owners typically, I would say, are not like crazy about— they have their idea, this is what I'm doing, you know, and they— and sometimes, you know, you don't see that flexibility, especially like I watch like Hell's Kitchen or you watch, you know, Restaurant Nightmare or whatever show you're watching, you know, and, you know, the amount of— the amount of actionable information that you can get out of AI, even for my business, we can go on ChatGPT And now have like a research tool just like what you're doing, right? And you could go, oh, here's 3 point-of-sale systems. Give me, you know, a research paper comparing these 3 systems. You know, in a restaurant using your software can go, oh, tell me about all the happy hour specials within 10 miles of my restaurant. You know, yeah, that's, that's just crazy. And then you have sitting there and whatever and how, you know, however long it takes it to do it, probably maybe up to an hour. Boom, you have a report in front of you. Now you go, okay, maybe we're a little overpriced. Maybe we're not doing the right thing. Maybe we need— everybody's serving the same thing. Maybe we need to mix it up and change some menu items and put some new, new different foods out there that people want. You know, it's—

yeah, it's typically seconds to minutes as opposed to an hour. It's just so quick the way it can go out there and gather all that information. And the other really great thing about AI is, I mean, besides the competitive information, the third-party market data that it can go out and bring and, you know, append to your first-party data, it also gives you the ability to understand your business in different ways because you can ask in natural language what's happening, right? What are the factors that are affecting my business and what are the things that I want to know about my business? That I traditionally would need to spend a lot of time researching data. A great one for restaurants that take reservations is just recency, frequency, and monetary spend. How do I connect that reservation data to the POS data? And even a lot of the POSs that have an integration with something like an OpenTable, like, you don't get that robust of data in there. So you still have to go download both sets of data and then do your best to match that, to understand that recent frequency and monetary spend. Whereas with AI, now we can have the AI do that work and then we can just talk to it in natural language. And some people use ChatGPT and they may upload their data to ChatGPT and there's nothing wrong with that. That may work for some people. The problem is that LLMs and stuff like ChatGPT, they don't learn from your data the same way that something like what, how our system will, because the ontology isn't there. The machine doesn't understand what a piece of pizza is, right? And you think like, oh, it's just a piece of pizza. But from a data standpoint, that piece of pizza is an item number and it might be sliced pep, half pep, whole pep. What do those things mean to the machine? It has no idea because it doesn't have an ontology to explain to it what a piece of pizza is. It just sees sliced pep number 1, 2, 3, 4. So you're not going to be able to get real insights from something like a ChatGPT in the way that you would be able to get something from our system. And we've also spent a bunch of time hardening the math because ChatGPT and LLMs, the reason why they're not good at math is because they predict what 2 2 equals, right? They're not actually adding 2 2. They're saying this is what 2 2 should equal. Well, it's usually not correct, right? So the math part is very hard for these machines and some of them are getting better at it. But what we can do is we can take that information and we can turn that natural language into a SQL or a Cypher query query depending on what's, you know, called for at the moment. And then we can use that to be able to route it to the proper location. Because, you know, LLM, and, and that's just one of the tools that we might use. You can imagine our AI is sitting behind a desk with a group of tools in front of it, and then your, your input tells it what tool to pick up and plug into the machine, right? So it understands through its knowledge map what tool it should be picking up. It picks up that tool that's appropriate for that request and plugs that tool in in order to get the answer to feed you back the correct answer to your request, not just what it thinks it might be or what people call hallucinating, right? That's what— that's when an LLM or when AI makes something up, it's hallucinating, right?

Oh yeah. We talk about that. I've talked about that with people all the time about you know, what are you really getting? You got to really read it and see like, what are, what are you really getting out of that? So when people are, you know, I always know this from when I was in the hotel business. We were one of the first hotel companies to have like inventory and actually like live inventory and live data numbers for our labor expenditures and, you know, how much income was coming in and all that. And I know that when you're managing those your key numbers, labor, food cost, you know, you know, when you're managing that, you know, you're, you're running a more effective business and you're, you're run, you know, you're able to stay on target, you know, and keep your numbers. So when, when restaurants are like a dispensary is using like these kinds of software, what do you see like typically like You know, you have to spend— you know, I always tell people, like, you know, tools like a point-of-sale system or a tool like this, these are tools and you have to put time in and you have to set it up. And then once it's set up and you start using it, it really starts to save you like a ton of money because it's analyzing like, oh, when are you busy? Oh, well, you don't need 7 people here at 10 o'clock in the morning. You're not busy till 12. You know, so, you know, maybe half of those people need to come in and the other half comes in an hour later. And you really have to learn how to use these tools so that you can be more effective in scheduling, more effective in buying. And, you know, today, you know, we have a crazy economy. Everybody wants to save money. So what, like, from a savings standpoint, I'm, you know, I'm sure, you know, I don't know the cost. We're not discussing cost today, but You know, I'm sure that this basically pays for itself.

Oh, in so many ways. I mean, you can tie ROI back directly to amplification of work output, right? So, you know, especially as groups grow, you know, they need to hire business analysts. And look, we're not using— we don't think of AI as replacing people. We think of AI as augmented intelligence and being able to amplify the work that someone's doing. So as you grow, instead of needing to hire 2, 3, 4 business analysts just to run reports, understand your business, and dive in deep, we can now take that one person, give them the proper tool, and amplify the work they do times 5, right? So we're saving you payroll there. You know, we're saving hours of time for the people who are doing the work. And, you know, a lot of times you have to create a help desk ticket. Oh, I want to get this report. Here's my help desk ticket, then IT processes it and then assigns it, and then someone goes and builds it, and then they have to return it, and then you have to do iterations of that report because it's not exactly what you want. But we've changed all of that because now I can wake up in the morning and I can be on my phone and I can just ask the machine what I want to know, and it goes and it pulls all the data, does all that work for you, returns that report, and then if you want to save it, I can actually just pin it to a dashboard and create my own dashboards right from a natural language speaking into the machine. So there's direct ROI there. You know, it can do— there's so much that it can do that sometimes it can be overwhelming. And that's one of the areas where I think people get a little overwhelmed by AI because it inherently can just do so much, right? It can write marketing copy, it can search the web for competitive data, it can build you reports and dashboards and all these great things. So, you know, where do you start? And, you know, the savings, I think, as you grow and learn to use the tool, the savings become more and more apparent in the amplification of the work that your staff is outputting and the reduction in hiring that you need to do long term because you're able to get more with less. And in today's society, in the direction that we're heading and the cost of everything, you know, labor is just so expensive. So being able to optimize your labor spend, being able to optimize the home office to spend to be able to, you know, make those employees superpowered is really what's going to give you that competitive edge that you're going to need to continue to thrive in today's economy.

Yeah, one of the things that I've said many times over on the podcast and articles that I've written and in talking to people is AI is not necessarily going to replace people, but people who know how to use AI are going to replace people who don't know how to use AI. So it's super, super important. I I tell everybody, get a paid account on ChatGPT. Start somewhere, pay for it, because when you're paying for it, you're, you're that— whatever you're doing on there, right, in that AI tool, it starts to know what you have. It's, it's like learning about your business or what kind of blogs you're writing or what kind of copy you're writing or what the tone is that you want. And the same thing, like, with using Genetica. It's learning about your restaurant or your dispensary and what's on your inventory. And hey, you have a bunch of steak and it's not selling. So you're going to either be throwing this steak out or you need to go run a special. You know, you need, you know, a lot of people don't, don't use, you know, you have to put these tools to work. And, you know, people that know how to use AI are going to be do very well in the job market. I mean, I was reading a thing where people who like a new job is AI prompt writing, right? How to write prompts for AI is like a job now. I mean, that's crazy. That's a job.

Oh, oh yeah. I mean, the more effective your prompt is, the more effective your answer is going to be, right? I can see it in our own user base. I see people and I watch their journey because we can see every single thing that someone puts into the system. We watch how the machine thinks. I've got one guy that just monitors that all day long. And goes in and helps the machine to understand where it got things wrong, right? So that we can refine that, that output. And I can watch users come into the platform and ask really basic questions and then kind of struggle a little bit to understand how to ask the next question, right? And I watch them grow and I watch them really understand how to talk to the machine and to get really, really effective answers, especially on inventory levels. What's going bad, how they should be thinking about moving their inventory, labor, how they should build their schedules is a really big one. I've seen recently, I've started seeing people looking for combinations of employees that are most effective and asking really advanced questions to understand, you know, how fast and efficiently people are moving the guests through the experience and like what combos of people are most effective at doing that. And it's been really fun to watch the growth of our user base.

Pretty crazy to see that. That's pretty crazy to see that. I remember running reports. We would run reports on like in the hotel, in the fine dining restaurant. Okay, which waiters have the highest sales? How many people did they wait on? And then we would see like, okay, well, Jim, this guy's kicking butt. And then we have, you know, John, he's not doing— he's not doing any upselling, whatever. We didn't have John work with Jim. So he can learn whatever Jim is doing so we can get this guy's sales up. And, you know, having, you know, that's just basic point of sale. Now we have this point of sale with AI. It's on steroids. And I mean, you know, this is a great product. And I think a lot of point of sale companies are probably going to want to license this type of product into their point of sale system. Or you're going to end up selling to restaurants directly and just have a list of integrations at some point.

Yeah, we're doing a little bit of both right now. Actually, we have both models. We have where point-of-sale systems can either use an SDK and they can build an experience into their system and do like a Chat BI type tool, or they can snap our entire product in if they want to use the agents and they want to use the dashboards and, and all the things that come along with it. And we've got some customers in Australia and Germany and here in the US that are all doing different flavors of that. And then we also have direct restaurant customers as well. We have direct retail customers as well. And, you know, we see both ways of it going. I actually really love selling to individual restaurants myself, you know, groups of restaurants, because my passion is there, right? I understand it so well. So, I love seeing the efficiencies and watching them grow and watching them be successful with the tool.

Yeah, it's a really great tool. I mean, I tell everybody, you got to start experimenting with AI because AI is the future. This is what's going to be, you know, people are going to have to know how to use AI. 5 years from now, it's going to be on the resume. It's going to be like on the thing. Do you know how to use AI? Do you know how to use AI? It's going to be like a job requirement within the next 5 years. Every job.

100%. I'm in the middle of hiring some people right now. And one of the biggest qualifications is, do you know how to use AI? Not just because we're an AI company, but because we use AI to code, right? We use tools like Cursor and Klein and RuCode and these type of bots that will help us to write our code. And, you know, we have our coders spending more time debugging and working through and using the machine to amplify their output, right? And it allows us to move so much faster, you know. And when people— I show people things and I'll say, oh, you know, this is on the roadmap, that's on the roadmap. And they'll be like, oh, okay, well, when's that coming? Oh, the next 60 days. What? Yeah, and they're blown away. I'm like, yeah, what used to take months now takes weeks because AI does half the work for us.

Right. Yeah, it's crazy. So if people want to find more about Genetica, they go to getgenetica.com, right?

That's correct. And they can also go to demo.getgenetica.com and they can actually play with the tool live. You just have to punch in your email, it sends you a link, and we actually have a walkthrough on there and everything. I'll tell you how to use the tool, and then we just give you access to go in there and play with the tool and check out the results. There's all the data that's in there is real data. We've had to hide PII and stuff like that so that we're not showing off customer names and giving out private information. But all the data in there, if you go and you look at how our agents run, if you go and look at, you know, the some of the reports that are in there, all those things are real data. And if they're interested in having a further conversation, we can actually give them a live demo and we can have them ask specific questions that they might want to ask to be able to see the machine in action. We can run agents for them to have them understand the sentiment of their own business right there live. I can't tell you how many demos I do, and I run a sentiment analysis agent on someone's business and they're just blown away by the results. And so many times, you know, there's areas for improvement that they didn't even know were an area for improvement. Because they weren't searching forums like Reddit on a regular basis.

Right. Yeah, it's amazing the information that you can get using this AI instead of sitting down, like sitting down and doing all this, you know, paperwork and going through all this stuff and spreadsheets and this and that. What used to take days can just be done in a few minutes. It's literally amazing. And then you can, you know, make better decisions, quicker decisions. And things like that. You know, I used to, you know, I tell people like one of the books that I like is Mel Robbins wrote this book, you know, 1, 2, 3, blast off, whatever she used to say. You know, you just count to 5 and go, you know, you don't need to sit around and, you know, marinate over a decision. You know, you can get— you don't have to go, oh, where am I going to get all this information from? Now you can use this AI tool. Get all your data in there and make and learn how to use it and put together and make good business decisions and make them in less time, less effort. You don't have to go send employees all around to all the restaurants to collect menus. You can be collecting all of that online, not by sitting there typing, but just punching it in and getting the actionable information.

I think You're 100% correct. I think another big value prop too is, you know, we all have that one key person who when they leave, we're lost, right? It's that person who runs the reports, knows the data, and then they end up leaving the business. And then you're like, where do I go from here? And then you go hire someone and it takes them 4 or 5 months to ramp up before you're back to where your production level was. Well, with AI, AI doesn't quit. Right? It doesn't leave. It doesn't go find another role. It just is constantly working for you. It's on 24 hours a day, right? I can wake up in the middle of the night if I can't sleep because there's something bothering me about my business, which we've all had that moment, right? I can't sleep. This is keeping me up at night. Now I can roll over, pull up my phone, and talk to the machine about it. And it is a, you know, it's a a master's degree, PhD-level intelligence that can tell me about my business and answer those questions that are keeping me up at night so I can rest well. And that alone in itself is worth the ROI, right?

So when merchants, like, when they batch out, is that— and there's like a report produced by the point of sale, is the AI sucking that in and then analyzing it and then sending everybody an email too? Like that?

It sure can, if that's what you want it to do. You can set up alerts for anything inside there. You can set up agents and alerts that just watch for specific things. Like, um, one of our customers has an agent that just watches for, uh, comps over a threshold of revenue, and as soon as comps hit a threshold of revenue, it starts to email the people who are in charge of that particular region and starts to alert them. Any of those type of things, too many transfer checks by a server. Like there's all kinds of things that you can monitor that just trigger those alerts. And certainly if you're, you know, if you want to set up an alert that, you know, once you batch out and ingest the data and then it can send that report that, you know, hey, here's these transactions, here's what happened, here's the things you need to pay attention to. Oh, and by the way, here's an explanation of what's likely there. Oh, and by the way, here's an action. Do you want to send this to,, you know, Bob or Sally, whomever, to be able to solve this problem or take a look at it or give you more details, right?

So I really appreciate you coming on the podcast today, Sarah Kabakov from Genetika. Check out their website, getgenetika.com, and the demo.getgenetika.com. Go check out a demo. And if you have a restaurant, bar, nightclub, got a cannabis business and you're looking for a better way to manage your data and get more analytical information, this is definitely the future of data analytics. I have not seen anything remotely even like this, and I get contacted constantly for people to come on the podcast. So, you know, I try to get the coolest products and this product definitely hit the cool level.

So I appreciate that. My, my team works hard at this. You know, we had, we had a dream and some really, really talented team members, and we've been able to accomplish a ton. And we're really proud of what we're building. And we really think it's going to help, you know, restaurant owners thrive.

So, so check out the podcast, B2B Vault, the Biz to Biz Podcast. We're on YouTube, we're on LinkedIn, we're on Facebook. We're on Spotify, Apple Podcasts, wherever you listen to podcasts, we're there, whatever app you use. And YouTube, you can catch the video. And again, thank you for Sarah for coming on the podcast today from Genetica. Everybody have a great day. Carpe diem. Peace out.

Thanks so much.