SaaS Interviews with CEOs, Startups, Founders
Notre Dame Owns 20% Of this Safety SaaS Spin Out, Raising $200k Now
26 Apr 2022
Chapter 1: What is the main topic discussed in this episode?
And so how much are you looking to raise?
Chapter 2: How much funding is Safa currently seeking?
So currently we're looking at $200,000 and a $2 million cap, 20% discount. We have 125K of that hard committed, 25 soft committed. So we have 50,000 outstanding currently. 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 these podcast interviews. Check it out right now at getlatka.com. Hey, folks. My guest today is Ark Goliath.
He's the CEO of Safa, a B2B SaaS company operating the safety analysis process for safety-critical software. Ark, you ready to take us to the top? Yeah. Yeah, most definitely. What's an example of safety-critical software? Yeah, so safety-critical software, specifically, we can look at a few different industries, the automotive industry, robotics industry, medical devices, and aerospace.
Essentially, these are exceptionally complex systems, and they're dealing with humans in many cases, either in the transportation of them or they're working around them. So in any case where a failure can happen in the operation of that software that may harm a human, we can consider that a safety-critical software.
So you might sell to Delta Airlines and the software that runs the planes that they have to check right before every takeoff. Yeah. Yeah. In theory, Delta Airlines could use our product for any of their safety case development around their planes. Interesting. Okay. And so how do you price this thing? What's the average customer paying per year? Yeah.
So currently, you know, we're, we're pre-revenue and very early stage. So when we're looking at pricing, we're typically using a, you know, competitor pricing. Uh, so we were looking at IBM doors, JAMA software. These are very large requirements, management softwares in the space, uh, for reference there, IBM doors can start at $50,000 for an enterprise application.
Then they'll charge any additional user seats. Typically, this ranges from $500 to $1,600. And then any additional functionality and add-ons coming in for whatever price they may put that at. So you're building, you're building, you're building. When did you write the first line of code? This year, last year, sometime else?
Yeah, so I mean, I guess to give a little background, you know, we've been working with a professor at the University of Notre Dame. Her name is Dr. Jane Cleland-Huang, and she's been working on traceability, specifically automating that process for the last 20 plus years. So if she was here, she'd probably say she started in early 2000s trying to figure this problem out.
You guys, though, joining a team was last year? Yes. I was brought on specifically to commercialize this technology into a standalone spin out from the university. Yeah. So this is always, we get this a lot with founders.
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Chapter 3: What industries rely on safety-critical software?
Plus license fee. And then what does that leave for you, the professor, and any of their co-founders? Yeah, yeah. So, you know, we've sort of set aside for now in terms of first round investment, you know, in a seed round or something like that, as well as an employee options pool around the 40 to 50% of that equity table or that cap table.
In terms of what goes to everyone else, you know, Jane is going to be keeping like about a 9% equity stake. Alberto, who is our lead engineer, another 9%. Myself will be at 10%. And then we have our AI engineer, Jin Fang, who will have 2% as well. Interesting. Okay. So between Jane, the lead engineer, you, the lead AI engineer, you guys all together own 50%, right? Just a little bit under. Yeah.
A little bit under, which we've gotten pushback on. Yeah. And then an investor puts some capital on their own, some above that. Notre Dame will keep 20% and that's how you're planning. Okay. Yeah. Okay. Interesting. I guess, why do a guy like you, you're bright, you're sharp, you can commercialize. Why get in a mess like this? Why not just launch something yourself from scratch and own 100%?
Yeah. Yeah. So, I mean, it really was, I guess, a happy accident or whatever you want to call it, an event of chaos where I happened to interview for a random position looking at founder associates for for this university research. Right. Do you have the skills or the background to essentially commercialize this technology for me? It's just quite a phenomenal piece of technology.
The natural language processing models and deep learning models that we're applying to this problem are exceptionally generalizable. So on my own end, I've looked at starting separate companies around natural language processing, and it just seemed like a better fit for me and my skills for something that we can expand into many industries for. So you're in charge of commercialization.
Who's going to be your first customer? Yeah, so right now we're finishing up our MVP and I know that term is used very broadly, but this will be somewhat of a more put together first product offering, if you will. We're currently looking at two to three development partners that we're going to be starting within the next month to month and a half. One of those is LHP Engineering.
We're currently in talks about what will that potential partnership look like? How can we add to their process? They work specifically within the automotive industry and will be helping us with some implementation for some of our more advanced features. And then we're looking at two other smaller companies that work in the robotics field, specifically within agritech and mobile robotics.
Also, is LHP Engineering going to be paying you for this? So LHP Engineering is actually going to, right now we're discussing them coming in on our safe round. So they would come in for potentially, they've self-committed to $25,000. So, you know, I guess technically we won't consider that payment. We may have them pay us a nominal amount in order to say it's a paid pilot.
But moving forward, the other pilot partners will be paying us in.
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Chapter 4: How is Safa's pricing structured compared to competitors?
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That's NathanLatka.com forward slash P-A-R-A-G-O-N. And so when do you think you get your first paid customer spun up, right? You refresh the BB&T or Chase Bank account. Whoa, there's 50K there. Yeah. Yeah. So right now, at least the way that the product roadmap is turning out, we're looking at a beta program in about Q2 or Q3 of 2022.
And then we're looking at a full release in Q1 of 2024 or 2023. Sorry, my mistake. Um, so we'll probably be looking at that first paying candidate, uh, within that beta program. Obviously that'll be a discounted fee in terms of what a full license fee or licensed customer will look like. We'll probably be probably see that in Q1 of 2023.
What are you learning right now as you talk and have commercialization conversations, what can you price against? Is it sort of number of software runs or tests completed in a certain month or what's the metric? Yeah, so that's an option. It's an option that we're sort of open to. The traditional way we've seen pricing in this industry is how many users are actually on the platform.
So within an engineering team, do you have 10 people who would be interacting with this platform, 20 people? And typically that's how IBM Doors and JAMA Software price their offering as well. And what are you guys doing uniquely different than those two companies, IBM Doors and JAMA Software? Yeah, yeah.
So, I mean, the biggest and most obvious is the machine learning and deep learning aspect of it.
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Chapter 5: What is the background of Safa's founding team?
So, I mean, these are great tools, right? We're not going to knock against them, but essentially they provide a blank slate for companies to come into and create all of their documentation, link all of this documentation together and provide change analysis that way. Where SAFA is differentiated is within that application of deep learning and natural language processing.
So as opposed to having an engineer having to manually go through and link all of these things together, we can automate that process, partially automate it so that we can speed that up. In terms of change analysis, we're able to better understand how one change in a part of a complex system affects a top level requirement or something like this.
And then finally, we're also looking at integrating safety standards directly into the platform, sort of native standard support, which IBM Doors and JAMA, they don't provide this. Engineers typically need to know this like the back of their hand. But if we can provide them this type of support within the platform, we can increase that speed to safety certification. Very cool.
And how many folks are on the team today full time? Yeah, so full-time, we technically don't have any full-time employees at the company, but we do have our lead front-end engineer, our lead engineer. We have two... So I guess how many are part-time total? Yeah, so four of them. About six, six people. Six.
And so because you're still waiting on MVP to get done, are you in charge of raising a safe round as head of commercialization? Yes. Yes. That is, I handle all of the business side in terms of setting up the websites, getting all of the product market fit validation into place, any infrastructure we may need. And then finally also interfacing with VCs and getting that funding.
And so how much are you looking to raise? So currently we're looking at $200,000 and $2 million cap, 20% discount. We have 125K of that hard committed, 25 soft committed. So we have 50,000 outstanding currently. Very cool. And so when do you think that'll close? We're looking to close that at the end of next month that we should have everyone in.
And I'm currently meeting weekly with people to drum up interest. Well, you're off the raises, Ark. It's going to be fun to watch. You have to come in six months, 12 months, give us an update, okay? Yeah. All right. Before we wrap up, let's chat through the famous five here. Number one, favorite business book. Favorite business book? It's kind of a cop-out. Start with why.
Number two, is there a CEO you're following or studying? Masayoshi-san, even though I wouldn't really consider him as much of a CEO, but more of a holdings. SoftBank's more of a holdings company now, but yeah. Number three, what's your favorite online tool for building the business? Notion. Number four, how many hours of sleep do you get every night? Five to six. Okay. And what's your situation?
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Chapter 6: What equity stake does Notre Dame hold in Safa?
Married, single kids? Well, I'm not single. I'm in a relationship. Not married. No kids. But not married. Yeah, no kids. All right. How old are you, Ark? I am 27 years old. 27. Last question. Something you wish you when you were 20. Something I wish... If you give your all to something, it will work out. Don't stress out about it. Guys, there you have it. Stop on that AI. Notre Dame spin out.
And in case you're not familiar with how those spin outs work, they're anticipating Notre Dame will own about 20% of the IP. The professor that developed it will own about 9%. ARC in charge of commercialization will own, call it 10%.
And then some key engineers and other employees own 20% to 30% in addition to the investors coming in on their $200,000 safe right now that they're closing on a $2 million cap. We hope they can get it done. They're building software that helps security-critical infrastructure manage and make sure testing is working and competing directly with IBM Doors and JAMA software.
We'll see what happens next. Ark, thanks for taking us to the top. Thank you, Nathan.