UAE-Based Algebra AI Raises US$7 Million To Close The GCC Mid-Market's AI Deployment Gap

UAE-based artificial intelligence (AI) transformation company Algebra AI has officially launched after securing US$7 million in funding from US-based venture builder and technology investment platform Infinity Constellation, UAE-based venture capital (VC) firm BECO Capital, global VC firm Silicon Badia, and Saudi Arabia-based investment firm Waseel Investments. 

Founded in Dubai in 2026 by Anis Harb alongside investors from BECO Capital, Silicon Badia, Infinity Constellation, and Waseel Investments, the company develops and operates customized AI-powered workflows for mid-market businesses across the GCC. Algebra AI was established to address a gap in the AI market, where mid-sized businesses are often too large for standard AI tools, but may not have the resources required to implement enterprise-level solutions. With Harb as CEO, the company currently serves clients in the financial services, food and beverage, distribution, and manufacturing sectors. 

In an interview with Inc. Arabia, Harb, who previously spent a decade at Deliveroo scaling the global delivery platform’s operations across the Middle East, said that Algebra AI was founded to serve a business segment he had long seen being underserved. "We are built for mid-market businesses in the GCC—too large for off-the-shelf AI tools, too small to justify enterprise-grade complexity,” Harb said. “We embed with each client, rebuild their core workflows as AI-native systems, and run them as an ongoing managed service. The same team that builds the system continues to operate and improve it. One accountable partner, no handover.” 

Underlying this approach was a pattern Harb observed repeatedly inside growing organizations. "One problem kept surfacing regardless of market or function: the people closest to the operation were spending most of their time on work that shouldn't require them,” he explained. “Chasing a number from another team. Waiting on an update that should have been automatic. Reconciling two versions of the same report. The judgment was there. The time wasn't. What struck me was that this wasn't a people problem—the teams were good. It was a structural one. The connective tissue between functions had never been built properly, so people were doing it manually, every day, at the cost of everything else. That's the problem Algebra AI was built to solve." 

For Harb, the persistence of such operational bottlenecks reflects a broader shortcoming in today's AI market. "Most AI solutions fall into one of two camps: tools simple enough for anyone to use, and platforms that assume you have an internal tech team to implement and maintain them,” Harb pointed out. “Mid-market businesses fall between both. They have real operational complexity - multiple systems, approval logic, compliance requirements, teams with different working habits. And they don't have the technical resources or clean data infrastructure that either type of solution assumes.” 

According to Harb, the underlying issue is not the availability of AI tools, but how businesses approach the problem they are trying to solve. "The deeper misunderstanding is that this is a technology problem,” he said. “It is not. It is a design problem. The tools exist. What's missing is the work of mapping them to how a business actually operates—not how it looks on paper. I see this play out regularly. A pilot runs cleanly in a controlled environment, then hits the real operation: a supplier who sends updates by WhatsApp, an approval step that was never documented, a legacy system that talks to nothing else. The tool doesn't collapse—it just gets quietly worked around, until the team drifts back to the spreadsheet, and the AI investment becomes a line item nobody questions and nobody owns. That is how AI is playing out across much of the real economy right now. Deployment is happening. Transformation is not. The answer isn't a better tool—it's a different implementation model, one built around how the business actually runs, where accountability doesn't end at go-live." 

That diagnosis also shaped how Algebra AI's investors approached the company from the outset. "We did not approach this as a conventional funding round,” Abdulaziz Shikh Al Sagha, Managing Partner at BECO Capital, told Inc. Arabia. “The syndicate co-founded and incubated Algebra AI from inception, which reflects how clearly we all see the structural gap it is addressing. Tens of thousands of mid-market businesses across the Gulf are generating significant economic output with no viable path to AI adoption. Off-the-shelf tools are built for businesses far simpler than these, and enterprise solutions assume dedicated technology teams and clean data infrastructure that most mid-market operators do not have.” 

“What resonates equally strongly is the model,” Al Sagha continued. “What we are seeing here is the rise of service-as-a-software, the shift from traditional software-as-a-service to intelligent systems that deliver complex professional services autonomously and at scale. Algebra AI is that model, built for the GCC mid-market, by a team with the operational depth to execute it here. The company designs systems around how a client's business actually operates, builds them, and stays accountable for running and refining them over time. There is no handover at go-live. And underpinning all of it is the team Anis has built around him. That combination of market, model and team is what brought the syndicate together. None of this would have come together without Namek T. Zu'bi at Silicon Badia, who likewise shared our views on service-as-a-software, and brought the right people to the table." 

For Harb, the conviction shared by Algebra AI's investors also reflects a broader opportunity emerging across the GCC. "The GCC has a structural advantage that doesn't get talked about enough,” he said. “Many mid-market businesses here didn't grow up on legacy infrastructure the way their counterparts in Europe or the US did. They're not untangling decades of technical debt, outdated enterprise resource planning (ERP) configurations, or processes that were locked in before modern tooling existed. That makes the path to AI-native operations genuinely shorter here—not as a talking point, but in practice. After all, a business that built its operations in the last ten years has far less to undo.” 

Harb also predicted that the shift to AI-native operations would reshape how businesses grow in the region and beyond. "The most fundamental shift over the next three to five years will be the relationship between headcount and output,” he predicted. “The assumption that growth requires a proportional increase in people is one that AI will break. But the more important change is what that frees up. The most valuable people in any mid-market business—the commercial director, the head of operations, the chief financial officer—are spending a significant portion of their week on work that has nothing to do with why they were hired. Chasing updates, consolidating information, pulling numbers that should already exist in one place. AI can run that layer. When it does, those people get back to the work that actually moves the business." 

In Harb's view, the companies embracing this shift the earliest would gain a lasting competitive advantage. “The gap between early movers and everyone else is still open in the MENA,” he noted. “|But it won't stay that way. Most businesses see the productivity dip that comes before the gains—as processes get redesigned and teams adapt—and they pull back. The ones that push through are already on the other side. What will surprise people most is how quickly the distance between those two groups becomes visible, and how hard it becomes to close from behind." 

Beyond his outlook for the market, Harb also reflected on what building Algebra AI has taught him. "The lesson I keep coming back to is that the organizational chart is never how work actually moves,” he said. “The real operational logic of any business lives in the heads of good people making fast judgment calls. That is a feature when you're small. It becomes a constraint as you grow—because every time you solve a growth problem, coordination overhead quietly absorbs whatever capacity you just created. Your best people end up spending more time reconciling, chasing, and escalating than actually deciding. The work is critical. It just doesn't require their judgment—it requires their time. What I wish I'd understood earlier is that this is a structural problem, not a people problem. The connective tissue between functions—the coordination, the information routing, the follow-up loops—was always going to be manual until someone built a system to run it. That's what Algebra AI was built to solve." 

That experience has also informed the advice Harb now offers entrepreneurs entering the AI space. "My advice to founders: start with the operation, not the technology,” he said. “Find a specific, painful, well-understood workflow, and go deep on it before you go wide. The temptation in this space is to chase every use case—the technology makes so many things feel possible that breadth starts to look like a strategy. It isn't. The founders who build lasting value will be the ones who understood one workflow archetype better than anyone else, delivered it repeatably, and expanded from a position of depth. The technology is ready. The harder work is the translation—understanding how a business actually operates, not how it's supposed to, and building for that reality. That's where the value is. It's also where most of the market still isn't looking."