When Ajim Capital was founded, one question drove the earliest conversations: why do so many smart people look at Africa and see risk, when the playbook for what's going to work is already written?
The answer was a catalogue. Over several years, we built a proprietary database of 300+ business models that succeeded in emerging markets facing conditions similar to Africa's — incomplete infrastructure, mobile-first consumer behaviour, large informal economies, young demographics, and rapidly digitising commerce. India. Indonesia. Brazil. Mexico. Vietnam.
We studied what worked, what the timing looked like, what the enabling conditions were, and how long it took. Then we mapped those conditions to where Africa is today.
The sceptical view of market analogies is that they oversimplify. Africa is not India. Nigeria is not Indonesia. This is true. But it misses the point.
We're not looking for identical markets. We're looking for structural parallels: the moment when mobile penetration crosses a threshold, when digital identity infrastructure matures enough for financial services to scale, when SME formalisation reaches the point where vertical SaaS becomes viable.
These structural moments are predictable in hindsight. The insight is learning to see them in advance — and building a database is one systematic way to do that.
"We don't invest in Africa because we hope it works. We invest because we've studied every market that faced the same conditions, and we know what happens next."
India's Darwinbox, Indonesia's Mekari, Brazil's Gupy — all built payroll and HR infrastructure for businesses that were managing people on spreadsheets. Africa's SME workforce is at exactly that inflection point. Eazipay is the portfolio company executing this model in Nigeria.
Wise scaled by solving the same problem in Europe. Remitly built a business on US-to-Philippines transfers. The Africa version is more complex — more corridors, more currencies, more regulatory environments — but the demand signal is identical, and the total addressable market is larger. Raenest, LemFi, Moneco, and Payday are all executing variants of this model.
WeChat commerce in China showed that when a messaging platform becomes the operating system of daily life, commerce follows. WhatsApp has done the same in Africa — over 90% smartphone penetration in urban Nigeria, Kenya, and South Africa — and the B2B enablement layer is still being built. Chpter is building exactly this.
Market analogies are a starting point, not a conclusion. The database tells us what is likely to work. It doesn't tell us which founder is going to execute it, or whether the enabling conditions have arrived in a specific market.
That's the other half of what we do. Deep on-the-ground networks — across Nigeria, Kenya, Ghana, and Francophone Africa — that give us signal on founder quality and market readiness before the data is obvious.
The 300-model database is the filter. The networks are the source. Together, they produce a very different kind of conviction than reading a pitch deck.
If you're building something in Africa that has already worked somewhere else in the world, we want to hear from you. Not because we think copy-paste works — it doesn't. But because we've spent years studying exactly how models adapt, where the local nuance creates defensibility, and how to size the opportunity correctly.
We're not pattern-matching away from conviction. We're pattern-matching toward it.