AUTO-TRANSCRIBED – PLEASE FORGIVE ANY TYPOS OR ERRORS
Aaron Spatz 00:00
You’re watching America’s Entrepreneur on Youtube. Welcome to the show. I’m your host, Aaron Spatz. And each week we interview entrepreneurs, industry experts, and other high achievers as a detail their personal and professional journeys. Before we jump in, hit the subscribe button and be sure to hit the bell icon so you’re notified every time we release a new episode. Thank you so much for tuning into America’s entrepreneur this week, we are just so delighted to be able to continue to bring such such amazing guests. So technology continues to be a chief concern for a lot of businesses, a lot of even a lot of entrepreneurs, right. There’s a ton of tech startups out there. There’s a ton of technology being developed every day there cybersecurity related concerns. There’s there’s a whole bunch of things out there as it relates to technology. And so I’m really excited to welcome Ted Willis to the show. Ted comes to us with a with a really interesting background. But most recently, he spent the last 10 years as a founder of NLP logics. And NLP logics is an artificial intelligence machine learning solutions company. So that’s about the extent of my depth of knowledge on those topics. I’m gonna let him do all all of the explaining. And we’re gonna get right into it. So Ted, I just want to welcome you, sir. Thank you so much for making time to be with me today.
Ted Willich 01:10
Yeah, thanks, Aaron. Thanks for the opportunity to talk to you and be on the podcast.
Aaron Spatz 01:16
100%. So like, let’s let’s let’s go right for it. So you and I share the common bond as US Marines, but like help everybody can understand you know, where you’re from, cut a little bit of your story. And then what, what excited you are what inspired you to get started in the business world?
Ted Willich 01:35
Yeah, so the, it all started. So I grew up in in Southern California, I grew up in a place called Mission Viejo, and had an extraordinarily good time in high school. And my grades reflected that. And so the only college that would accept me on probation was Ripon College, a small school in Wisconsin that my dad got to they had to take me because I was a legacy. Right. And so, yeah, so I majored in history and was able to squeak out a, a Bachelor of Arts. And of course, a history degree is also known as pre infantry. So I then went and went through the peace PLC program there in Quantico, and to become a Marine officer and squeak squeak through on that as well. And then commissioned and served as an infantry officer from 88 to 92, was headquartered out at Camp Pendleton. And loved it great friends, you know, how it is right, Aaron, you know, lifelong friends, great experience. Yeah, got out in 92, and then co founded a company with Baghdad, that built hospital and physician networks, for groups across the country, and it grew very fast. And we were headquartered up in Northern Virginia, and then moved down here to Jacksonville, Florida, that’s where I am now down here about 18 years ago, grew the company big and then you know, decided that I wanted to, you know, go off and give it a go on my own and the last few years, at the previous company, we’re doing a lot of work with machine learning to automate internal processes, and the and so God just kind of enmeshed in that saw that the future is there’s a big future for this machine learning AI stuff. So we started this company, and we build solutions for companies to automate tasks. And so the elevator pitches, we teach computers to do what humans can do, or would want to do. And and that’s kind of been the been the journey. And yeah, that’s been been pretty cool on on all those fronts had a lot of fun along the way.
Aaron Spatz 04:02
Yeah. Well, it’s, you have a really unique position of perspective, because you grew up in a family where business was like, was a part of life. And so share with me a little bit about that, where, you know, your your father doing what he was doing, and bringing you into the mix of all this, like, what was that like, like, and how much of an impact would you say that that had on you going forward?
Ted Willich 04:24
Yeah, no, not a big impact, you know, growing up, um, you know, seeing someone build companies and I always thought that’s how that’s what you did, you know, it was always the kind of the way of the world and, and so it never fazed me to worry about starting a company. I just thought that’s what that’s what you do. And the one coachable moment people say, well, when did you know you wanted to get out of the military? And you remember those cards that used to give us air and every year that had to pay rank? What you were gonna make? Yeah, whatever. Everyone flips it over and looks at what the top general makes, right? And it’s like, the one thing I remember looking at that I’m like, oh, I want to do better than that, like, I want the opportunity. I may not, but I want the opportunity to do better. And so, so that’s certainly contributed to it, as well. And the people have asked kind of how a history major infantry officer, etc, got into, you know, high tech and technology. And it’s really get that goes back to the Marine Corps as well. And if you remember, right before Desert Storm, the, you know, the maps that they had of the desert was featureless, like you didn’t take it was useless. Right? Right. And then they, they flew these magic boxes to our unit, that we didn’t know what it was at the time, but they call the GPS, right, the Trimble trim packs. And it was like, just Yeah, was like a big thing. I was like, Oh, my God, look at the impact Tech has, you know, before, you know, it’s, there’s a huge multiplier, right? So ever since then, I’ve read, read everything I could about technology and emerging stuff and everything. So that’s yeah, kind of where it is today.
Aaron Spatz 06:15
I gotcha. Okay, so, so what I’m seeing and what I’m kind of detecting as you’re talking is, like, there’s like this convergence of a lot of different things. So one, your, your early exposure to technology and, and a prep, not just a technology, but a practical application of that technology, on, you know, on the battlefield, or it could be anywhere, but that was where it was for you in that particular instance. And then with your, with your growing up in business, as you’re talking, I was thinking like, well, this is a guy who grew up in an environment where not able to do something just wasn’t like, wasn’t considered it was like, nobody told me I couldn’t do business. I just, we just continued to go that way. And so it’s like, you didn’t know any better. And, and, and like, that’s awesome. Right. And so that kind of helped you kind of think in terms of, you know, business ownership, and and just all the skills that that no doubt you’ve you’ve acquired, and you’ve honed, you know, over the years. And so tell me then, like, when you went to go launch, you know, when you went to start NLP logics. What is the startup process for you? Like what like, was this a capital infusion? Required startup was a bootstrap? What like, what, what is going through your brain, I guess, in terms of founding a company, knowing all your background, but like, where did you put your focus and your emphasis in terms of work that need to get done.
Ted Willich 07:43
So once we decided on the business plan, and that part was relatively easy, then it was just, you know, we always knew we were going to bootstrap the company, okay. So, you know, drain 401, K’s drained insurance accounts, strain, whatever. Just to kind of get things going. Once we really solidified the business plan, started to get those first one or two customers, which, which, in my opinion, is the hardest thing to do in a startup is just get customer number one, like, so difficult. And so started getting one or two customers, we didn’t have enough capital. So we went out and raised a very small amount from some angel investors. So we’ve raised less than, you know, 375k, and that was, you know, 10 years ago, which isn’t a lot of money. Like, that’s, that’s not a big, that’s like a runway for a CH 46. Right, that’s not very long. And so, um, I guess they probably don’t fly those anymore. But the and then once we got that we just started getting, you know, kind of more and more momentum. And now today, we’ve got, you know, over 60 employees and, you know, 50 customers and across the US and expanding overseas a little bit now. But yeah, just took it was just getting that breakthrough period, the first couple years really, were not fun. It was it was difficult, you know, probably took us close to five years to just break even. And that’s, you know, that’s difficult, but I just keep getting it out. Right, you know, yeah.
Aaron Spatz 09:28
Well, like that’s, that’s an important truth and lesson, I think, for a lot of entrepreneurs to understand. And it’s just, it’s something that like, resonates with me, but I don’t resonate with a ton of people that have been in this journey, to some extent. It does. It can and it does take time. It’s not it doesn’t often just, you know, launch rapidly on day one is like, it takes some take some time to build some some momentum so, and those early days for you. I imagine I could be wrong, please correct me if I’m wrong. But I imagined that the bulk of your work efforts were centered around acquiring customers. I mean, it’s like you need the customers to keep going. But while you’re doing that, I’m sure there’s 100 other things going on behind the scenes as well. So how do you manage that? How do you multitask? How do you get the right people around you to help you with all that?
Ted Willich 10:19
Yeah, well, first of all, the we started the company with, with two other co founders, so Robert Marsh, and Matt Bursa, great guys, you know, they, they are there, and we’re there to really be able to deliver on the technology side. So they’re both brilliant technologist. So it wasn’t by any stretch, it wasn’t just me, it was it was us, as a team, and just really working hard together to get this thing off the ground. So having, you know, very good, you know, aligned partners is, is very, very important. And that that really helped. And the, you know, and then once getting the clients, it just kind of it just kind of rolls from there, right? You just You just kind of figure it out. And, and having a lot of experience helps, you know, obviously, because you’re wearing a lot of hats, right? Your legal, your HR, your, you know, you take out the trash, clean the sink. Oh, the so having that. Having done that once already did obviously was a real big help. Yeah,
Aaron Spatz 11:31
for sure. So what So what was the specific product or service offering that you were that you’re offering these, these first few customers? Like, what? What are you guys working on?
Ted Willich 11:42
Yeah, the. So maybe again, go back a little bit, I’ll tell a little story of the genesis of the company. And then it may make make some sense. But the, the genesis of the company, actually came from a predictive modeling contest hosted by Kaggle. It’s K GG le Comm, which recently was bought by Google. And that’s kind of the Coliseum for data science. And companies and governments and other entities would put up cash prizes, and then they would put up large amounts of data. And they would say, if you can solve this problem using this data, and you have the best solution, then you get cash. And so Matt, or Seth or one partner started entering into the contest, and the first contest was to given all this information in electronic health record, identify which patients have undiagnosed type two diabetes, and he ended up winning, and we’re all excited, we’re like, Oh, that’s great. And we’re gonna, you know, sell it to electronic health records. And where do you go after that market? And Matt’s like, he’s like, no, no, we can’t. He said, Because the machine learning model that we built, was designed to win a contest, it wasn’t designed to be put into production. So you, because the algorithm in the model was so complex, just the compute power, renders it basically useless. And that’s when we saw, we felt like that the market is going to need a solutions company to actually be able to fit the model or build the predictive model, and then ultimately put it into production. It’s that second step, that’s actually the hardest part. And everybody kind of focuses on the data science side and the, you know, building a really cool predictive model or some other type of machine learning solution. But this is really the hard part is actually getting getting it out there. And so that’s when we changed our business model. And the instead, we’re going to do machine learning as a solution. Our first customer was an automotive marketing company, here in the southeast. And we built response models that if you send someone a, a coupon, or a postcard or whatever, what’s the probability that they’ll respond and come in and get a lube oil and filter or get some other maintenance thing? Now understand, this is across, you know, hundreds, if not 1000s of these different stores. So very large amounts of data and everything. And that was that was a success. Second customer who was a circuit board manufacturer in the UK, and they were, they wanted a what’s called a churn model. So given all the data on specific clients, which clients have the highest probability of leaving, just based on signal that’s in the data. So that was our first kind of international foray, and then our big break came with two clients. One was the Florida poison Information Center Network. where we built, it’s a statewide, it’s still there today. But it’s expanded to like 14 Other poison centers across the US where we have algorithms running on the back end of their systems looking for outbreaks of different things and substances and poisonings and everything. And then another big break was with the energy trading company, up in the northeast, buying and selling megawatts on the grid, basically, using algorithmic traders and everything, so, so and then ever since then, it’s just, it’s just kind of really starting to take off now. Because there’s really cool, yeah, there’s, there’s a ton of demand for this stuff. And there’s not a lot of companies with the experience that have actually done it, because there’s a million pitfalls, you know, along the way that we have certainly fallen into, I
Aaron Spatz 15:48
can only imagine. And I think like, problem number one, and again, this is this is like with a totally green perspective, like not knowing next to anything about this industry, is just getting your hands on the datasets themselves, like the data sources. And so like, if, if I’m running a company, I’m probably highly unaware, generally speaking of, of maybe various data sources that I already have access to, or that I already that already, that I can already touch. And so how do you help companies discover like, like, man, you’re sitting on top of a mountain of data right now. And you don’t even realize that like, Where Where does that come from?
Ted Willich 16:25
Yeah, that’s, that’s a very good question. And it’s, it’s really, our approach with our, with our customers, is we’ll do usually a 45, to 60 day discovery period, where we’ll go through and we’ll crawl through which data, you know, what do they have, it’s always siloed, it’s always dirty, meaning there’s just got to clean it up and everything. And then we’ll also, you know, what is it that you want to optimize? What do you want to Automator? And? Or what do you want to analyze, ultimately, and so, we’ll, we’ll do an inventory, and let’s just say, you know, they want to, you know, they want to build a predictive model to, you know, drive email campaigns, right, so they want to email offers to all of their clients and, or existing client base. And so, you know, you collect all the information. So you usually have, you know, a named really don’t matter, you know, the machine doesn’t matter what the first name last name, so we usually get rid of that. You know, we’ll want to do things like, Do you have their address? And if the answer is, yes, that’s great. Because not only can we use internal purchasing type data, what they bought when they bought it, we can also geo locate people to a US census. So now you’re pulling it average homeownership, you know, average number of kids, and you know, average income, all the stuff that’s in the census. And so you can start to pull in these different data sets. And at that point, you’ve got a pretty good view of what people you know, what people do, and or how they purchase, you know, Amazon’s obviously perfected this, right? You bought this? So you might want this, right? That’s a suggestion engine, and that is a machine learning model that based on your purchases, and they’re usually pretty accurate, right? Yeah.
Aaron Spatz 18:22
Wow. Yeah. Cuz I’m thinking, I’m thinking of like core logic when it comes to like housing, statistics and things like that. So like, there’s just, there’s a ton. And so I imagine for a lot of companies, it like this, this may or may, again, please correct me, if I’m, if I’m speaking outlined here, but like, there may be companies that this doesn’t really apply as much, because they may not have a ton of data that they that they work with. But then there’s other companies that I mean, their CRM is just like rich with just terabytes of data that you can extract. And so I’m just thinking of all the different various data sources that you’re able to pull from and then, I mean, really, where the magic happens is like you’re taking all these various data sources, pulling them together and coming up with some, like really amazing insights and actionable insights rather for, for what a company can do with that, right?
Ted Willich 19:11
Yeah, no, you’re you’re spot on, you know, the companies that that don’t have a lot of data will usually say, Okay, for the next six months, start collecting this, you know, and then after, you know, after X number of months, you usually have enough that you can get a rudimentary solution out there kind of a stopgap Gotcha. Um, the other thing companies should be looking at is data around repetitive tasks that their employees are doing. So if if they’re doing, you know, clicking through and I’ll just use an example of, you know, like loan documents, you know, if you have human beings looking at something in an image, like a PDF or something like that, and then they’re typing it into Another system, like that’s right for automation, you know, or if they’re clicking things. So one of our customers is a very large medical record coding company, okay? And their medical record coders have to basically VPN into an electronic health record, go through the clicks, and then and then log out, do the coding log in, enter the codes. And we’ve automated that whole process so that they don’t do the clicks and the machines do the, the work on that. And so there’s just, yeah, it’s great. Like, when you start looking at companies and seeing how they do stuff, you’re like, Oh, my God, and the ROI like, is usually pretty easy to quantify, right? Yeah, I’ve got 50 people doing this. And I can get that down to 10. People, you know, you do that math?
Aaron Spatz 20:51
Yeah, that’s a substantial. I mean, it’s a substantial cost savings. So I’ve, you know, and this kind of gets down to like the business theory and things like that. But I’ve seen, I’ve seen companies also reposition themselves, so that now like, their headcount may not necessarily decrease, but they’re just bringing on us a different type of employee, right? They’re bringing on like, different skill sets. So like, because I think that’s been one of the concerns, I’m sure you have been on the front row seat of this, of like, man, you’re here, and you’re gonna replace everybody, you know, we’re gonna be like, two man companies in the future and stuff like that. Like, I don’t know how much I agree with that, because I just I see companies needing, like, they need people to still, like, just just higher levels of knowledge workers, I guess, is what I’m trying to say. So like, what’s your, what’s your feedback to that?
Ted Willich 21:37
Yeah, I mean, it’s, it’s exactly that it’s, it’s freeing humans up to do the more, you know, the heavier thinking, if you will, you know, a great example of a customer that we have now, is, we’re automating a lot of workflows for a company in the work comp, space, and very document heavy, but it’s repetitive. And so we’ve automated a lot of the processes, but if the computer’s can’t figure it out, it’s usually it’s gonna take someone with domain expertise to understand it, like they’re gonna, they’re not gonna be able to just look at it to solve it. And really, what it does is it allows companies to bring on, you know, more business, the employees, you know, they train them up, you know, on the, on the higher level things. And, you know, and right now, companies can’t find people to work. So, you know, it’s kind of just almost the opposite problem where I gotta get the work done. I don’t have anybody that’ll do it. And, you know, obviously, if things change because everything’s cyclical, right, you know, sure. That, that that’ll flip and then companies will be incented, you know, that they’re, they’re not wanting to hire as many people. So they’re trying to automate as much as possible. So, yeah,
Aaron Spatz 22:56
that’s a that’s so fascinating. And it’s like, it’s funny, you mentioned that, because it’s like, yeah, I mean, companies are having a heck of a time trying to just find people to do anything at this point. And so, if you’re a job seeker, at least, from the few people I’ve spoken to, it just seems like it’s a very hot market, if you’re, if you’re out looking for a job, because there’s a there’s a ton opportunity out there. So but but so. So Ted, let’s let’s shift gears a little bit more into just the into the just to the business perspective of things, because I think there’s there’s a, so the audience that’s listening to this there, there’s there’s a lot of military veterans, there’s not military people in here as well. But people that are either in the entrepreneurial game now or they’re, they’re contemplating it. And so what like, what do you see as being some of the more common pitfalls that you’ve maybe personally experienced? Or things that you see a lot of first time? First time entrepreneurs make that you think, man, if they could just get that right on day one and not learn that tough lesson, they would be in a much better spot just from day one.
Ted Willich 23:56
I think my first first thing I would say is that if if you can’t bootstrap it, and you know, you can’t get some friends and family to loan you some money or something like that, then then your business pant plan probably isn’t good enough. Anyway. I see a lot of people that start companies that all they focus on is raising money, they’re just constantly spending time trying to find investors. And you know, my advice would be make money, don’t raise money. Just because there’s a lot of strings attached to that you’ll get bogged down in the whole process. You know, now you got Equity Partners, you know, you got to deal with them and, obviously be open and honest with them. At the same time you’re trying to run a company. My other advice would be until you get to, you know, above 10 or 15 million a year don’t even talk to the VCs or private equity Are any of those folks? Unless, you know, you’re really, unless you really got it right, unless you really got something that that is hot, even then if you have something that that’s hot, you probably could bootstrap it anyway, or at least give it a go for a year or two or three, build up the revenue. So that way, you’re not giving away half the store. Right? And so, the subete probably been my main piece of advice, you know, pick your partner’s well. And, and, you know, and then just be ready, because as you grow, you’re, you know, your skills are going to have to change and grow with it, along with your team, your leadership team, right. I mean, it’s, it’s one thing to be, you know, a platoon commander, but then all of a sudden, now you’re a company commander, right? So, you know, like I said, we’ve got over 60, folks, and it’s more difficult than when we had six, you know, and this time next year, we’ll probably be, you know, with our current growth path, we’ll probably be pushing 100, folks. So it just takes different skill sets at that point.
Aaron Spatz 26:09
Yeah, that’s really I mean, that’s really, really good insight and wisdom. You know, you’ve talked, you mentioned capital raising, I agree. There’s, I mean, there’s a lot of folks out there, that’s, I mean, that’s what they focus on is just raising capital, but I like your I like your kind of validation to that is, you know, like, but is, does the business model work? Like, are you making money? Is there is there an opportunity to bootstrap it, at least initially? And I think there’s, I think there’s a lot of wisdom to that. And so, you know, how do people get going with an idea to a point where, like, well, let’s, let’s just ask you like, with, with your like, with, with the, with your company? When did you get it to a point or when you’re like, you know, what, like, we’ve got something here. We can, we can now we can help pay ourselves like, we’re gonna we’re gonna survive, like, at what point? Did that occur?
Ted Willich 27:03
Probably year, three, late, you’re three early, you’re four. And that was, you know, that was, that was, yeah, first few years, like, you know, whatever you do, or whatever it is, you know, it’s gonna take time, if you think someone’s gonna take a month, expected to take three to four months, you know, if you think something’s gonna take six months, it’s gonna take a year, because it’s just, it’s, um, yeah, it’s a slog, you know, it’s, it’s, it’s difficult. And, you know, there’s, there’s not a lot of unicorns out there, like, you know, and even though, you know, you look at the history of Facebook, and Google and the others, they have a lot of adversity at the, at the beginning. You know, I would also say, don’t think that you can work a full time job, and then also start a company, like, you have to take that leap, because now you’re in it, you’re forced to, every day, how am I gonna make money? And how am I gonna get clients? And you know, it? Yeah, it’s tough. The first year, my wife and I used to joke because the, we would, you know, get up, we’re trying to start the company, I’ve made calls to my network, just trying to drum up some business. And I would have to stop calling around 9am, because people wouldn’t return my calls. So I’d have to call from like 730 to nine. And then it’d be what we call Cricket Cricket time, because people were calling back during green hours. And then at about five o’clock at start to get some calls back, and then, you know, work later, and it was basically the market, telling us what our value is, at the time in the early years. We weren’t anything, you know. And as that changed, and as we got more return calls and clients and everything, you could feel the company changing and then we hit that point that you just you just mentioned in your question of, Okay, now we’re making it now we’re starting to do it. So it was kind of a very unscientific way of saying, Yeah, we made it.
Aaron Spatz 29:15
Sure. Well, but it was early days. I mean, you’re you’re you’re hustling, you’re working your network. And again, you’re you’re offering to do exactly what like you’re at you’re you’re you’re asking them for an opportunity to take a look at their data, see what you’re able to do to help them better optimize your business like what like what was your approach?
Ted Willich 29:33
Yeah, yeah, it was exactly that it was we were selling really advanced analytics. People didn’t really understand what what machine learning was back then the markets really starting to figure it out now, which is great. But back then we would we would basically go in and sell analytics. And then once we got a hold of their data, then we could tell them okay with this, we could build a machine learning model that could optimize your You know, client acquisition, it could optimize, you know, your reduce your customer churn like we would tell them, but we, we couldn’t really go in and say what we could do, which is more of an analytics sale at the beginning, and it was just a way to get to the data to, then we could start bringing them down that, that roadmap and we’ve got clients, we, you know, we have a couple clients have been with us like nine years, and because the journey never ends, once they, once you start automating stuff and applying the technology, and you get that ROI, it just, you know, it just expands the, you know, the comment we make around here is, you know, land and expand, you know, you get in at a point, deliver for the client, make them happy, and they’ll reward you with more business.
Aaron Spatz 30:45
So true. And so with with with this specific service offering. So when you’re going in, and you’re you’re helping these companies, were there specific verticals that you’re targeting in the early days, or are you guys, are you guys verticals specific now? Or like, what does that look like?
Ted Willich 31:05
So, in the early days, we really went after more of the, like the marketing companies and artware. And folks that had a lot of high transactional data, okay, that understood, at least at a rudimentary level, what could be done using predictive modeling slash machine learning. And then what ended up happening Aaron is, is we didn’t start to verticalized by industry, we started to create, we created five or six product lines. One product line we have is computer vision. So we can take large amounts of imagery, train the computers to identify things in the imagery and get it back to the client. So we have a client right now, in the rail inspection industry, they take massive amounts of pictures of Choo, choo trains, right. But there’s not enough human beings to look and process it. So we train the computers to do that. Another product line we have is robotic process automation. That’s where you’re training bots to do the clicks and the copies and the pace. You know, one of our customers for compliance for their fleet of drivers, they have to make sure their driver’s licenses are still valid. So we automated validating that that’s still good with like the state and, and, and things like that. The other product lines is using a technology called natural language processing, which is our first name, right and Opie logics to be able to read massive amounts of documents, and then pull out insights and pull out things that the customers are looking for. Another line we’ve gotten into is application development. So we’re building systems for our customers now, because of the machine learning and automation that we did that customers said, you guys know more about our data than we do? Can you guys build our next gen of our platform that runs our business? So? So that’s kind of been the journey. So it’s more it’s more product slash technology. Vertical versus industry?
Aaron Spatz 33:19
Makes sense? Yeah. I mean, that’s man, that’s so cool. So when you’re when you’ve been worked with some these companies are, because I’m thinking of just like, the natural language processing aspect of this, where you’re talking about how you’re you just reading massive amounts of, of data or pages. And so, like, how has that enabled you, I guess, enabled your clients then to better digitize their, their, their companies, because they may be sitting on like, you know, like, walls of filing cabinets or bankers boxes full of statements and stuff. So like, maybe they’re paying someone to run a whole bunch of stuff into a scanner and scan it to PDF, and then you’re, then then this model is like, chewing on all that data and like going back into history and grabbing more. Like have you seen any of that?
Ted Willich 34:05
Yeah, yeah, we have we’ve seen, like, things called GDPR compliance. Yeah. Okay, we’re in Europe. So a lot of American companies that have like, credit card numbers, because someone filled out a form and wrote a credit card number, they may have that in that pile of bankers, you know, banker boxes, but you can’t pay someone to go through, you know, but you could pay someone to scan it, but then just train the computer to identify where there’s, you know, credit card information, so you can delete it or you can offski You know, blur it out or whatever. So, like, that’s one use case that is exactly happening that you know, you kind of you brought up and there’s there’s 1000 different examples of things that could be you know, pulled out more That’s a liability that is just sitting in, you’ve got information sitting on a pile of backer boxes.
Aaron Spatz 35:06
Yeah. Wow. So where do you see the industry heading? You know, like, you’re, you’re, you’re on the edge of this, you’re I mean, you are you are in the machine learning, artificial intelligence world. And so where do you see this progressing? Like, where do you think the next few years is gonna is, is is going to lead.
Ted Willich 35:25
So it’s really exciting because at least our space that we’re in, you know, the custom, you know, machine learning, automation solutioning companies, there’s not a lot of us out there, but they’re beginning to emerge, like it’s a, it’s almost a whole new niche. And, honestly, we thought, for a long time, we were the only ones kind of out there doing it, you know, Watson with IBM, and then Palantir is kind of on that on that cusp. But there’s kind of a groundswell of companies like us. And there, there’s a podcast, that’s I want to give a plug to another podcast, but it’s, it’s called a merge, I think, em er J, and they highlight this whole industry. And the exciting thing for us is, when we started the company, everybody said, You need to focus on one industry, and you need to solve one problem, you got to do it over and over and over. And we just said, No, this, this technology is transformative, that the opportunity is much, much bigger than that, you know, don’t care about multiples, don’t care about valuate, don’t just don’t even care. Because if we build a company, and we build it, with a strong foundation, all that other stuff will call into place. And, you know, I think in the end, we were right, because that’s what’s starting to happen is the groundswell is happening, where companies like ours, you know, are able to, you know, answer the call, you know, where businesses want to optimize their processes, they want to train their data that they’re sitting on, to do things and go to work for them. And, yeah, it’s just not a lot of teams out there that can do this stuff. There’s a lot of talk, I think my toothbrush says is, you know, powered by AI. And it’s like, the everything’s AI. Right. And there’s just not there’s a lot of smoke and metal, not a whole lot of doing.
Aaron Spatz 37:17
Wow, okay, well, that’s I mean, that, that kind of helps kind of answer some of that, because I think there is I mean, it’s, I feel like it’s everywhere, like everywhere you go. Yeah, I mean, exactly. Toothbrushes powered by AI. That’s awesome. But yeah, but that, but that is what it feels like, though. And so it’s it’s interesting that you that you feel like that, like we’re still kind of in the beginning phases of this. So it’s gonna be interesting, as more and more players show up on scene of like, where like, where collectively where the industry kind of finds itself going, or what crazy ideas people begin to think about applying or attempting to solve. And it’ll be it’ll be fastening, it’ll be fascinating to see kind of where the where this lands, for other companies or for just just the average everyday consumer, like, all the different various applications of this. It’s really, it really is fascinating, for sure. I can’t imagine what you’ve seen just over the last 10 years. I mean, that’s, I mean, it’s got to be crazy to be able to look back.
Ted Willich 38:15
Yeah, it is, in fact, I’m here at our office in Jacksonville, and I look out on the main hallway. And we have our first computer that that we bought, you know, and this was 10 years ago, right? It’s got a GPU, it’s got, you know, it was really, really high end back then. And now it’s a little bit of a, you know, the butt of a joke. Yeah, when you look at it, but really the technology where it was 10 years ago, and where it is today is just it really is mind boggling. It’s as mind boggling as when you and I first saw that Trimble trim pack, and it would show you exactly where you were, you know, on the ground, and which is great. And it’s exciting. I mean, there’s there’s also some concerns. You know, me personally, I have concerns about our adversaries, or potentially future adversaries, like the Chinese. You know, I saw statistic the other day, they have like, more honorable kids than we have, like students in the US and they’re pouring massive amounts of, of, you know, money resources into artificial intelligence, and, you know, they’re, they’re probably they’re going to be starting to nudge a little bit ahead of us here unless we, you know, kind of get our game together. And a great example is the, you know, employees I think Google was was awarded a defense contract and and then some of the employees at Google said no, we don’t want to work on defense work. And it’s like, well, you know, you got the best and brightest and all of a sudden, they’re not you know, who’s gonna do the work that right. So it’s, it’s a little bit concerning from that. I can’t imagine that in China that they’re they’re big. Their group Alibaba that some of their employees said, No, we’re not going to help with the defense. I’m not sure how far that would go. But not it’s just yeah, it’s an interesting quandary. Right? There’s a lot of articles and interesting conversations to be had around the ethical use of AI. And, and because it really the, the compute power is there to do some extraordinarily amazing things, you know,
Aaron Spatz 40:22
I mean, it’s like, I mean, you could pull straight up a science fiction movie, man, it’s like, some I mean, and not even that far ago, like that long ago, like, there’s these crazy science fiction, like machine learning, artificial intelligence, type, you know, type storylines, that at the time felt a little, I mean, you kind of got the sense, it was semi plausible, maybe. But now it’s like, Man, that is totally doable, totally doable, if you have enough resources, and you’re able to drop a ton of money into the, you know, the just supercomputers and everything else, and churning through massive amounts of data. I mean, there’s, there’s pretty scary applications to it. And I think that’s going to lead to a lot of big ethical debates. And that’s going to be that’s going to be interesting to see kind of where that all lands. Because I mean, again, not like not to get too off topic, but I mean, but you you see how, just like home surveillance systems, right, like you’ve got, you get your ring and nest and all these other companies that make you make these types of cameras and things. And, I mean, there’s, they’re even tying themselves into each other, like and forming our own little mesh networks, which is, which is crazy. There’s a lot that you’re, there’s a lot that your technology does without your knowledge, and necessarily without your consent, which I think is really troubling.
Ted Willich 41:40
Yeah, it is. And there’s, there’s a lot of, you know, the power that, you know, the power and the technology that’s out there is is, you know, to your point, mind boggling, and, you know, it’s it’s the privacy versus convenience argument, you know, me personally, you know, I like it when my phone tells me which route to take home. Right? You know, right? It’s, it’s, I do like that, because it knows where I live, it knows where I work, when I go and all of that. The, you know, I drive. I bought a Tesla about a year and a half ago. And I love the technology. And it’s like, every three weeks, there’s a new update pushed out, you know, and I remember what it was like, when I first bought it, I was blown away. Now I look at what it was like back then I’m like, Oh, that was nothing compared to how it is now. So it’s just getting, it just gets better and better. Which is, which is very exciting. And at the same time. Yeah, there’s there’s privacy issues, like, you know, yeah, I guess I guess, opt out of stuff or something.
Aaron Spatz 42:48
I don’t, right. Yeah. Well, I mean, my you my prayers that you folks like you that are on that are on this cutting edge, like we get, we get as many ethically minded people as possible, like on the leading edge of this, because then I mean, you really are going to be in a position where you’re, you know, flick of a toggle switch somewhere right can can really have some massive repercussions for people. So anyway, thanks for humoring me, I could go off into a whole I mean, we could go into a whole nother three hour segment about the privacy and surveillance, we could talk about Edward Snowden and a whole bunch of other things. Right? We could go down that trail. Maybe we could save that for some time. Yeah, there you go. Yeah. But, uh, but no, so But going back to just the idea of entrepreneurship, and I, you know, again, you, you, you hit on the the capital raising side of things, you know, I’m, like, I’m a believer in capital raising, if, if, if it makes sense. I like though, I really do like how you said, and I’m gonna paraphrase this horribly, but basically, you know, like, if your proof of concept shows that it can make money, then you really should try to bootstrap as much as you possibly can. And so I think they’re, like, there’s a few things you said, I’m, I’m trying to encapsulate and capture, like a lesson learned here. And then I like for you just to, like, make comment to this, but it’s kind of like, you know, as an entrepreneur, focusing, again, don’t get focused on all these other 3000 things that that could possibly distract you, but focus on solving a real problem for for your customer. And like, start there and like, is it like, am I am I oversimplifying that Ted, or is it is it like, Is that is that should that be home base? Or should you root yourself in something else?
Ted Willich 44:30
Yeah, no, I think that that and again, it’s my opinion that you know, for at least a year or so maybe two whatever prove your concept prove not only to yourself but have customers and really try not to fall into that trap of trying to raise money we raise money i We do have four or five outside investors who are great. We love them and everything. but we didn’t have to give away as much equity, because we proved that we could execute on a business plan. And if you just start focusing on raising money, first of all, it’s a full time job, it will, it will absolutely distract you. And you’re trying to convince people to buy into your dream, and it’s easier to sell it if you’ve already bought in. And if you’re, you’ve already got that sweat into it, you’ll make that sales pitch, you know, much better and get a higher valuation, excuse me and give away less, which ultimately, you know, you want to do, right, I think.
Aaron Spatz 45:39
Yeah, I mean, people want to create things that that have massive value. I mean, like I, to your point earlier about the looking at the looking at the annual wage increases for, for our US military and government officials, you see, you see what, you know, what the stair step process looks like. And then you look at opportunity outside, and there’s nothing wrong with wanting to better better your own position, better your family’s position, and better those around you. And like, and in your case, you you guys are creating jobs, you’re pumping into the local economy, they’re in Jacksonville, you’re doing when you’re doing a lot of different things that are, that are massive value add to society. And so it’s like, I think, I’m, I’m probably quoting somebody when I say this, but I mean, entrepreneurs really are the lifeblood of this country. And, and like think, thank God for people like you that are that are willing to, you know, put, you know, cash in cash out the 401 Ks. I’ve talked people that have mortgaged their houses and all sorts of crazy things to get things going. And, and the thing is, though, like, we don’t talk a lot about the failures, right, we talk a lot about the successes. Yeah. And I’m sure there’s tons of lessons learned there, too. Right. Um, I’m just continuing to get back up again.
Ted Willich 46:51
Yeah, that’s it. You know, I always joke with people, I always tell him, I have a PhD and failure like I can. There’s a ton, you know, of, you know, abs ebbs and flows, peaks and valleys. And so, you know, you just learned from them, and you get up and get back out there and get added. You know, I would add also that, you know, as the company gets bigger, and us as an organization, we can do more things to to help our community. So, you know, we, for the last seven years, we’ve run a little analytics boot camp every summer for the Duval County Public Schools, focusing on those high schools where maybe there’s a little less opportunity. Yeah. And we’ve also established relationships with a couple of universities here and in town for the pipeline of college students. So as you get bigger, it becomes less about you know, the company has to be successful, we have to we have to deliver, but it creates opportunity to be an active positive, you know, force in, you know, in the community, and then it just, there’s a flywheel, right, as as our employees do more and more volunteering, and they do more and more good. It just helps the company and then you know, it all feeds into it. Right, just just do the right thing. And generally things kind of fall into place.
Aaron Spatz 48:16
Yeah, that’s that’s really cool. Well, if people want to learn more about you about the company, what’s what’s the best place for them to go?
Ted Willich 48:23
Yeah, I mean, LinkedIn, there’s not a lot of template lunches out there. I don’t think so. Look me up on LinkedIn. The company is NLP logics. So November Lima Papa ello gi x as an x ray. There it is. You just there two steps ahead of me here. Yeah, you can hit us up on the on the web there and if you’re ever in the Jacksonville area we’re in in the South Pointe area just south of downtown about five minutes from downtown Jax. I can’t imagine it’s gonna be a lot of people going Jaguars games at least for the next couple of weeks because it’s hot.
Aaron Spatz 49:00
Yeah, sure, sure. But if you say Ted whatever you say my my my beloved Las Vegas Raiders have been off to a great start the season so a good good buddy of Mines a chiefs fan so him and I each other all sorts of crap all the time. So
Ted Willich 49:18
there you go. Well, we love we love the jacks here in town, although we tend to get beat up a little bit on the field as well as up field.
Aaron Spatz 49:27
That’s awesome. Well, what’s had I mean, this has been this really has been a true pleasure. I just I really do just want to thank you for take some time to speak with me share some of your stories. Again, we I mean, we we could keep going on and on and on. I think there’s just so much here but I really do. I really do appreciate you taking some time to explore the industry. I think you kind of give us a little bit of an educational bit of a background into just the industry as a whole the the the lessons the things that you’re able to help companies realize and then just talking to some of the specifics about the business right about about the basics of entrepreneurship about Just a couple of different core principles and beliefs and things of that nature. And so it’s been been tremendously helpful and very insightful, I’m sure to tons of people and so I just want to thank you for making time to be with me and again, I really do wish you and company the best it sounds like you guys are off to a I mean a phenomenal trajectory and in my prayers at that absolutely continues. So,
Ted Willich 50:22
thank you so much, Aaron, appreciate you building this platform to get the word out and and yeah, semper fi.
Aaron Spatz 50:33
Thanks for listening to America’s entrepreneur. If you enjoyed the show, please leave a review or comment on your preferred social media platform. share it out with friends, family, coworkers, others in your network. And of course, you can write me directly at Erin at Bold media.us That’s a Ron at Bold media.us Select