Molham Aref On Selling Two $100+ Million Companies And Now Raising $122 Million To Help Organizations In Efficient, Data And AI-Driven Decision-Making

Molham Aref’s journey as an entrepreneur is nothing short of fascinating. With multiple successful ventures, big exits, and a deep history in AI, his story offers insights into the trials, triumphs, and evolution of the tech world, especially around the rise of AI.

Molham’s latest venture, RelationalAI, has attracted funding from top-tier investors like Madrona Venture Group, Addition, Tiger Global Management, and Menlo Ventures.

In this episode, you will learn:

• Molham Aref’s entrepreneurial journey highlights the importance of adaptability and cultural understanding, which shaped his success in building global teams.
• His early fascination with AI led to groundbreaking work in predictive technologies that transformed business decision-making across industries.
• Leaving a secure corporate job at AT&T for a startup taught Molham the value of agility and aligning cutting-edge tech with effective market strategies.
• Successful business ventures like HNC and Retek combined innovative technology with smart market strategies, leading to multimillion-dollar exits and IPOs.
• Molham’s experience with failure taught him the critical importance of timing, showing that market readiness often determines success or failure.
• RelationalAI’s focus on simplifying AI infrastructure for enterprise applications aims to help businesses make smarter, data-driven decisions at scale.
• Throughout his journey, Molham emphasizes persistence, the right partnerships, and resilience as keys to overcoming challenges and achieving long-term success.

 

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About Molham Aref:

Molham Aref is the founder and CEO of Relational.ai, LogicBlox and Predictix. He has over 25 years of experience leading teams that deliver high-value predictive and prescriptive analytics solutions to some of the world’s largest enterprises.

Previously, he was CEO of Optimi (acquired by Ericsson), a leader in wireless network simulation and optimization, and co-founder of Brickstream (now Nomi), a leading provider of computer-vision-based behavior intelligence solutions.

Molham has held senior leadership positions at Retek (now Oracle Retail) and HNC Software (now FICO). He received his bachelor’s in Computer Engineering, M.S. in Electrical Engineering, and M.S. in Computer Science from Georgia Tech.

Connect with Molham Aref:

• LinkedIn
• Crunchbase
• RocketReach
• Researchr

Read the Full Transcription of the Interview:

Alejandro Cremades: Alrighty, hello everyone, and welcome to the DealMaker Show. Today, we have an incredible founder, a repeat entrepreneur who has built and exited multiple companies successfully. He has experienced both bootstrapping and raising capital, and right now, he is doing something amazing.

Alejandro Cremades: In the world of AI, he has been involved in this space long before it was even called AI. We’re going to be discussing all the good stuff—building, scaling, financing, and exiting. So, brace yourself for a very inspiring episode. Without further ado, let’s welcome our guest today, Molham Aref.

Alejandro Cremades: Welcome to the show.

Molham Aref: Thank you, Alejandro. It’s a pleasure to be here. Thanks for having me.
Alejandro Cremades: You were originally born in Beirut, Lebanon, but you moved quite a bit with your family—Switzerland, Egypt, and many other places. How was life growing up for you?

Molham Aref: That was my normal. My dad worked for a multinational company called DuPont, and every few years, we had to pick up and move. There’s something incredibly valuable about the experience of being the new person in an unfamiliar environment where you don’t fully understand the culture or language.

Molham Aref: The environment constantly changed, and I learned to listen, observe, absorb, and adapt. More importantly, I realized the common threads of humanity—no one has a monopoly on good or bad. Every culture and society has its own strengths and appealing aspects.

Alejandro Cremades: You mentioned something profound—learning to adapt. Moving from place to place, making new friends at a young age, I imagine that shaped you significantly. How do you think that experience influenced who you are today?

Molham Aref: I think it’s essential. I still keep in touch with friends I made along the way, even through my transitions to college, graduate school, and startups. After the exit from my most recent startup before this one, I had a daughter who was around eight or nine years old at the time, and I wanted her to have the same experience. So, we moved from Atlanta to New York.

Molham Aref: I wanted her to experience moving and adapting. We lived in New York City for a couple of years before moving to the Bay Area. While it’s not as international as my experience, it still broadens perspectives. I believe exposure to new environments benefits everyone.

Alejandro Cremades: Out of all things, how did you first get involved with the world of AI, or as it was called back then, computational technology?

Molham Aref: Back in the early ‘90s, we called it computational intelligence because AI was in a winter period and had a negative reputation. The terms “data mining” and “database mining” were more acceptable.

Molham Aref: There was also a resurgence of neural networks, which was an allowed term, but calling it AI was out of the question. In business, whether running a small or large company, and particularly with large companies deploying billions in capital for inventory, manufacturing, wireless spectrum, transportation, and labor—every decision can be make-or-break. You want to make those decisions with the best analysis possible.

Alejandro Cremades: Absolutely.

Molham Aref: Over the years, humanity has developed predictive technologies that help understand market demand and prescriptive technologies that manage logistics. Many of these technologies originated in World War II to help with army deployment and logistics—winning and losing wars depended on ammunition, food, and manpower.

Molham Aref: These technologies have evolved over time and now determine the success of businesses and organizations.

Alejandro Cremades: So, that’s how you got into it?

Molham Aref: Yes, I was deeply curious about how to teach computers to make decisions like humans. Recognizing patterns in images, understanding text—these challenges were fascinating from a scientific perspective.

Alejandro Cremades: Speaking of interesting shifts, you moved from AT&T after your studies at Georgia Tech to working on IPOs. That’s quite a different experience.

Molham Aref: I really followed my interests. My first job was with AT&T, where I took a summer internship in an advanced development group in Atlanta, working on computer vision. I was at Georgia Tech at the time and loved the work. At the end of the summer, they offered me a full-time job, and I jumped on it.

Molham Aref: After two years, I realized that commercializing our work within a large corporation was difficult. We would showcase our innovations to big organizations, and they would express interest, but AT&T lacked the commercial muscle to bring them to market. So, I left to join a startup focused on neural networks for fraud detection and supply chain management.

Molham Aref: I wanted to see the technology commercialized. Sometimes, you get lucky. The startup I joined had great technology and a fantastic management team. Although I worked in Atlanta, the company was based in San Diego, and we went public in 1995.

Molham Aref: It was a top-10 IPO, and we were featured in Time Magazine—the same issue that had Marc Andreessen on the cover, along with Netscape and Spyglass. We were part of that early internet boom, and it was an invaluable learning experience.

Alejandro Cremades: That’s incredible. Later, you were part of two IPOs—HNC Software and Retek. What patterns did you notice that contributed to their success?

Molham Aref: In both companies, we had not only great technology but also strategic go-to-market motions and moats.

Molham Aref: With HNC, we helped banks detect credit card fraud, which was a massive problem in the early ‘90s. We created a fraud consortium where each bank that became a customer contributed data, giving us access to the most extensive fraud dataset. This made our models more accurate and created a near-monopoly—at one point, we had 23 of the top 25 credit card-issuing banks as customers.

Molham Aref: Retek’s success was similar. We strategically aligned with Accenture for scalability, allowing us to dominate the retail ERP space. These combinations of technology and strong go-to-market strategies were critical to success.

Alejandro Cremades: After two successful IPOs, did you feel invincible? Was that the moment you decided to start your own company?

Molham Aref: Exactly. It gets to your head. You start thinking, “This is easy—I should just do this myself.” So, in the early 2000s, I started a company with venture funding. Unfortunately, the idea was ahead of its time, and in our world, being too early is indistinguishable from being wrong.

Molham Aref: After that failure, a former college friend approached me about launching another startup—OptiMai. We focused on intelligent applications for wireless network optimization, serving customers like AT&T, T-Mobile, and American Movil.

Molham Aref: Since I had IPO experience, I was able to bootstrap the company with just $300,000, and we later sold it to Ericsson for about $100 million. It wasn’t a Silicon Valley-style exit, but turning $300,000 into $100 million was a great outcome.

Alejandro Cremades: That’s an incredible exit. Why did you choose to bootstrap rather than raise VC funding?

Molham Aref: Initially, it was just about getting started with the money we had. But we soon realized that our customers were willing to fund development since so much was at stake for them. Why take investor money when you can grow through revenue?

Alejandro Cremades: Thank you.

Molham Aref: You know, it’s grueling and requires comfort with risk and operating in the fog of war, so to speak. That’s easier to do when you don’t have anything.

Molham Aref: But once you’ve created something of value, it’s like, “Oh, crap.” You know, you don’t want to lose it, especially if you think you can’t do it again. For some people, it feels like their one and only chance, and they almost freeze with fear.

Alejandro Cremades: Thank—

Molham Aref: —with fear. So anyway, I did not know that. Going into these things, I thought failure would put more stress on founder dynamics. But in my experience, it’s actually success—building something valuable and then being scared to lose it—that can create a lot of issues.

Alejandro Cremades: No kidding. Now, once an entrepreneur, always an entrepreneur. After you got that big fat check you were alluding to, you essentially went at it again.

Alejandro Cremades: Now, let’s talk about timing too, because I find that being an entrepreneur is also about being in the right place at the right time in history. When you got started with Relational AI, it was a little before this whole absolute craziness around AI took off.

Alejandro Cremades: So why did you decide that Relational AI was the next rodeo for you? How did everything come together?

Molham Aref: Yeah, well, first, I appreciate you saying that we weren’t just latecomers to this AI bandwagon. In 2017, we picked the name Relational AI. At that time, deep learning and machine learning were already prevalent, but we specifically chose “Relational AI” because we believed in the need for AI for relational data—where most enterprises store their data.

Molham Aref: One way to think about AI is through the lens of consumer AI versus enterprise AI. In the enterprise world, the standards are much higher because the decisions made can directly impact people—customers, employees, and the business itself. Mistakes can lead to layoffs or legal consequences, so enterprise AI has to operate with much more safety, rigor, and attention to compliance.

Molham Aref: The motivation for Relational AI came from my career of building companies that created intelligent applications across industries like retail, banking, and telecom. These applications required combining multiple techniques—predictive analytics, prescriptive analytics, graph analytics, rule-based reasoning, and more. Typically, you’d need to integrate five or six different technology stacks to support such applications.

Molham Aref: Building an intelligent application remains really difficult when you’re stitching together multiple technologies. So much of the engineering effort goes into tying these pieces together rather than into the core value of the application itself. In every applications company I worked with, we ended up rolling our own tooling and infrastructure to simplify the process. That made me realize the world needed a solution like this—one that wasn’t limited to just one company at a time.

Molham Aref: I also knew this wasn’t a business I could bootstrap. Building infrastructure takes time—sometimes three, four, or even five years. After selling my last company, I moved to New York for a couple of years. Then, as the deep learning wave emerged, I thought it would be a shame to end my career without having real Silicon Valley exposure.

Molham Aref: So, I moved my family to Silicon Valley, settled in Woodside near Stanford, and started learning how the community operates. One thing I truly appreciate about Silicon Valley is that the bigger the idea, the more interesting people find it. In contrast, in Atlanta, the bigger the idea, the more people question, “Who do you think you are, dreaming that big?” Silicon Valley is built around supporting entrepreneurs—providing access to talent, funding, and expertise.

Molham Aref: Very randomly, I ended up meeting a lot of helpful people, including Bob Muglia, who had just left Snowflake after helping build it into the company it is today. We met almost by chance through a social network. At Snowflake, Bob had been thinking about how to bring AI to Snowflake. When he realized that we were focused on AI for relational systems—embedding AI in relational databases—he got very excited. That was a major breakthrough for us.

Molham Aref: So anyway, the idea behind Relational AI was simple: building intelligent applications is hard, and we wanted to make it easy. That required new infrastructure, and building that kind of infrastructure is not easy. So, I followed the old advice: “Go West, young man—or old man—and see if you can get help on the journey.” Moving was second nature to me, and it paid off by giving me access to an invaluable network.

Alejandro Cremades: So with Relational AI, how do you guys make money? What’s the business model?

Molham Aref: Our model is similar to data cloud platforms like Snowflake. Having a clever go-to-market strategy that scales by leveraging someone else’s investment in go-to-market has been helpful for me in the past. This time, we aligned our success with Snowflake and their customers.

Molham Aref: We go to market as a co-processor—Snowflake calls it a native app—that plugs into Snowflake. Customers can easily turn it on, and it runs inside Snowflake’s security perimeter, maintaining governance with no need to move data around. This brings AI capabilities that Snowflake doesn’t natively offer.

Molham Aref: Snowflake already has Gen AI and Document AI capabilities, but enterprise AI requires much more—what some call composite AI, compound AI, neuro-symbolic AI, or decision intelligence. Businesses need the full AI stack, not just generative AI and vector databases. Our integration provides that without forcing customers to extract their data into separate point solutions. This makes Snowflake customers happy, strengthens Snowflake’s positioning as a platform, and allows us to tap into their $1.2 billion-per-year go-to-market machine.

Molham Aref: With over 11,000 customers, Snowflake provides a massive market for us. Every one of those customers benefits from our solution compared to existing alternatives.

Alejandro Cremades: That’s amazing. And for listeners interested in Snowflake, we actually had the current CEO of Snowflake on the podcast, where he talked about their $100 billion business plan while at Google. So, great guy.

Alejandro Cremades: One thing that comes to mind—you raised $122 million. Why did you decide to raise money this time versus bootstrapping?

Molham Aref: Because this is infrastructure, not an app that can immediately tie to incremental business value. Enterprise infrastructure takes time—this is fundamental technology combining AI, databases, programming languages, and more. The depth of innovation required meant bootstrapping wasn’t an option.

Molham Aref: I did fund the seed round with $7.5 million, which got us going for a few years, but we eventually needed to raise significant capital.

Alejandro Cremades: So when you first sought outside investors for your Series A and beyond, why did you choose those specific investors?

Molham Aref: That’s a great question. Our Series A was heavily oversubscribed. When I first moved to Silicon Valley, I didn’t fully understand the funding model. I had a few early conversations that made me realize I wasn’t yet speaking the language of the Valley.

Molham Aref: Our idea was big, but it required first-principles thinking, and before the rise of Gen AI, it wasn’t easy to explain. Bob’s involvement changed everything. He had just played a key role in building Snowflake, the largest software IPO at the time. His endorsement meant there was a long line of interested investors.

Molham Aref: Ultimately, we raised $40 million, with $22 million coming from insiders—Bob, myself, other board members, and colleagues from past companies. We had to say no to many VCs. Bob and I had both seen the damage caused by having the wrong investors. We prioritized partners whose values aligned with ours.

Molham Aref: Soma from Madrona stood out as someone who would do the right thing, so we were delighted to have Madrona lead the round. We also brought in Lee Fixel from Addition and Menlo Ventures. Saying no to some investors—especially friends—was difficult, but we had to optimize for the right long-term partners.

Molham Aref: And then the Series A—so Series B happened very quickly thereafter, within six months, and it was unsolicited. Tiger Global, I think, had the vision to understand what we were doing and recognized that Soma and Bob were involved. That deal happened in the typical Tiger Global way at the time: a call, a term sheet, and closing within 30 days. It was an interesting and fun experience for me, having lived outside of Silicon Valley and never experienced something like that before.

Alejandro Cremades: So, obviously, those investors are betting on a vision—the future that you’re building with Relational AI. If you were to go to sleep tonight, Molham, and wake up in a world where that vision is fully realized, what does that world look like?

Molham Aref: Yeah, I think in that world, building intelligence into the systems we use to make decisions becomes increasingly cheaper and more accessible. We’ve essentially made it possible for people to do that.

Molham Aref: The quality of decision-making, not just for businesses but for all kinds of organizations, improves significantly.

Alejandro Cremades: Thank you.

Molham Aref: Right now, it’s just too difficult to amplify, curate, or assist decision-makers across the board. You see it even at the level of governments—questionable decision-making happens because there’s no real ability to predict the consequences of those decisions.

Molham Aref: If every decision could be made with a reliable prediction of its consequences and timeline, decision-making would improve. And I believe the world would be better because of that. You wouldn’t have uninformed individuals—or people who could have made better decisions—making uninformed, poor choices that lead to the failure of companies, governments, and societies.

Alejandro Cremades: Since we’re talking about the future, I want to take a moment to reflect on the past. If I were to put you in a time machine and take you back to that moment when you were about to turn the page with Retek—when you were feeling almost superhuman and ready to start your own company—what advice would you give your younger self before launching the business?

Molham Aref: Yeah, I’d say pick your partners well and truly understand the sacrifices involved.
One thing I’ve learned is the power of simply showing up every day—putting one foot in front of the other and not giving up. It may sound cliché, but you really can’t understand it until you’ve lived it.
There were moments when I had no idea how we were going to make payroll. But just getting up and pushing forward eventually led to the right outcome. It’s incredibly difficult, and it’s not for everyone.

Molham Aref: There is a cost—you pay a price. There are people in my life I wish I had spent more time with. Even when I’m physically present with my friends and family, sometimes I’m not really there, if you know what I mean.

Molham Aref: There’s a big price to pay, but for me, this is my passion. This is what I love—the combination of technology and the entrepreneurial journey. So, no regrets, even though the cost is high.

Alejandro Cremades: I hear you. Well, Molham, it has been an absolute honor. Thank you so much for being on The Dealmakers Show. For those listening who would love to reach out and say hi, what’s the best way for them to do so?

Molham Aref: Yeah, you can reach me at my email—first name dot last name at Relational AI. I’m also on LinkedIn, and I have a Twitter account where you can DM me. So LinkedIn, email, and Twitter—or X.

Alejandro Cremades: Amazing. Well, Molham, thank you so much for being on The Dealmakers Show today. It’s an honor to have you with us.

Molham Aref: Thank you, Alejandro. I really, really appreciate it.

*****

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