Omar Alolayan, Chief of AI and co-founder of Almutanabi

Individual investors in Saudi Arabia can’t watch the market all day, and the recommendations they act on rarely account for their own risk tolerance. Omar Alolayan co-founded Almutanabi to fix that: algorithms that read the market in real time and size trades to each investor's risk, with client money staying in its own brokerage account. After a PhD at MIT and seven years of R&D, the CMA-licensed platform has ranked sixth of 121 Saudi equity funds and is now expanding to institutional clients and Gulf and Arab markets.

Omar Alolayan, Chief of AI and co-founder of Almutanabi: Each week, My Morning Routine looks at how a successful member of the community starts their day — and then throws in a couple of random business questions just for fun. Speaking to us this week is Omar Alolayan (LinkedIn), Chief of AI and co-founder of Almutanabi. Edited excerpts from our conversation:

Enterprise: How did your career begin, and what problem did you set out to solve for individual investors in Saudi Arabia?

Omar Alolayan (OA): I began my career in engineering and scientific research, graduating from King Fahd University of Petroleum and Minerals before joining Aramco's research center. I later earned a PhD from MIT, where I focused on AI algorithms for engineering and scientific problems. During my PhD, I saw AI's ability to identify complex patterns beyond human capacity. I reached out to my co-founder, Mohamed Al Salloum (LinkedIn), who had experience in automated, high-speed trading based on technical signals. We launched an R&D project that showed us AI, developed with the right scientific methodology, could significantly outperform traditional algorithms.

We identified four key challenges for individual investors: Time, since most can’t monitor markets continuously; unreliable recommendations that may not reflect an investor's risk tolerance; emotion, which can lead investors to hold losing stocks or make poor selling decisions; and traditional investment funds, which often deliver inconsistent performance at relatively high fees.

Almutanabi was built to address these challenges. It's a Shariah-compliant, CMA-licensed platform that analyzes market data in real time and recommends opportunities, portfolio allocations, and liquidity levels based on market conditions and each investor's risk tolerance. Client funds stay in their own brokerage accounts rather than being held by us.

E: How did the idea evolve into the product it is today?

OA: The journey took seven years of R&D. We developed and tested multiple algorithms in live markets, where real-world experience exposed issues that theoretical testing did not. Eventually we developed algorithms capable of managing portfolios with performance competitive with leading Saudi equity funds, but at a much lower cost. We then realized the technology could scale across financial markets and decided to turn it into a product. From the start, our goal was also to build advanced scientific capabilities that could position Saudi Arabia as a leader in the field.

A key early decision was to serve both individuals and institutions. Most companies focus on institutions, but we believed we could address the real, everyday challenges individual investors face, so we designed our products for both.

E: What were the biggest challenges in building Almutanabi?

OA: We faced challenges on several levels. On the technical side, the hardware available to us wasn't sufficient to train AI models on the bns of data points we work with. At the market level, the Saudi market has seen geopolitical conditions over the past three years that affected liquidity and reduced both individuals' and institutions' appetite to invest.

Convincing investors to try the platform was easier than we expected. Investors today are eager to use the latest AI to improve their portfolio performance.

E: How did you deal with these challenges?

OA: We overcame the hardware limitations through several engineering solutions that let us make the most of the resources we had. As for market conditions, we see them as temporary, and we've recently started to see the Saudi market improve.

The most important shift in our journey happened within the R&D phase itself. We didn't arrive at our current algorithms on the first attempt. We went through multiple generations of algorithms, testing each in the real market. The mistakes those generations made are what led us to the version we run today.

E: How do Almutanabi's algorithms analyze stocks and generate buy or sell recommendations, and what data do they use?

OA: Almutanabi's algorithms build a dedicated model for every company listed on the market. Each model is trained on mns of historical data points for that stock so it can learn to spot opportunities at the right time. During trading hours, it reads data in real time, presents investors with the available opportunities, and recommends how to allocate capital among them based on the level of risk the client has set.

E: How do you measure the performance of your recommendations, what are AI's limits in predicting markets, and how do you handle the calls that go wrong?

OA: We measure performance in two stages. Before issuing any signal, we test each stock model on its historical data and don't approve it to issue buy signals until it shows a very high level of accuracy. After issuance, we record every recommendation our models generate and review its performance periodically; we also run real portfolios in the market and publish their performance figures on our website.

On the limits of AI, we need to be candid: no algorithm can predict every market condition, however accurate it is. It may issue a recommendation on a good stock expected to reach its target, only for the whole market to fall on a sudden geopolitical event, and the recommendation fails. The success rate of trading algorithms generally ranges between 50% and 60%. That figure may look modest, but profitability in the markets doesn't depend on the hit rate alone. It depends on the gap between the size of gains on winning trades and losses on losing ones. That's where our advantage lies: we designed our models to control losses when they're wrong. The goal is for investors to earn positive returns over the long term, and to hold up better than the market during downturns.

E: How do you build trust with investors who are cautious about relying on AI for investment decisions?

OA: Through numbers first. Our portfolios managed by Almutanabi have been operating in the Saudi market since March 2025, and their performance during this period ranked sixth out of 121 funds investing in Saudi equities, placing them among the top 5%.

We also don't stop at recommendations. We give investors the full picture: the latest news on the stock and an assessment of whether that news is positive or negative, so they can make informed decisions rather than simply follow a recommendation. The platform adapts to each investor's convictions, too: users can limit their investments to companies that comply with a particular authority's Shariah standards (the Al-Asimi lists, for example), companies that haven't recorded recent losses, one or more sectors of their choice, or companies whose price-to-earnings ratio falls within a range they set.

Finally, we are a recognized entity licensed by the Capital Market Authority (CMA), which is precisely what investors lack in anonymous recommendation groups. The client's money doesn't pass through us in the first place; it stays in their portfolio with their broker, so they don't need to entrust us with their money to benefit from the platform.

E: How large is the market your platform can address, and what will drive revenue growth as you expand from individuals to institutions?

OA: We serve two segments: individuals, through platform subscriptions, and institutions, through customized algorithms tailored to their investment policies and management styles. We see significant potential in both. The Kingdom has more than 7 mn investors, according to the CMA, while algorithmic trading still accounts for about a quarter of trading value, compared with 60-80% in the US. We've also launched Almutanabi Global to offer Shariah-compliant algorithms to US investors, where Saudi investors' US equity trading exceeded SAR 250 bn in a single quarter.

E: Looking ahead, where do you want Almutanabi to be in the coming years?

OA: Our primary goal is to build Saudi technology and localize advanced scientific capabilities in AI research and its applications, helping the Kingdom become a leader in the field. We aim to become the Middle East's leading company in AI research and financial-market applications, operating in line with Islamic Shariah principles. We plan to expand into Gulf and Arab markets next year. Our ambition is regional, but our roots will remain Saudi.

E: What do your mornings look like?

OA: I start my day with Fajr prayer, and I cannot think of a better way to begin the day. After that, I get ready for work and leave early, at 6 AM.

E: Who has had the greatest influence on your career?

OA: Jim Simons, the mathematician who founded Renaissance Technologies and one of the great legends of algorithmic trading, whose fund delivered exceptional returns. An idea he expressed in 1996 inspired me — that price movements are not random, but close enough to random to make extracting any edge from them extremely difficult. That was one of the reasons I entered this field despite its difficulty.