Gebeya’s Remarkable Growth in AI Solutions
Gebeya’s AI product suite is rapidly gaining traction, amassing 85,000 users just four months post-launch. Among its offerings, Gebeya Dala—often referred to simply as Dala—has emerged as the standout product.
Dala empowers users to develop applications using natural language, eliminating the need for coding proficiency. While its inspiration comes from Lovable, a $6.6 billion AI startup, Dala aims to serve a unique purpose within the African context.
This broader mission extends beyond the currently popular trend of “vibecoding.” According to Amadou Daffe, founder of Gebeya, there’s limited interest in this trend among many Africans at this time. He shares that younger voices have highlighted the potential of integrating comic books into app development, underscoring a need for creativity beyond traditional coding platforms.
With a decade of product development experience, Daffe’s journey culminated in the creation of Dala. Since founding Gebeya in 2016, he has seen the company transform through various iterations.
The initial vision for Gebeya (known as Gebeya 1.0) was to serve as an educational institution, training high-level software engineers while providing outsourcing opportunities. This model was analogous to Andela’s approach, focusing on nurturing talent throughout East Africa. Over time, the company evolved into a pan-African talent marketplace before adjusting into a Software as a Service (SaaS) platform that empowers other entrepreneurs to establish their own talent marketplaces.
In its latest iteration, Gebeya has turned its attention to AI products, with Daffe asserting the critical importance of remaining agile in the tech landscape. The idea for Dala was solidified after observing non-technical staff successfully create a working product at Lovable. However, Dala aims to go well beyond merely being another vibecoding platform, positioning itself as a comprehensive solution for app development.
Funding Landscape and Gebeya’s Unique Position
When discussing startup ecosystems in Africa, Ethiopia is often overshadowed by countries like Egypt, South Africa, Kenya, and Nigeria. Yet, Daffe has successfully secured funding from notable venture capitalists, including Partec Africa and Orange Digital Ventures, due in large part to his company’s pan-African structure.
Daffe emphasizes that starting a company solely in Ethiopia would have significantly hampered fundraising efforts. With a focus on developing talent, he ranks his engineering team among the finest globally. This commitment to nurturing talent also aligns with other African tech innovators, such as Mark Essien, who has harnessed internship programs to fuel his own ventures.
Despite being relatively new, Dala has attracted thousands of users, with a remarkable 8% converting into paying customers—significantly higher than the typical industry standard of around 3%.
The high conversion rate can be attributed to Dala’s flexibility in payment options, allowing users to pay in local currencies and utilizing popular methods like mobile money. Nonetheless, Daffe acknowledges that Dala’s growth is modest compared to larger global AI platforms. He notes that Lovable boasted 300,000 active users within its first two months and reached 8 million within a year, a pace fueled by substantial capital investment.
Although Gebeya has previously raised funds for other initiatives, it has not yet secured investment aimed specifically at its AI ambitions. However, Daffe believes that the unique advantages his company holds in Africa—such as being mobile-first and supporting multiple local languages—position Dala to penetrate markets that larger companies may overlook.
Strategic Development of AI Models for the African Market
Dala employs existing AI models from prominent tech labs, but Gebeya enhances this through an innovative component Daffe refers to as an orchestrator. This system intelligently directs user queries to the most suitable underlying AI model, optimizing performance for diverse applications.
“Gemini or OpenAI might not always be the best solutions. The orchestrator determines the most effective choice,” Daffe explains. Currently, this orchestrator works with Dala’s existing architecture, but Daffe envisions an evolution towards developing proprietary, context-specific language models.
Instead of competing with larger, general-purpose models, Gebeya aims to cultivate focused solutions tailored to regional user behavior. Daffe aspires to create contextual or small-scale language models that address specific domains efficiently.
This vision is bolstered by Gebeya’s partnership with Cassava Technologies, which operates data centers and fiber infrastructure across Africa. As Gebeya prepares to gather more user data for training its models, the need for GPU-enabled infrastructure becomes essential—especially where local data residency regulations apply.
“If we launch a language model or a specialized agent in a specific region, we’ll ensure it operates within that country’s infrastructure,” Daffe states, highlighting the importance of local resources. Collaboration with Cassava allows Gebeya to build and deploy context-specific models in Africa rather than relying solely on international cloud services.
Navigating Challenges in AI Development on the Continent
Dala’s reliance on external AI models, like those from OpenAI and Google, introduces ongoing challenges, including managing inaccuracies, API fluctuations, and cost management per prompt. Daffe acknowledges that these technical obstacles can hinder progress and notes the steep learning curve for his team.
Beyond technical difficulties, scaling the platform poses significant challenges. Although Dala has shown rapid growth, Daffe understands that speed is vital in the competitive AI landscape. This urgency extends beyond product quality; it encompasses distribution strategies, capital efficiency, and effectively communicating AI’s potential to diverse African audiences.
Rather than viewing these challenges as threats, Daffe sees them as pivotal growth opportunities for the continent. He believes Africa’s youthful, mobile-first demographic represents a chance to innovate beyond mere coding, embracing a broader spectrum of digital engagement—from music and gaming to fully realized digital products.
