This report from CB Insights unveiled the winners of the third annual Retail Tech 100 — a list of the 100 most promising private retail tech companies across the globe. This year’s winners are using technology to help retailers create more connected and personalized experiences and drive efficiency and profitability. For this week’s posts, click on the paragraph links.
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If you haven’t already, please study our Bootstrapping Course and Investor Introductions page.
TryHackMe CEO Ben Spring and his co-founder are two techies who started by bootstrapping with a paycheck. With zero marketing budget, they have scaled TryHackMe to a million users and significant revenue.
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?
Ben Spring: I was born and raised in Portsmouth, England. I also went to the University of Portsmouth. I have a degree in Computer Science.
Sramana Mitra: Of the millions of people who are pursuing a machine learning career as a citizen data scientist track, data scientist track, or a developer track, in what time frame will that impact industry?
Gideon Mendels: It’s a gradual change. It’s already impacting the industry. When I studied computer science, there weren’t any machine learning courses in the curriculum. You can take one as optional. Today it’s core. Even if they start in a software engineering role, having that knowledge is significant. The impact started five to seven years ago.
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If you haven’t already, please study our Bootstrapping Course and Investor Introductions page.
Raghu Ravinutala, CEO of Yellow.ai, has built an incredible AI startup from India with a global base of enterprise clients. Fabulous story!
Sramana Mitra: Let’s start by introducing our audience to yourself as well as the genesis of Yellow.ai.
Raghu Ravinutala: I’m the Co-Founder and CEO of Yellow.ai. Yellow.ai enables enterprises to drive automation on their customer experiences and employee experience by integrating a whole set of enterprise data and delivering phenomenal experiences that the companies can leverage for sales, marketing, HR, and IT automation.
Sramana Mitra: There seems to be a very large number of developers who are learning Python and are either practicing or aspiring machine learning engineers. The number is in the millions. What are these people doing?
Gideon Mendels: As in how are they learning?
Sramana Mitra: What is the application? What is the career path? Is the industry active enough to absorb five million ML developers?
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I’m a big advocate for building small, capital-efficient startups. Not all entrepreneurs need to chase Unicorns. Not all investors need to chase Unicorns. There are many more viable ideas for those smaller ventures and there are considerably more opportunities for their exits, which means cashing in earlier on your hard work.
One type of exit is under $50 million, and to achieve that, your strategy should be to build a capital-efficient company that shows product-market fit in an efficient, bootstrapped manner.
That capital-efficient strategy is required for all stakeholders to make money when harvesting through smaller exits.

If you haven’t already, please study our Bootstrapping Course and Investor Introductions page.
There are roll-ups of e-commerce brands going on right now. This case study delves into one such that has exited into a roll-up effort.
Jay Perkins, Co-founder of Kettlebell Kings, currently runs Living.Fit which produces digital workouts, fitness education courses, and fitness equipment.
Sramana Mitra: Let’s start at the very beginning. Where are you from? Where were you born, raised, and in what kind of background?
Jay Perkins: I was born and raised in San Antonio, Texas. In 2004, I moved to Austin, Texas to go to college at the University of Texas. Pretty soon after arriving in Austin, I just fell in love with it. I felt like this was an incredible place to be in.
Gideon Mendels: If you think about the managers, they’re mostly looking for this visibility. If I use the software engineering analogy, as engineering managers we are able to look at everyone’s pull request, commit history. We have full visibility on who’s working at what. A lot of these managers rely on self-reported progress.
With Comet, we provide them with this full visibility. As a manager, you can see every result of every experiment by every team member. The main goal there is that those managers can support their team members and guide them in understanding what’s working and what’s not working.
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