Sramana Mitra: What you’re talking about is there are certain categories of businesses that are not bootstrappable.
Felix Rodriguez: That’s right.
Sramana Mitra: Being a FinTech company as a lender is not necessarily a bootstrappable business.
>>>Sramana Mitra: And in those four months, what kind of metrics did you have to show to be able to raise the series?
Felix Rodriguez: I’ll never forget how the numbers went. In the first month, our revenue was $4K. Then it was $16K, $40K, and then $80K. It was really a driver of if I spend more on ads, I’d get more customers. I was building a partner network to be able to convert those bookings into actual customers that actually use the service.
>>>Sramana Mitra: Okay. What were the other startups that you were working on at this point?
Felix Rodriguez: Immediately after that, we were thinking that for this company that has over 50 people, what could I and a couple of other engineers build that’s more automated. We were really passionate about automation. I think people call it AI now. But we were thinking about how could we automate the publishing business. We had a website business where we had a bunch of web designers. So, in order to get traffic on the web, you have to put content, right? And Google was starting to really take off.
>>>Felix has done nine ventures and sold several of them. He is currently building a venture-funded,
AI-enabled FinTech venture. Really intelligent, scrappy maneuvering in various alleys of online entrepreneurship.
If you haven’t already, please study our Bootstrapping Course and Investor Introductions page.
In this case study, Cognaize Founder Vahe Andonians talks a lot about bootstrapping – bootstrapping to exit, bootstrapping with services, so on. You will also learn a nifty way of building domain knowledge on top of horizontal AI expertise. This is a valuable and extremely interesting way of building AI companies for entrepreneurs to consider.
Sramana Mitra: Let’s start at the very beginning of your journey. Where were you born, raised? What kind of background?
Vahe Andonians: I was born in Iran. When I was a couple of weeks old, we moved to the United States. Then my parents moved to Austria. I grew up in Austria. I studied there. I studied high-frequency technology. I did my first job there. From there, we went to Germany. I’ve lived in Germany now for 12 years.
In this case study, you will hear Vahe talk a lot about bootstrapping – bootstrapping to exit, bootstrapping with services, so on. You will also learn a nifty way of building domain knowledge on top of horizontal AI expertise. This is a valuable and extremely interesting way of building AI companies for entrepreneurs to consider.
>>>If you haven’t already, please study our Bootstrapping Course and Investor Introductions page.
Quavo Co-founder David Chmielewski transitioned from a developer to an entrepreneur by leveraging his solid domain knowledge in a particular area of FinTech: dispute resolution for credit card transactions. He and his co-founders effectively used bootstrapping using services and piggybacked on the Pega Systems platform. Read on to learn more about his journey.
Sramana Mitra: Let’s start at the very beginning of your journey. Where are you from? Where were you born, raised, and in what kind of background?
David Chmielewski: I was born in Michigan in a small tourism-driven town. They have good schools but generally not a tremendous amount of job opportunities if you wanted to do something in technology. I was one of the lucky people who always knew what I wanted to do. I was exposed to computers pretty early.
Sramana Mitra: What scale are you at right now?
Todd Schwartz: This year, we’re in the over $400 million range.
Sramana Mitra: When did you go public?
Todd Schwartz: In 2021 on the NYSE. When I walked up to the stock exchange, it was never about financial gain. It’s so funny to me to see OppFi on the banner. This was literally about helping people. I want to make that clear. If financial gain is the reason you’re doing it, your heart and soul won’t be in the business.
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