Begin AI Revenue, Valuation & Funding (2025)

[00:00] Hey, folks. My guest today is Rima Alshik. She's a three time Founder and Engineer who has a proven track record in bringing her technology to market. She's helped companies of all sizes, startups, and scale ups. 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? [00:18] >> Yeah, let's go. [00:19] So just to be clear, you mentioned all those customers you work with. Did you start this with an agency? [00:25] >> Begin? No. Begin is a platform from the get go. So we're still prelaunch. At the moment. We're still testing with a select customer group. [00:35] So walk me through that. How many customers are you testing with today? [00:39] >> We're testing with a 10 small like groups, like a group of customers just to test the platform viability and feasibility before we go GA. Yeah. [00:49] And so how did you find these folks? Is this cold outreach or friends of yours or what? [00:54] >> Well, [00:57] >> through the years, through like ten years, I've had the luxury of working in 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. Yeah. [01:16] What's the Can you talk about any of these customers and how they're using you in this testing phase? [01:21] >> Yeah, for sure. So we have We worked initially with the dating app who was testing our product to detect fake profiles. 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 [01:52] >> found a way to make these scale challenges meaningful to them and turn them to their advantage. Like Amazon recommendations, a large chunk of their revenue. Or you can look at [02:05] >> some dating companies like detect fake profiles 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. [02:32] Do make these 10 customers pay for the test or is it free? [02:37] >> 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. And now we're getting to the point where, like, we're getting ready to launch. And then as we launch, I'm confident that some of these customers will turn into paying customers. [02:56] And, Rima, you keep saying we. How many folks are on the team today? [03:00] >> Great question. We're about 10 between part time and full time. Six is core team full time. [03:06] Six full time. And are you the sole founder? [03:08] >> I am the sole founder, yeah. [03:10] 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? [03:17] >> Well, to be honest with you, like I started this as a, because I was trying to solve a very small problem and tinkering through the problem, I found a very general purpose solution. 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 datasets in a private way without, you know, without compromising the security and their own Kinda like [03:42] a data lake, something that I don't know Yeah, what's data lake or [03:45] >> exactly. Well, like, think of it as like an ecosystem of players who are working together, like to fight scam or [03:54] >> build the customer experiences across devices like cars, watches, etcetera. So when found this, you know, 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 [04:19] >> trying to catch up someone to where, you know, where this is going, felt like more of a distraction than actually, [04:26] >> you know, positive value. [04:28] So, Rima, are you rich? How are you paying six people full time with with with no revenue yet? [04:33] >> We have we raised the pre seed round. So we have to yeah. [04:38] Oh, what's going on there, YouTube? Good to see you guys. Now imagine this. You love watching these interviews with SaaS founders. But imagine if we took all of the valuation data out from over 2,807 interviews I've done manually. Saves you a lot of time. Well, we've done this. We've built it into the beautiful interface inside of Founderpath. Check this out. I'll show you how you can access this in a second, but you log in, you connect [05:01] your Stripe account, you see your valuation real time, you can see what it changed over the past eighty eight days and even set goals for valuation this year. Now the secret evaluation is there's many different ways to value a SaaS business. So the reason you're gonna see three or four different valuations inside of your Founderpath dashboard, this is all free by the way, is because depending on who's doing the buying of your SaaS company, you're gonna [05:26] get a different valuation. A VC is gonna pay a different valuation, private equity firm is different. If you're gonna do a minority sale, that's different. And if you sell the whole business, that's a different valuation. You can see all those when I hover over here. Right? So the teal is what a VC would pay. Yellow is what private equity and red is if you sold the whole thing outright. Now what's cool about this is this is [05:47] not built off random data. Again, you guys hear these interviews on YouTube. All these datas are built from real time valuation data points founders share with us on the show. So traction 1,200,000 seed round 3.7 raise. They sold 22% of their business. Go in here and filter by the event. Maybe you only wanna see companies that have sold the whole business. Well, here are a bunch that have been acquired the valuation and the multiple. Maybe you're [06:13] going out right now and you're raising your seed round. We'll go in here and look at all this recent seed deals that went down, what they raised, what valuation they raised at and what percent that they sold. There's never been a larger dataset of SaaS valuations than what you can get now inside of Founderpath. [06:31] And we're thrilled to bring it to you. [06:33] Alright. We're gonna go back to the YouTube video here in a second, but if you wanna check this tool out, if you wanna jump in and sign up, you can check it out for free to get your valuation at this link. This link, founderpath.com/products/valuations. Or if you go to founderpath.com and hover over products, click on get your valuation here, and go ahead and sign up to give it a whirl. Again, all that valuation data live right [06:59] inside the platform. I hope to see you there. Alright. Let's jump back into the interview. Okay. So how much did you raise in the pre seed? [07:05] >> A million dollars. [07:06] Okay. So now the story is making more sense. So pre seed, when did you raise that? [07:13] >> It was December last year. So December 2021. Yeah. [07:16] 2021. Okay. So you raised a million pre seed. Now most folks pre seed sort of like a million on a 5,000,000 cap. Was 5,000,000 your valuation, something like that? [07:25] >> No. It was 10 pre. [07:27] Okay. So you're a great negotiator. [07:30] >> Well, the technology we're building is really hard. I mean, it's a 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 doing all the processing on devices. And that basically eliminates a year from the timeline of production for companies. So that's really significant. And it can I think this company can be really huge? [07:58] Rima, I love how you're betting on yourself. You know, you've done two things where most everyone else These are the two most dilutive events in a company's history, your co founder and your seed round. You're doing it a 100% yourself and most people sell 20%, 25% of their seed round. You only sold a little under 10%. So I just love that you're betting on yourself going all in. This is just fantastic. Now, people are gonna be [08:19] listening going, Wait, what did her deck look like? How would she get a million on 10? Is she an exited founder? Why did investors believe her? Tell me more about that. [08:28] >> Well, I mean, what I am building is something that I know inside out. I can talk about it for like years. So for the last ten years, I've been dealing with scale challenges. So I've helped companies of all sizes to like go from having a few 100,000 users to dealing with like those million customers hitting their databases at scale. [08:48] What are some of those companies? Can you name a couple of them? Do we know them? [08:53] >> Sure. So in [08:57] >> I'm just like rolling through all the NDAs in my head, but Oh, [09:01] hold on. There might be a better way to do this. I can just I can go to your LinkedIn, right? And read off some right? Of your historic Lixar fueled by BDO. You were the data and AI practice lead, right? [09:12] >> Yeah. So we had about 50 data engineers, data scientists helping all kinds of like enterprises in automotive industry, in [09:22] >> airlines, airports, healthcare. We've helped a lot of different companies deal with some of these scale challenges that I'm mentioning and building their data platforms. [09:33] Before that, you were a lead software engineer at LiquidNet. Before that, you were a CEO and co founder at Mokus.io, which looks like a dev shop, right? Is that what that was? [09:41] >> Mokus.io was an automated dev shop. So we had, like, we had we built, a 300 engineers network, and when we built an algorithm that can build teams for the task at hand for releases. So that was a cool one actually. We made about a million dollars in revenue in the first year of operations. So that's one of the values. [10:03] So what happened to it? How much did you do in 2017? Or was million your best year? [10:09] >> We saw it was it in 2017? We did Yeah. So like we first, you know, first there was like pre launch activities, obviously, so preparations. And then as soon as we launched with we got to like the million dollars in revenue about by the end of the year. So say like, we'd exit the year around like a 100 k MRR. [10:31] I was gonna say, and just to be clear though, when you say a 100 MRR, that's project volume, right? You have to pay out a large chunk of that 70% to the engineers, right? [10:40] >> Correct. Yeah. Yeah. That's Yeah. It was getting optimized over time though. So like it would go, you know, it would start at like 70% and then goes down to like 60%. But eventually we're reinvesting everything, making back in the business. [10:54] So what happened? Did you sell it? [10:57] >> So Mokus happened at the time when, so I'm a Syrian founder, so I come from Syria and it happened at the time when the Syrian war was at its peak and I had to change country. Lucky for me, Mokus, I built it when, [11:12] >> you know, without venture backing, so I built it all by myself. So I didn't have to, you know, deal with complexities of closing down shop. I had to close it down because I needed to change country. [11:26] I see. Yeah. Okay. And then taking back one time before that, so you had a company before that called Nabish, I believe, right? For almost three years. [11:35] >> Nabish was a Freelance marketplace. Yeah. So [11:42] >> was so in MENA, so Middle East and North Africa. So that is a [11:49] >> very large and complex region [11:55] >> from a population density perspective and geopolitical scenarios. And the issue there is like you have a lot of talented people who don't have access to opportunities or the other way around, like employers who can't find a talent because of lack of infrastructure. So we wanted to build like the first infrastructure that enables that talent access. We did really well. We we became really famous at the time with our work, you know. [12:19] What was what year was your highest revenue year? [12:23] >> So Nabish, I would say like last year before early was was reaching its highest, you know, revenue. But I would say I think we were like getting to like 200,000 users, if I remember well. [12:40] What was revenue [12:40] >> in 2015 at Nabish? Do you remember? [12:44] >> I don't, I'm sorry, but it wasn't, I wouldn't say it was more than like $50, $60 ks. [12:54] >> MRR. MRR, yeah. [12:55] Okay. So the reason I ask those questions is your ability to go raise a million on 10 for this idea. You've had companies before, you've grown them in revenue, you fled a war. I mean, this is like, you're an incredible individual. So you were able to point to a lot of this history. So I guess let's flip it back to these first 10 customers you're working with now. Let's say that the test period ends. What's the [13:18] success metric? How do you know if they're gonna pay or not? [13:21] >> Let me share with you where my ability to raise funding comes from. If I look at what we're building and the massive opportunities that we have right now is basically where this came from. There are a lot of companies building for facilitating for customers to benefit from their own data sets. It's very hard to find a way to, you know, optimize your customer experience [13:53] >> with your own data set if you have blind spots. And the potential we're providing is based on the ability to pull data from different companies and build that network effect. And that technology is really hard to build. And like I said, it was an accidental discovery for me. And having like multiple patents pending, that's where all that, you know, the potential came from and that's where the I see. [14:18] But, Rima, we have we have about two minutes left here. So, like, let's say you're testing with a dating app to detect fake profiles. Right? So you're effective how are you identifying that fake profile so your other customers can know not to, you know, understand that that is a fake profile if they if that person tries to sign up for their account, right, or or their their business? [14:35] >> Yeah. So the way we do is, like, we we build, like, mathematical representations of each person and their activities in an application so that we don't have to share data between applications. And when that mathematical mathematical representation appears in a different application, they know like, oh, that looks fake using our algorithms. So [14:56] You're a collection of patterns really. [14:58] >> DNA, fake DNA, basically. [14:59] Technological fake DNA. [15:01] >> Correct. Yeah. [15:03] Very interesting. So what do you think you'll charge for this? Like, I mean, is this something where you come out of the gate, you're closing a $100,000 a year deal, or is it gonna be like, you know, PLG product led growth motion, $10 a month sort of deal? [15:13] >> I mean, the more users you have, the more users you connect with, the more value you create. So the way we think of it is like, if I can charge a penny per device, we're still, you know, our customer is benefiting, we're benefiting. [15:25] So that's what you think your model will be per device, penny per device, something like that? [15:28] >> Yeah. That's our most educated guess right now. We provide like, you know, a commitment discount, [15:35] >> volume discount. [15:37] How many devices are you testing on right now across the 10 test accounts, 10 customers? [15:41] >> About the last test we ran this morning was about a million and a half users with 200,000,000 interactions. [15:51] 200,000,000 interactions. So 1,500,000 users is one user correlated to one device? It's a one to one? [15:57] >> Correct. [15:58] Yeah. Okay. Interesting. Okay. I I love this. I'm I'm curious what happens once you launch your paid plan. We'll see what happens. In the meantime though here, Rima, let's wrap up with the famous five. Number one, favorite business book. [16:08] >> Favorite business book. I wanna say like I'm gonna go a little, you know, [16:17] >> be an outlier. Like, I think I love philosophy. So like I read Eastern philosophy. So I'm going to say my favorite business books come from like the Vedas, which is like the Eastern philosophy of like how to think holistically of the world. [16:32] I love that. Number two, is there a CEO you're following or studying? [16:36] >> Yeah, a lot of them. Today I wanna say I'm really impressed by a CEO who's a Canadian CEO for, [16:48] >> his name is Ali Fadhiri. He's the CEO of a fintech company in Canada. [16:53] >> Very cool. [16:54] Number three, favorite online tool for building Begin. [16:58] >> Favorite online tool for building Begin. [17:03] >> We're using HubSpot a lot. [17:05] >> Fair enough. [17:06] Number four, how many hours of sleep do you get every night? [17:10] >> Well, I try to hit six, seven hours if I could, but reality is we're looking at six maximum. [17:16] And Rima, what's your situation? Married, single, kids? [17:20] >> I'm married, with a four month old. [17:22] Oh, congratulations. Very cool. [17:24] >> Thank you. [17:25] And can I ask how old you are? [17:27] >> I'm 33. [17:28] >> 33. [17:29] Last question. Something you wish you knew when you were 20. [17:33] >> Oh, boy. [17:37] >> You know, like, I feel very lucky because I learned what does it look like to have an executive board in my early twenties. So I think that was really helpful for me. But what I learned the hard way and I wish I learned the first day is that every technology is centered about people, around people. So like you have to build a technology person first. And that's why everything we're thinking about, business model, technology, product is [18:02] >> all user first. [18:03] Guys, begin.ai will help apps understand what's a fake account. She's building basically technological DNA. If that DNA or pattern matches across her different customers, they all benefit from learning from each other and still in an anonymized way. No data issues there. She raised a million bucks pre seed on a 10,000,000 pre money valuation. Was able to raise that valuation because she has successful companies in the past, growing one of them to over $1,000,000 in revenue. She's [18:27] also a sole founder owning a 100% at start as she looks to scale. Really betting on herself. Rima, we're rooting for you. Thanks for taking us to the top. [18:33] >> Thank you, Nathan. [18:36] One more thing before you go. We have a brand new show every Thursday at 1PM Central. It's called Shark Tank for SaaS. We call it deal or bust. One founder comes on, three hungry buyers, they try and do a deal live and the founder shares back end dashboards, their expenses, their revenue, ARPU, CAC, LTV, you name it, they share it and the buyers try and make a deal live. It is fun to watch every Thursday one [19:01] p. M. Central. Additionally, remember these recorded founder interviews go live. We release them here on YouTube every day at two p. M. Central. To make sure you don't miss any of that, make sure you click the subscribe button below here on YouTube, the big red button and then click the little bell notification to make sure you get notifications when we do go live. I wouldn't want you to miss breaking news in the SaaS world, whether it's [19:22] an acquisition, a big fundraise, a big sale, a big profitability statement or something else. I don't want you to miss it. Additionally, if you wanna take this conversation deeper and further, we have by far the largest private Slack community for B2B SaaS founders. You want to get in there. We've probably talked about your tool if you're running a company or your firm if you're investing. You can go in there and quickly search and see what people [19:44] are saying. Sign up for that at nathanlatka.com/slack. In the meantime, I'm hanging out with you here on YouTube. I'll be in the comments for the next thirty minutes. Feel free to let me know what you thought about this episode and if you enjoyed it, click the thumbs up. We get a lot of haters that are mad at how aggressive I am on these shows, but I do it so that we can all learn. We have to [20:04] counter those people. We got to push them away. Click the thumbs up below to counter them and know that I appreciate your guys'support. Alright, I'll be in the comments. [20:12] See you.