Getting to the Root of the Problem: Anis Harb, Co-Founder and CEO, Algebra

Anis Harb has a rather interesting professional trajectory. It starts traditionally in banking with J.P. Morgan, then ventures into courageous, high-impact, scale-focused roles at tech startups, specifically launching and leading Deliveroo’s Middle East business for a decade (which, to be honest, has stopped being considered the unique career pivot it used to be). But then he adds his own plot twist.

As if driven by an urge to solve the inefficiencies he had run away from in banking, only to eventually face them in the tech sector as well, he decides that, instead of looking for another career niche where he might not encounter it again, he would tackle the problem itself.

“Year after year, I saw the same pattern. Every time volume grew, the answer was more people and more process. That worked until keeping up became the job and nobody had time to build forward,” Harb explains. “Data arrived from different teams and markets at different times, and by the time we pieced it together, the moment to act had often passed. The business had the intelligence it needed. Getting it to the right person in time was the hard part, and that gap is where growth opportunities get lost.”

That is where Algebra, a UAE-based artificial intelligence (AI) transformation company, comes into the picture. The company develops and operates customized AI-powered workflows for mid-market businesses across the GCC. While Algebra is sector-agnostic, serving clients across financial services, manufacturing, and distribution, it maintains a deliberate focus on repeatable workflow models, avoiding one-off custom solutions that can become difficult to manage at scale.

Harb continues, “AI can close that gap by running the coordination layer and making the operation readable in real time. That makes a business more efficient, and it also helps it grow, because the team can respond faster, take on more volume and act on opportunities while they are still live.”

Algebra AI officially launched in June 2026, backed by US$7 million in funding from a group of regional and international investors, including US-based Infinity Constellation, UAE-based BECO Capital, Jordan-based Silicon Badia, and Saudi Arabia-based Waseel Investments. “I could also see who needed it most,” Harb adds. “The GCC has more than 30,000 medium-sized companies, many of them too large for off-the-shelf tools and too small for enterprise programs. That became Algebra.”

Now, let’s look more closely at the problem and Algebra’s solution. Harb explains that operational growth and organizational complexity tend to become obstacles when hiring additional staff buys time but little else, when the same errors occur so frequently that correcting them becomes part of the job, and when keeping up with daily operations leaves little room to focus on future growth. “I saw this firsthand when Deliveroo expanded into grocery, which brought a challenge common across grocery delivery,” he says. “Each grocer carried 10,000 to 20,000 products, and their product data arrived in many formats, from Excel sheets and PDFs to photos of supplier catalogs. Bringing each new grocer live took weeks of careful work, and keeping stock accurate as it changed every day took ongoing effort from our operations and support teams.”

Hiring more people was the natural response, and it worked, but the experience also made Harb realize how much of that repetitive work could be handled by well-designed systems. “I hear the same pattern in conversations today. One contracting COO told me his pipeline is capped by how many tenders his team can price by hand,” he says. “That is a revenue problem as much as an efficiency one. Once that constraint lifts, the question moves from ‘how do we keep up?’ to ‘how do we grow?’”

So, what exactly is Algebra’s solution? Harb explains that businesses typically have their data scattered across enterprise resource planning (ERP) systems, customer relationship management (CRM) platforms, emails, spreadsheets, documents, and WhatsApp conversations. Employees spend considerable time transferring information between these systems, verifying procedures, and securing approvals, often resulting in critical information reaching decision-makers too late for timely action.

“General-purpose AI can answer questions. Closing the gap takes a system that knows how your business runs. Every company has its own logic: which customers get priority stock, who signs off on a discount above a certain level, which supplier confirms orders on WhatsApp. That logic is what turns data into the right next step.

“So we start by mapping the operation as it works today, including the tools, handoffs, approvals and exceptions. Then we design a tailored system around it, connected to the systems the business already uses. The system can take the next step, such as preparing a quote using the client’s own pricing rules, routing an approval, updating a record or flagging an exception. The team makes the decisions that need their judgment, with the information already in front of them.”

The benefits, Harb explains, extend beyond operational efficiency. By automating routine processes, businesses can reduce costs and accelerate workflows, while enabling employees to respond to customers faster, prepare more quotations, and devote greater attention to revenue-generating opportunities.

Medium-sized businesses often fall between standardized software solutions that require in-house management and complex consulting programs designed for large enterprises. “What makes our approach different is that we stay with the system after launch,” Harb says. “AI systems keep changing: models evolve, business rules shift, new exceptions appear and integrations change around them. To keep performing, a system needs ongoing care. At Algebra, the same team designs the system, connects it to the operation, runs it in production and keeps improving it as the business grows. We stay accountable for the system doing what it’s built to do.

“That makes the managed service part of the product. Clients gain an operating capability that becomes more valuable the longer it runs, supporting both efficiency and growth as the business takes on more.”

Harb explains that the discovery phase of the problem takes one to two weeks, followed by six to twelve weeks of system design, development, testing, and integration, with the goal of going live within approximately 90 days. Clients work with their existing teams but must provide an executive sponsor, access to relevant systems and data, and a process owner to define business rules and manage exceptions. 

The Algebra commercial model consists of a one-time implementation fee followed by a fixed monthly fee for operating and improving the system. However, Harb emphasizes that the most important investment on the client’s side is internal alignment on responsibilities, implementation, and measurable outcomes in both efficiency and revenue growth.

For SMEs considering a do-it-yourself approach, Harb highlights several common mistakes in AI adoption. The first is treating AI as a software purchase rather than an operational capability, without identifying the specific business problem it should solve. Another is automating processes before properly mapping their workflows, rules, and exceptions. He also warns against overlooking how AI and employees should work together, with technology handling repetitive tasks while people retain responsibility for decisions requiring judgment. Finally, businesses often treat implementation as the finish line, failing to recognize that AI systems require continuous monitoring, maintenance, and improvement to remain effective. “My advice is to start with one clearly defined area, agree on measurable outcomes, build human oversight into the design and make someone responsible for the result. Then expand once the first system is working reliably,” he says. “The companies that benefit most from AI will not be the ones that run the most pilots. They will be the ones that turn AI into dependable operating infrastructure.”

The partnerships with Infinity Constellation, BECO Capital, Silicon Badia, and Waseel Investments developed organically, Harb says, with each investor bringing distinct strengths. Yet, drawing on his experience as an operator, Harb acknowledges that one of the biggest challenges lies in balancing investors’ long-term ambitions with the daily realities of building a business. “As an operator, you’re constantly making decisions about customers, people and execution, and things don’t always move in a straight line. Alignment on the destination is important, and so is the flexibility to adjust how you get there,” he says. 

“Clarity around decision-making matters just as much. Having experienced investors as co-founders is a tremendous advantage, and we’ve been deliberate from the beginning about separating strategic oversight from operating decisions. That lets us benefit from their experience while keeping the speed and autonomy needed to build. As the business grows, those dynamics will evolve, so we keep communication open and revisit expectations regularly.”

Looking ahead, Harb’s ambitions for Algebra extend well beyond the GCC. “Over the next three to five years, our ambition is to build a global leader in AI-enabled business services, starting in the GCC,” Harb says. “We’re focused on developing solutions that can be deployed faster and more efficiently across customers, while continuing to deepen our expertise in the industries we serve.”

‘TREP TALK: Algebra Co-Founder Anis Harb Shares Three Dos for GCC Entrepreneurs

First, build systems earlier than you think you need them. At Deliveroo, much of our operating knowledge lived with talented people making fast decisions. That works when you’re small, and it becomes a constraint as you scale. The earlier you turn that knowledge into repeatable processes and systems, the easier growth becomes.

Second, treat each GCC market differently. The GCC is often discussed as one market, but regulation, consumer behavior and operating dynamics vary significantly. What works in Dubai won’t necessarily work in Riyadh or Kuwait City, so localize your approach for each market.

Third, embrace new technology early. AI is changing how businesses can operate and scale. Founders have an opportunity to build companies differently from day one, with technology doing work that historically required significant headcount. I’d encourage them to experiment early and think about how they’d design their business if they were starting from scratch today.

‘TREP TALK: Algebra Co-Founder Anis Harb Shares Three Don’ts for GCC Entrepreneurs

The first is hiring your way out of operational problems. When a business grows, adding people often feels like the quickest solution. If the underlying process is inefficient, you’re simply scaling that inefficiency. Fix the process first, then hire where people can create the most value. The second is expanding before your foundations are ready. Growth can hide a lot of operational weaknesses. Processes that work at a small scale can break quickly when you add new markets, products or customers. Make sure the business can support the next stage of growth before accelerating.

The third is letting your best people get buried in process work. One of the biggest hidden costs in a growing business is talented people spending their time on repetitive tasks: the partnerships nobody pursued, the customer opportunities nobody followed up on, and the analysis nobody had time to do. That’s growth you lose without ever seeing it on a dashboard.