SaaS Interviews with CEOs, Startups, Founders
She Fled the Syrian War Then Raised $1m, Fraud AI Tool now Worth $10m
19 Apr 2022
Chapter 1: What challenges did Rima face while building her AI platform?
Do you make these 10 customers pay for the test or is it free?
At the moment it's free because for us, you know, we're building a very challenging platform. So for us, really, it was about proving the viability of the technology first.
You are listening to Conversations with Nathan Latka, where I sit down and interview the top SaaS founders, like Eric Wan from Zoom. If you'd like to subscribe, go to getlatka.com.
We've published thousands of these interviews, and if you want to sort through them quickly by revenue or churn, CAC, valuation, or other metrics, the easiest way to do that is to go to getlatka.com and use our filtering tool. It's like a big Excel sheet for all of these podcast interviews. Check it out right now at getlatka.com. Hey folks, my guest today is Rima Al-Sheikh.
She's a three-time founder and engineer who has a proven track record in bringing her technology to market.
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Chapter 2: How does Rima select customers for testing her platform?
She's helped companies of all sizes, startups, and scale-ups, and along with Fortune 100 companies, research, build, and ship AI and software to production, serving millions of consumers per day. Rima, you ready to take us to the top?
Yeah, let's go.
So just to be clear, you mentioned all those customers you work with. Did you start this with an agency?
Begin? No. Begin is a platform from the get-go. So we're still pre-launch. At the moment, we're still testing with a select customer group.
Chapter 3: What unique solutions does Begin AI offer to its customers?
So walk me through that. How many customers are you testing with today?
We're testing with 10 small groups, selected group of customers, just to test the platform viability and feasibility before we go GA.
And so how did you find these folks? Is this cold outreach or friends of yours or what?
Well, you know, through the years, through like 10 years, I've had the luxury of working with a lot of different companies in the tech space. So it wasn't very hard for me to kind of like select the best customers who are tech enabled to test and provide feedback.
Can you talk about any of these customers and how they're using you in this testing phase?
Yeah, for sure. So we have, you know, we worked initially with a dating app who was testing our product to detect fake profiles.
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Chapter 4: What funding strategies did Rima use to support her startup?
So, I mean, Begin AI is really useful for customers who are scaling their products so that they can, you know, As customers scale, they hit scale challenges. So they're like, we have a lot of customers using our product. We need to find a way to personalize the experience to them or detect fraudulent interactions.
And large players found a way to make these scale challenges meaningful to them and turn them to their advantage. Like Amazon recommend the revenue is really a large chunk of their revenue. Or you can look at some dating companies like detect fake profiles and and maintain them in a particular contained environment and so on.
So what we do is we provide these solutions to scale-ups without having to build their own in-house expertise or data platforms or hire machine learning engineers, which take a long time. So yeah, so that's the kind of like testing we've been working on, you know, detection of fake content and recommendations.
Chapter 5: How does Rima's background influence her entrepreneurial journey?
Do you make these 10 customers pay for the test or is it free?
At the moment, it's free because for us, we're building a very challenging platform. So for us, really, it was about proving the viability of the technology first. And now we're getting to the point where we're getting ready to launch. And then as we launch, I'm confident that some of these customers will turn into paying customers.
And Rima, you keep saying we. How many folks are on the team today?
Great question. We're about 10 between part-time and full-time. Six is core team full-time.
Chapter 6: What lessons did Rima learn from her previous ventures?
six full-time. And are you the sole founder?
I am the sole founder. Yeah.
Oh, I love that. Very cool. You know, everyone says you have to have a co-founder, like you go find a co-founder. Why'd you decide to be, why'd you decide to go at this yourself?
Well, to be honest with you, like I started this as a, because I was trying to solve a very small problem and, and tinkering through the problem, I found a very general purpose solution.
And, and I was like, holy moly, this could be huge, you know, because I found a way to connect, to get companies to work together, to enrich their data sets in a private way without, you know, without compromising the security and their IP.
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Chapter 7: How does Begin AI plan to scale and generate revenue?
Like a data lake, something like a data lake or something.
Yeah, exactly. Well, think of it as an ecosystem of players who are working together to fight scam or build customer experiences across devices like cars, watches, etc. So when I found this process to do this solution, I thought, this could be huge, but I need to talk to someone like to figure out if I'm like, am I living in my head?
So I started calling potential customers and I wanted to try to find a co-founder, but I was moving. I was already flying at a high speed and trying to catch up someone to where, you know, where this is going felt like more of a distraction than actually, you know, positive value.
So Rima, are you rich? How are you paying six people full time with, with, with no revenue yet?
Yeah.
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Chapter 8: What future opportunities does Rima see for her company?
We raised the pre-seed round.
Okay. So how much did you raise in the pre-seed?
A million dollars.
Okay. Now the story is making more sense. So pre-seed, when did you raise that?
It was December last year. So December 2021.
2021. Okay. So you raised a million pre-seed. Now most folks pre-seed sort of like a million on a 5 million cap. Was 5 million your valuation, something like that?
No, it was 10 pre-seed.
Okay, so you're a great negotiator.
Well, the technology we're building is really hard. I mean, if you look at what we're doing, you might think it's a crowded space. Everybody's trying to simplify workflow and machine learning. But we're really taking it to a whole new level by doing all the processing on devices. And that basically eliminates a year from the timeline of production for companies. So that's really significant.
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