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Founder Interview

How SAFA Is Automating Safety Case Analysis for Safety-Critical Software While Raising a $200K SAFE Round (Interview with CEO Aarik Gulaya)

Interview Date
April 13, 2022
Interviewee
Aarik GulayaCEO
Watch
Watch the full interview

Company Metrics at Interview Time

Hard Committed (April 2022)

$125,000

Team Size (2022)

6 people

Notre Dame Equity Stake (2022)

20%

Historical Snapshot

These numbers were reported by Aarik Gulaya during the interview recorded in April 2022 and are a historical snapshot, not current figures. See SAFA’s current numbers.

Key Takeaways

  • 01SAFA is a Notre Dame spinout automating safety case analysis for safety-critical software in automotive, robotics, medical devices, and aerospace.
  • 02The company is pre-revenue at the time of the interview in April 2022.
  • 03SAFA is raising a $200,000 SAFE round with $125,000 hard committed and $25,000 soft committed, leaving $50,000 outstanding.
  • 04Notre Dame will retain a 20% equity stake in the spinout plus a nominal license fee.
  • 05CEO Aarik Gulaya holds approximately 10% equity, with the lead engineer and professor each holding about 9%.
  • 06The team has six people, all part-time at the time of the interview.
  • 07SAFA is targeting a beta program in Q2 or Q3 2022 and a full product release in Q1 2023.
  • 08LHP Engineering, a potential development partner in the automotive industry, has soft committed $25,000 to the SAFE round.
  • 09SAFA differentiates from IBM Doors and Jama Software through machine learning, deep learning, and native safety standards support built into the platform.
  • 10Aarik Gulaya was brought on specifically to commercialize the technology developed over 20-plus years by Professor Jane Cleland-Huang at Notre Dame.

Company Metrics at Time of Interview

MetricValueSource
SAFE Round Hard Committed (April 2022)$125,000Founder interview, April 2022
SAFE Round Soft Committed (April 2022)$25,000Founder interview, April 2022
SAFE Round Outstanding (April 2022)$50,000Founder interview, April 2022
Team Size (2022)6 peopleFounder interview, April 2022
Notre Dame Equity Stake (2022)20%Founder interview, April 2022
CEO Equity Stake (2022)10%Founder interview, April 2022
Professor Jane Cleland-Huang Equity Stake (2022)9%Founder interview, April 2022
Lead Engineer Alberto Equity Stake (2022)9%Founder interview, April 2022
AI Engineer Jin Feng Equity Stake (2022)2%Founder interview, April 2022
LHP Engineering Soft Commitment to SAFE (April 2022)$25,000Founder interview, April 2022
IBM Doors Enterprise Starting Price (competitor, cited in talk) (2022)$50,000Founder interview, April 2022
IBM Doors Per-User Seat Price Range (competitor, cited in talk) (2022)$500 to $1,600Founder interview, April 2022

Growth Breakdown

Revenue

SAFA is pre-revenue at the time of the interview. The company is targeting a beta program in Q2 or Q3 2022 with discounted pricing, and expects its first paying customers in Q1 2023 at a full license fee.

Customers

SAFA has no paying customers yet. The team is in talks with two to three development partners, including LHP Engineering in the automotive industry and two smaller companies in the robotics and agri-tech fields.

Team

The company has six part-time team members at the time of the interview, including a lead front-end engineer, a lead engineer, and an AI engineer. No full-time employees have been hired yet.

Funding

SAFA is raising a $200,000 SAFE round with a $2,000,000 cap and a 20% discount. At the time of the interview, $125,000 is hard committed, $25,000 is soft committed from LHP Engineering, and $50,000 remains outstanding. The round is expected to close by the end of the following month.

Growth Strategy

University Spinout and IP Licensing

SAFA is commercializing over 20 years of research from Professor Jane Cleland-Huang at Notre Dame, giving the company a deep technical foundation in traceability and natural language processing. Notre Dame retains a 20% equity stake and receives a nominal license fee in exchange for the IP.

Development Partner Pipeline

Rather than pursuing cold sales, SAFA is building relationships with two to three development partners who will help validate the product and refine advanced features. LHP Engineering in the automotive industry is the lead partner and has soft committed $25,000 to the SAFE round.

Differentiation Through Machine Learning

SAFA differentiates from established competitors like IBM Doors and Jama Software by automating the manual linking of documentation through deep learning and natural language processing, reducing the engineering burden of safety case analysis.

Native Safety Standards Integration

SAFA plans to embed safety standards directly into the platform, removing the need for engineers to memorize complex certification requirements. According to Aarik Gulaya, this native standard support is not offered by IBM Doors or Jama Software and can accelerate the speed to safety certification.

Staged Beta and Full Release Roadmap

The company is following a staged go-to-market plan: a beta program in Q2 or Q3 2022 with discounted pricing, followed by a full product release in Q1 2023. This approach allows SAFA to gather real-world feedback before committing to full commercial pricing.

Best Quotes

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.
I was brought on specifically to commercialize this technology into a standalone spinout from the university.
currently we are a 100% Notre Dame wholly owned, but in the next month, month and a half, we will be spinning out the company and Notre Dame will have a 20% stake in terms of the idea center. Then we'll also be paying a nominal license fee to the University of Notre Dame.
So currently we're looking at $200,000 at a two million dollar cap, 20% discount. We have 125 ks of that hard committed, 25 soft committed. We have 50,000 outstanding currently.
So the biggest and most obvious is the machine learning and deep learning aspect of it. So these are great tools. 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.
if we can provide them this type of support within the platform, we can increase that speed to safety certification.
we're looking at a beta program in about Q2 or Q3 of twenty twenty two. And then we're looking at a full release in Q1 of twenty twenty four or 2023, sorry, my mistake. So we'll probably be looking at that first paying candidate within that beta program.

What Happened Next

This interview captured SAFA at a very early stage in April 2022, when the company was pre-revenue, raising its first $200,000 SAFE round, and preparing to spin out of Notre Dame. The figures and plans described here reflect what Aarik Gulaya reported at that point in time and are not current. Visit the SAFA company profile on GetLatka for the latest available data on revenue, funding, and team growth.

View SAFA’s current profile and metrics

Full Transcript

Introduction and What SAFA Does

Nathan Latka

00:00Hey, folks. My guest today is Aarik Gulaya. He's the CEO of SAFA, a b to b SaaS company automating the safety analysis process for safety critical software. Aarik, you ready to take us to the top?

Aarik Gulaya

00:10>> 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

00:41>> can consider that a safety critical software.

Nathan Latka

00:43So you might sell to Delta Airlines and the software that runs the planes that they have to check right before every every takeoff?

Aarik Gulaya

00:49>> Yeah. Yeah. In theory, Delta Airlines could could use our product for for any of their safety case development around their planes.

Pricing and Competitor Benchmarks

Nathan Latka

00:56Interesting. Okay. And so how do you price this thing? What's the average customer paying per year?

Aarik Gulaya

01:00>> Yeah. So currently, we're pre revenue and very early stage. So when we're looking at pricing, we're typically using competitor pricing. So we were looking at IBM Doors, Jama Software. These are very large requirements management softwares in the space. 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

01:29>> in for whatever price they may put that at.

First Line of Code and University Origins

Nathan Latka

01:31So you're building, you're building, you're building. When did you write the first line of code? This year, last year, sometime else?

Aarik Gulaya

01:38>> I guess to give a little background, we've been working with a professor at the University of Notre Dame. Her name is Doctor Jane Cleland-Huang. And she's been working on traceability, specifically automating that process for the last twenty plus years. So if she was here, she'd probably say she started in early two thousands trying to figure this problem out.

Nathan Latka

02:00You guys though joining the team was last year?

Spinning Out of Notre Dame

Aarik Gulaya

02:03>> Yes. I was brought on specifically to commercialize this technology into a standalone spinout from the university.

Nathan Latka

02:09Yeah. So this is always we get this a lot with founders. I remember when I was at Virginia Tech trying to spin IP out of the university's research lab was a nightmare because they just had very archaic terms around ownership and all this kind of stuff. So is Notre Dame friendly here? How much equity does Notre Dame own in SAFA?

Aarik Gulaya

02:25>> Yeah. So we're we're working directly with the idea center at Notre Dame. They're their, you know, entrepreneurship center. They've typically the classic process is sort of just to license IP out to larger corporations. And then, in some cases that research may or may not come to light. In this case, we were attempting to build a startup within Notre Dame. So currently we are a 100% Notre Dame wholly owned, but in the next month, month and a

Notre Dame Equity Stake and License Fee

Aarik Gulaya

02:51>> half, we will be spinning out the company and Notre Dame will have a 20% stake in terms of the idea center. Then we'll also be paying a nominal license fee to the University of Notre Dame.

Nathan Latka

03:03Yeah, okay, got it, got it. Plus license fee. And then what does that leave for you, the professor and any other co founders?

Cap Table Breakdown

Aarik Gulaya

03:09>> Yeah, so we've sort of set aside for now in terms of first round investment, 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, 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

03:41>> AI engineer Jin Feng who will have 2% as well.

Nathan Latka

03:45Interesting. Okay. So between Jane, the lead engineer, you, the lead AI engineer, you guys altogether on 50%. Right?

Aarik Gulaya

03:52>> Just a a little bit under. Yeah.

Nathan Latka

03:54A little

Aarik Gulaya

03:55>> bit under, which we've gotten pushed back on.

Nathan Latka

03:58Oh, 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

04:22your Stripe account, you see your valuation real time, you can see what 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 get

04:46a 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 not

05:08built off random data. Again, you guys hear these interviews on YouTube. All these datas are built from real time valuation data points founder 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 going

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05:56you 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 inside the platform. I hope to see you there. Alright. Let's jump back into the

06:22interview. Yeah. And then the an an investor put some capital on their own, some above that. Notre Dame will keep 20% and that's how you're planning. Yep. Yep. Okay. Interesting. I guess why do 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 a 100%?

Aarik Gulaya

06:39>> Yeah. Yeah. So I mean, it 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 this university research, 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

Why Aarik Joined Instead of Starting Fresh

Aarik Gulaya

07:09>> 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.

First Customers and Development Partners

Nathan Latka

07:25So you're in charge of commercialization, who's going to be your first customer?

Aarik Gulaya

07:29>> Yeah, so right now, you know, we're finishing up our MVP and I know that term is used very broadly, 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

07:52>> 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 agri tech and mobile robotics.

Nathan Latka

08:08So is LHP engineering going to be paying you for this?

Aarik Gulaya

08:11>> 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 soft committed to $25,000 So,

Path to First Paid Customer

Aarik Gulaya

08:24>> 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.

Nathan Latka

08:35And so when do you think you can get your first paid customer spun up, right? You refresh the BB and T or Chase bank account and woah, there's 50 ks there.

Aarik Gulaya

08:43>> 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 twenty twenty two. And then we're looking at a full release in Q1 of twenty twenty four or 2023, sorry, my mistake. So we'll probably be looking at that first paying candidate within that beta program. Obviously, that'll be a discounted fee in terms of what a full license fee or licensed

09:11>> customer will look like. We'll probably see that in Q1 of twenty twenty three.

Nathan Latka

09:15What 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?

Pricing Model and Metrics

Aarik Gulaya

09:25>> 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 price their offering as well.

Nathan Latka

09:46Mhmm. And why what are you guys doing uniquely different than than than those two companies, IBM Doors and Jama software?

Differentiation from IBM Doors and Jama Software

Aarik Gulaya

09:53>> Yeah. Yeah. So the biggest and most obvious is the machine learning and deep learning aspect of it. So these are great tools. 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

10:20>> 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

10:44>> 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.

Team Size and Structure

Nathan Latka

10:56Very cool. How many folks are on the team today full time?

Aarik Gulaya

10:59>> Yeah, so full time, we currently we technically don't have any full time employees at the company, but we do have our lead front end engineer, our lead engineer.

Nathan Latka

11:11We have two So I guess how many are how many are part time total?

Aarik Gulaya

11:15>> Yeah. Yeah. So four. About six, six people. Six. Yeah.

Nathan Latka

11:19And so because you're still waiting on MVP to get done, are you in charge of raising the safe round as head of commercialization?

Aarik Gulaya

11:24>> Yes. Yes. That is 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.

Nathan Latka

11:40And so how much are you going to raise?

SAFE Round Details and Fundraising Progress

Aarik Gulaya

11:43>> So currently we're looking at $200,000 at a two million dollar cap, 20% discount. We have 125 ks of that hard committed, 25 soft committed. We have 50,000 outstanding currently.

Nathan Latka

11:56Very cool. And so when do you think that'll close?

Aarik Gulaya

11:58>> 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.

Nathan Latka

12:10Well, you're off to the races, Aarik. It's gonna be fun to watch. You have to come in six months and twelve months, give us an update. Okay?

Famous Five

Aarik Gulaya

12:15>> Yeah. Yeah.

Nathan Latka

12:15Would be awesome. Before we wrap up, let's chat through the famous five here. Number one, favorite business book.

Aarik Gulaya

12:21>> Favorite business book.

12:24>> It's kind of a cop out, Start With Why.

Nathan Latka

12:27Number two, is there a CEO you're following or studying?

Aarik Gulaya

12:32>> Masayoshi san, even though I wouldn't really consider him as much of a CEO, but more of a holdings, I guess SoftBank's more of a holdings company now, but yep.

Nathan Latka

12:41Number three, what's your favorite online tool for building the business?

Aarik Gulaya

12:46>> Notion.

Nathan Latka

12:47Number four, how many hours of sleep do get every night?

Aarik Gulaya

12:52>> Five to six.

Nathan Latka

12:53Okay. And what's your situation? Married, single, kids?

Aarik Gulaya

12:56>> Sing or well, I'm not single. I'm I'm in a relationship. Long term No kids. I'm married. Yeah. No kids.

Nathan Latka

13:03Alright.

13:04How old are you, Aarik?

Aarik Gulaya

13:05>> I am 27 years old.

13:07>> 27.

Nathan Latka

13:08Last question. Something you wish you when you were 20.

Aarik Gulaya

13:15>> If you give your all to something, it will work out. Don't don't stress out about it.

Closing Thoughts

Nathan Latka

13:20Guys, there you have it. Safa.ai, Notre Dame's spinout. And in case you're not familiar with how those spinouts work, you know, they're anticipating Notre Dame will own about 20% of the IP. The professor that developed it own about 9%. Aarik in charge of commercialization will own, call it 10%. And then some key engineers and all their employees own 20% to 30% in addition to the investors coming in on their $200,000 safe right now that they're closing

13:40on a 2,000,000 cap. We hope they can get it done. They're building software that helps safety critical infrastructure manage and make sure testing's working, competing directly with IBM Doors and Jama software. We'll see what happens next. Aarik, thanks for taking us to top.

Aarik Gulaya

13:52>> Cool. Thank you, Nathan.

Nathan Latka

13:55One 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 1PM

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15:04up for that @nathanlatka.comslashslack. 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 counter those people. We

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