Investors who want exposure to African markets face a strange problem: there is plenty of data, and almost no intelligence. Reports are scattered, stale, inconsistent between countries, and rarely structured for a decision. SubSaharaData exists to close that gap. As CTO, I lead the engineering and product that turns 54 nations' worth of complexity into something a capital allocator can act on.
The problem: data without a decision
If you want to know where capital is flowing in West Africa, or how political risk in one market compares to its neighbour, you can find a dozen PDFs and no clear answer. The numbers don't line up. The methodology differs by source. Nothing is built for comparison. The work of turning that into a position falls entirely on the analyst.
Our thesis is simple: the value isn't the raw data, it's the decision-grade layer on top of it — normalised, scored, comparable across all 54 countries, and surfaced in the moment someone needs to act.
What the platform does
- Risk scoring across every African nation, on a consistent methodology so countries can actually be compared.
- Capital-flow tracking — where money is moving, into which sectors, and how that's trending.
- Industry assessments across 13 sectors, so a user can drill from a continent-level view down to a specific industry in a specific country.
- A dashboard built for fast comprehension — maps, charts and scores that answer the question before the analyst has to assemble it.
How I built it
The stack is deliberately lean and cloud-native so a small team can ship fast without drowning in infrastructure:
- Next.js for the application surface — server components keep the heavy data work off the client and the pages fast.
- Supabase (Postgres) as the data backbone, with row-level security enforcing who can see what.
- Recharts and Leaflet for the visualisation layer — the maps and charts that make 54 countries legible at a glance.
- Tailwind for a consistent design system, deployed on Vercel.
The hard part was never the front end. It was the data engineering: ingesting inconsistent sources, normalising them onto one schema, scoring them on a defensible methodology, and keeping the whole thing fresh and trustworthy. Security is first-class — this is information investors will move real money on, so the architecture treats data integrity and access control as features, not afterthoughts.
The platform's job is to let an investor know where to act before the capital arrives. Everything in the architecture serves that one sentence.
Where it's going
The roadmap deepens the intelligence layer — more sectors, sharper scoring, and tighter feedback loops between what investors ask and what the platform surfaces. The goal stays constant: decision-grade, not data-dump.