Start-up life is exciting, demanding, and occasionally bizarre. You may find yourself working from the bathroom or partying with monkeys, lemurs, and camels. So did Stephanie Hanson, today's guest and an indefatigable entrepreneur building her second company, Gestalt. We chat about the challenges of growing a start-up — finances, hiring, and creating a strong culture — and squeezing lots of life in around long work hours.
Start-up life is exciting, demanding, and occasionally bizarre. You may find yourself working from the bathroom or partying with monkeys, lemurs, and camels. So did Stephanie Hanson, today's guest and an indefatigable entrepreneur building her second company, Gestalt. We chat about the challenges of growing a start-up — finances, hiring, and creating a strong culture — and squeezing lots of life in around long work hours.
Find Ensemblex and Stephanie on LinkedIn.
Hosted by: Shawn Budde
Guests: Stephanie Hanson
Produced by: Meagan LeBlanc
Theme Music by: Brad Frank
Shawn
Hello, this is Shawn Budde of Ensemblex, and this is the Ensemblex Exchange Podcast. Today, I'm talking with Stephanie Hanson, the founder of Gestalt.
Gestalt is building unified data ecosystems for the 3 trillion dollar lending industry by automating data organization, which is today a pretty manual process. Gestalt accelerates AI adoption, insights and in general allows organizations to use their data rather than think about organizing their data.
Stephanie is a repeat founder in the lending industry. She founded defi Solutions, the first user configurable loan origination software in 2012. After she sold defi and caught up on some sleep, she founded Gestalt, last year, to create the first data organization software for lenders. While not building companies, Stephanie has taken her family to all 50 states and they are currently working their way through the continents.
Why don't we start there, Stephanie. I've always said, we've known each other, I don't know, 15, 20 years now. I've always said you are a woman without a throttle. Whatever you go after, you go after it at full speed. And so yeah, why don't you talk first about the 50 states and how that went down and how long that took you? Because I think it was an express ride.
Stephanie
Yeah, it was. Well, it got kicked off out of guilt, mom guilt. I was a single mom, most of the time I was building defi and I was working a lot and I wanted to find time to spend time with the girls. And the older one had expressed a lot of interest in traveling and the younger one jumped on board with that. And so one Christmas, I just came up with a wild idea and I didn't like give myself time to think about it first, which is always best. And so I gave them suitcases and travel books and said, hey, the older one is graduating in three years. I said, let's start from scratch, no matter where we've been already, forget about it and let's hit all 50 states together in three years. And the rule was that while we were traveling, I couldn't work unless I was in the bathroom or if they were asleep. So I went to the bathroom a lot and luckily they slept till nine or 10. So I'd get up very early and start working. So yes, and I hope the girls don't listen to this. Bryce was helping me with sales and I had him in my phone as, “dad” so that I could answer the phone.
Shawn
Ah. Nice. That's very sneaky. So what was the weirdest thing that happened to you in the 50 states?
Stephanie
Oh my goodness. Everything was pretty, oh, we did, this wasn't weird, it was scary. We were trying to find a hotel because always we would do it on the day of, on like Expedia or last minute deals or something so we could get a good deal. And so we were in kind of the middle of nowhere and we went to this hotel and it was very creepy and I left the, they said, well, you can come check out the room first because I thought it might not be the best room. And, I don't know what I was thinking. I left the girls at the front desk, like in the chairs at the front desk, and I went with a stranger to go check out a room, and I was like, what am I thinking? They could like steal my girls. So I ran back, panicked. That was pretty weird. I'm sure the girls could think of better things than I can on the spot.
Shawn
I will say, I remember when you came through, when you did Illinois, I don't know, you worked wall to wall. You were out from nine till 10 at night or something like that.
Stephanie
Oh yeah, everything was, and we wouldn't make any plans that we just get on the plane and then we'd start looking on TripAdvisor everywhere we could find. And then we would go literally, yeah, Washington DC was crazy because obviously there's so much to see there and we'd start super early, we'd be back super late. Yeah, they were long days.
Shawn
I assume there's been more planning for the continents.
Stephanie
Yes, because I did get remarried kind of at the end of the defi era and there's seven of us and so you can't just, “Hey, let's jump on a plane and go to Oklahoma.” or anything quickly. So there has to be planning and and also like nothing makes me crazier than everybody saying I'm hungry. I'm hungry. I'm hungry. Where are we gonna eat, you know like that type of thing or getting on an airplane and having the people fight about window seats. So the seven continents is very planned out. I give everybody a schedule of exactly where they're sitting, exactly what room they're sleeping in, exactly where we're eating, exactly where we're going. So not a ton of room for spontaneity there, though we do a lot of planning as a family before we get there. And yeah, so we've hit every one of us, there's seven of us, there seven continents, and there were seven years to finish it until the last one graduats this year. And so everybody was assigned a different continent basically.
Shawn
Assigned a continent to make the plans for?
Stephanie
I mean, just like to be their sister continent, right? Like, yeah, so no, they didn't make any other plans. So Antarctica is our last one in December.
Shawn
And who got assigned to Antarctica?
Stephanie
Good question. Let's see. I guess it was, no, I'm South America, John's Europe, Jace's North America, so it'd have to be Riley. Riley, the second, second oldest. Yep, that's hers.
Shawn
All right. Well, we met when you were working at Think Finance. You had worked at AmeriCredit before that. You were on the client side of loan origination systems, in essence. What made you decide to flip over and be the vendor side of that equation?
Stephanie
Yeah, two things. So I'd done it, say, for companies. And I loved it. I was definitely passionate about origination systems, decision engines, automation. So I definitely love it. And I definitely saw the similarities. I don't think I would have actually done it though. I was on a girl's trip to Colorado. And I think one of the two other girls were going for a run and a bike ride like combination, and I looked at Georgine and said, I don't want to do that. And so we went for a walk. And so we were the lazy ones and we went for a walk and I had been let go from Think. And we're just talking about what I wanted to do. And I was trying to create this business, replacing gold knobs and gold fixtures in everybody's houses. And Georgine said, that is the stupidest idea I've ever heard and you're not gonna make any money and there's no margin. And then she asked what I wanted to do and I just said, there really should be a better origination system. And she said, you should do it. And so then she said she'd give me a little money. I said, I’d pitch in a little money, Lana one of the other girls on the trip, pitched in a little money and we went from there. So probably had she not kind of pushed me and encouraged me as you have with Gestalt, I probably wouldn't have done it.
Shawn
And what was wrong with the existing offerings?
Stephanie
Oh my gosh, so much. Number one, it would take a year plus to implement. Number two, it was a high professional services model. So anything you wanted done, you had to go to the vendor. There were some options out there. The one that I implemented the most often was kind of a blank piece of paper, and you could build anything you wanted to, which was awesome, as long as you had somebody like me who fully understood the workflow and could build something on a blank piece of paper. So the blank piece of paper, you had to have the right person. The not blank piece of paper, you had to have a million dollars in a year. And you couldn't change anything or configure anything once it was built.
Shawn
As I recall, you started on one of those platforms. You started defi on top of one of those platforms and then later switched. Like what led to that pivot?
Stephanie
Correct.
Stephanie
Yeah, so I had gone to that company and asked them if I could just come work for them and build something configurable and out of the box. And it wasn't their direction or vision as a company, which is fine and they've continued to do well. So we put them in as our decision engine thinking that number one, we knew it well, it was very powerful and it would give us credibility. But then as our vision was really that thousands of lenders could be on this platform and could configure anything from your bureau codes to your characteristics to anything. We were about six months in starting to launch the second client and my developer said it didn't scale like that. We could only use it for one. I didn't know the developers very well. I'd only known them six months. It was a hard soul searching, do I trust two developers?
I love developers, but often they're like lawyers and have their own opinions on, and wanna change everything. Or do I trust this platform that I've used many times and ultimately trusted the developers and pulled it out and built our own.
Shawn
And so how was that transition? Was that as expected or was that harder than expected?
Stephanie
No, I mean the team delivered, so the initial team and later team as well, delivered kind of on time, on budget and it worked well and it gave us what we were going for, which was the flexibility.
Shawn
So what was harder than you expected in starting defi?
Stephanie
Yeah, everything. Um, yeah, cause again, just like the 50 states, I didn't give it a lot of thought. I just said, yeah, I'll do it. And, yeah, hiring, hiring is hard. It was easy kind of, I wouldn't say easy, but for the first 10, you can kind of do it through your network. If somebody knows somebody and they're willing to work for equity. And then after the first 10, we really hit a wall where, you know, you didn't know anybody else to come on. You couldn't offer enough equity or cash to get anybody excited. We tried to use recruiters for a while, which was a mess, very expensive, and they always left after a year, no matter how good they were, because the recruiter took them to another place. So there was a period in there after we hired kind of everybody we knew in our network, and before we kind of had a name and a culture so that we could attract talent, that it was very, very painful.
Once we got through that period, we had a nice online presence and a good culture and we were able to attract and get enough resumes in to like choose, but prior to that, it was hard. I mean, money was always a constant struggle. I mean, I know you were constantly telling me I needed to have more in the bank and I just never was able to have more in the bank. So we were just always bootstrapping it and trying to grow. That was difficult.
I mean, people, issues are always, you know, always difficult. I would tell people when they came on, like, you may be able to scale and grow with the company, but you may not. And if not, then we have to part ways. And so I'd tell people that upfront, which some people didn't appreciate me telling them upfront because it wasn't exciting enough and that kind of scared them. And yeah, we had to part ways with lots of different people. And that was, you know, difficult.
Shawn
So part of the culture I remember involved monkeys and camels.
Stephanie
True, yes.
Shawn
What were you doing there?
Stephanie
Why?
Shawn
Let's go with why.
Stephanie
I mean, I think definitely our culture was quirky, I think is the right word. And I think that's accurate. I mean, I think typically a culture reflects the CEO and or the management team. And, you know, Weird Al is my favorite artist. And so quirky is probably accurate. And I had one of my early hires was the head of marketing and Kristen was very willing to have crazy ideas with me and like brainstorm. And so we did all kinds of weird stuff at conferences and we handed out jello shots and we wore rock t-shirts and we did all kinds of weird things that fit us. Like they definitely fit our personality. And then it was actually time for our five-year anniversary party. And Kristen had done all of our, we did annual anniversary parties, Kristin would do all the party planning, and then I would write a song parody for that year. But this year she was so swamped that on year five, she was so swamped that she said, I can't do it. You're gonna have to help. And so then I just thought of that book, Five Little Monkeys Jumping on a Bed. And so I got an air mattress and put a blanket on it. And I Googled monkeys for hire and they showed up, but one of the monkeys got sick. So there were four monkeys and a lemur jumping on a bed.
Yeah, everybody loved the monkeys. They'd take your beer, take your pizza. Like they were funny. They had t-shirts on with one, two, three, four, five on the back. And so then the monkey continued coming to all of our parties.
Shawn
Okay. I do remember coming to one and you sent out a message saying, “hey, it's really cold.”
Stephanie
Oh, the camel party was freezing.
Shawn
Yeah, I'm from Chicago and I'm like, oh, well, Dallas, you know, they don't know cold.
Stephanie
It was bad, yeah.
Shawn
And I walked out of my hotel and I turned around, went right back in and got my coat. So it was indeed cold.
Stephanie
Yes, it was freezing.
Shawn
You hit on a good point though, which is, is personality. And I think, you know, I've seen startups where the founder is trying to be someone else trying to be someone that they saw who was successful. After the Steve Jobs book came out, I think everybody decided that they were, had to be a visionary. What is your style? What is it that fits your personality?
Stephanie
Like in leading the team or the company or just in general.
Shawn
Yeah.
Stephanie
I mean, I like to be in charge. I like to make decisions, but I like to get input and hear from other people before I do those things. So I don't like to cede control of the decision, but I do not do well on my own. I definitely do well with partners and advisors and people helping.
And I would say I'm definitely a delegator. I'm a mix. I'm not detail oriented, but I'm not, not detail oriented. So somewhere in the middle. My mom would say I'm not detail oriented. Everybody who works for me says, thinks I am. But yeah, so I'm an, you know, I think I fit my, I love Strengthsfinder and I think that is my style, Strengthsfinder. So my top five are like command, I like to be in charge. Communication. I probably over communicate and say the same things over and over again. I send lots of updates. Achiever. I like to get stuff done and knock it out, Arranger, so I'm always trying to organize and organize chaos, and then Responsibility. So I think my personality profile thing says I don't have a lot of patience when deadlines aren’t hit and that's accurate.
Shawn
Okay, fair enough. So switching over to Gestalt, what is the idea behind Gestalt?
Stephanie
Yeah, the idea is that there are thousands and thousands of lenders out there, actually almost 200,000. A lender could be they're called many names, right? It could be a credit union, a bank, a buy now pay later, an auto finance company, like they go by many names, but and all these lenders use different operational systems that also go by many names, but generally loan origination systems, loan management systems, CRMs, accounting systems, and so forth.
Each one of those lenders needs a way to get the data from inside those operational systems to a centralized place because that data holds lots of insights and value. And if it's stuck inside the operational system, the lender can't do anything with it. So kind of part one of our vision is data organization. How do we take data out of these operational systems and centralize it, that the lender can us it for their AI models, their automation, their analytics. And then part two is how do we make the entire ecosystem better? Because once the data is there and organized, we can offer additional products, compliance products, vendor management products, different things on top of the data. So combination of centralizing data and then providing products on top of it.
Shawn
So when we at Ensemblex decided that we wanted to launch Gestalt, we knew you were the one who wanted to lead it. And I remember I talked to you and I kind of gave you the story and you said you were a six out of 10 on the idea and you came back a week later and you were at nine. I'm gonna assume now that you're at 10, but what evolved in your thinking over the course of that week to get you from six to nine?
Stephanie
Well, I think, you know, our first conversation, just kind of like when Georgine asked me a question, what you were saying, I knew was a problem. So I'd seen it with defi lenders, I'd seen it at lenders where I previously worked. So the six was because I agreed with you 100% it was a problem, and 100%, if somebody could fix the problem, it would help things. I probably got to a nine just, thinking about, do I feel comfortable that I can fix the problem? Right? Because data, I mean, it's messy, and it's a pain. And I would say until the last five to 10 years, there wouldn't have been a good way to create a SaaS solution for this. Everything was kind of bespoke and separate and different, but with just all the tools and AI and all the ability to create SaaS platforms, I think it's there. So I think I felt more comfortable about my ability to deliver it and then in the tools that were out there. And yeah, I like solving problems in market, but I'd also been retired for four years and we had a nice travel schedule and I was probably working 10 or 20 hours a week. So, and startup is a lot of hours, so.
Shawn
Yeah, it's interesting. Part of what inspired us for this is having worked with several dozen companies all over the world, 100% of them have a terrible data architecture and messy data, and someone has to go and correct stuff manually. We worked with one company that was adding something like 10 columns per week to the database and nobody knew which of the seven versions of a variable was the right one.
So how does Gestalt, if you've got all these companies that have messy data, think they need it in their own format, so to speak, what does Gestalt do to get them over the hump to use a more uniform approach, a consistent approach?
Stephanie
Yeah, so I would say with a lot of lenders that we talked to maybe don't have anything or just embarking on it, and that's the perfect candidate for us because they don't necessarily already have, you know, data points and things in their mind, but even for lenders that already have a warehouse, I think once they start building, they see how time consuming and how expensive it is.
And if they switch one of their systems that they have to remap that data in and figure out how to normalize it. And everything that lender does to build their own warehouse is done one time. So they don't build any automation around it. They don't build any like anomaly detection and different things around it because they're doing it one time. So they're kind of brute forcing it. So they also don't document their data lineage and how something got somewhere. They don't document their definitions. So we have a lot of features inside of the product that if you're building yourself, you're just not going to have because you don't have the time and money. And I think everybody on any tech or data team would say that it's very difficult to get people at the top to give money to data projects. Everybody thinks it should be able to be done cheaper and faster. And then when you give them a price, if you're doing it internally, everybody says, well, what can you get me for less and they end up maybe only mapping in 50% of the data or pushing off different data sources. So I think the thing would be we can do 100% of the data on 100% of the sources for the cost that they could probably do 25% and then have more features on top of it as well.
Shawn
And you mentioned automation. What is it that you're automating?
Stephanie
Yeah, good question. It could be anything in your underwriting process. It could be your decisioning. So it could be like rules and scoring and models behind your decisioning. It could be your funding process, how to automate the stipulations, how to automate booking the deals. It could be your collections process and how you're doing collections, how you're doing customer service. And then can also be on the analytics side. Many of the things that are just very manual to, maybe you put a new champion challenger in or a rule in, and then you have to manually go try to figure out if it's working or not.
Shawn
Yeah, and you mentioned anomaly detection. I mean, one of the things that has really astounded me as we've worked with companies is how often their systems, the LOS, the LMS, gets the data export wrong. It feels like it should be automated and it should be pretty much 100% reliability. And I'd say we've experienced in some organizations every two to three weeks, something seems to go wrong, any kind of overnight process. How are you guys handling that?
Stephanie
Two parts. So we definitely have a data notifications where if we don't receive the data or it's corrupt or it looks wrong, we can have a notification, we can try to reprocess, otherwise we handle it. If the vendor just makes changes, we take those changes in seamlessly and it doesn't break anything and we add those in automatically. And then if it's like specific data elements, we have put our data anomaly detector in, and so it looks across the data point over time and across other lender sets to see if maybe something is off.
Shawn
Got it. Thinking back to defi, what are the lessons from defi that have helped you with Gestalt?
Stephanie
I think I said earlier, I mean, just that I need smart people around me. I can't do everything on my own and I just do better having partners around me. For sure that, but then I would say at the same time, early on in defi, I thought the co-founder was going to join me from day one and I thought she was going to do sales and marketing and I was going to do product and she didn't. And I had to do sales and marketing and I learned that I actually like that probably even better than the product and so forth. So I had to do some things on my own for a while and it taught me that I enjoy those.
Yeah, I learned a ton about communication, ton about culture. I mean, monkeys are important, but just in general, being conscious of what your culture is and setting your culture, because as you're growing, you're bringing on people from other companies and that can easily make things confusing to the culture or can change it, right? If we bring on five people from Cap One, and they try to bring that culture in with them, then that starts to confuse the internal culture and that makes people cranky. And so, we definitely learned a lot about being intentional about the culture. Most importantly, I learned I'm not supposed to say, “I don't care”, but I'm supposed to say, “I trust you.” That's what the team told me very often. Yeah.
Shawn
Because you probably do care, to be honest.
Stephanie
I probably do care, but yeah, but that would be my standard when they would be giving, telling me something, I'd say, yeah, okay, that's fine, I don't care. And apparently I meant I trust you and not, I don't care. Ha ha.
Shawn
Yeah, I am probably guilty of doing the same thing, so I'll make sure I make that change as well. And you mentioned that with defi, you did a lot of bootstrapping. Is that the same approach you've taken here?
Stephanie
Not as much like with the defi we started with $300,000, we kicked off with $300,000 and because of the success at defi and, you know, having more people involved, we were able to raise more to get going on this one. So I would say no, this is, we've had a little more capital to get going this time, but, but still didn't kick off the pre seed with venture. We still kicked it off with friends and family to prove out the product market fit
Shawn
And where are you at on that?
Stephanie
We have completed, kind of exceeded all of our pre-seed goals and we're kicking off our seed round in May of this year 2024.
Shawn
That's fantastic. And what has been the biggest challenge in selling Gestalt into lenders?
Stephanie
I think it's the build, right? We went through this at defi too, when people thought they could build better or that they didn't really understand what we were selling. So we faced that here that like one lender had started building, they're nowhere near complete. But when we pitched the project, and we hear this sometimes, we don't have time to work on this project. And I'm always like, well, wait a minute, but we're doing all the work. So you're not having to work on this project. And in fact, behind the scenes, if you would just let us do this work, then you'd be way further along in three months than you would be if you didn't do this. And so I think probably that, that we don't have time for this project because we're so busy, we're so busy. And it's like saying, I don't have time for the gym, I don't have time to eat healthy. It's like you know, have time until it's too late. And so, yeah, so we probably need to figure out how to have that. We're trying to show through the data of our first, you know, dozen clients, how much time does it take the clients versus how much time does it take us so that we can use that.
Shawn
Yeah, I mean it's kind of a hidden killer. I can tell you at Capital One when I was there, we didn't have a great data architecture and we had hundreds, literally, of people whose sole job was to extract data. And one of the principles I had behind Gestalt is that I should be able to do an awful lot with a simple select query. Because as soon as you start doing joins, stuff gets...gets hard. And I think it made us as inquisitive as we were at Capital One, it made us less inquisitive because anytime I needed more data, I had to go back to someone, I had to wait a few weeks. You kind of look at it and to your point, it never feels like the most pressing need or the place where people want to invest the most energy. So, that's certainly a problem we've seen, Hopefully folks are starting to get the importance of this. And as you're talking about things like AI, you need good data. And if you don't have good data, you don't have good AI.
Stephanie
Yeah, that's the thing. I mean, people will say that their data is their IP. Well, I agree, but your data model, your data architecture, the data mapping is not your IP. While Gestalt, the SaaS company, isn't a hundred lenders getting together to build a better way, you can still imagine it like that. If a hundred lenders all needed a data warehouse, think how much cheaper it would be if they all pitched in on a data architecture, if they all pitched in on a data model, which is...you know, essentially what we're doing.
Shawn
That's a great note to wrap on. I love your observation. You need smart people, and especially when you're a small organization, every hire is critical, and having everybody aligned is really, really important. So thanks again for taking the time.
Stephanie
Yeah, thank you.
Shawn
You can look up Stephanie on LinkedIn, of course. You can also follow Ensemblex on LinkedIn. You can also visit us at Ensemblex.com. That's Ensemble - x dot com. Or you can find the Ensemblex Exchange podcast on all your major podcast platforms. And thank you so much for listening. Thank you, Stephanie, for joining us.