A selection of engagements across industries — each one a real challenge, solved with rigorous analytics and close collaboration.
A mid-tier microfinance institution was relying on manual credit assessments, leading to a 19% default rate. We built a machine learning credit-scoring model drawing on 40+ behavioural and transactional variables.
"Xorus gave us a model we could actually explain to regulators. The dashboard changed how our credit committee operates."
A leading Pan-African e-commerce platform was experiencing 23% stock-out rates during peak seasons, costing them millions in lost sales. We built a demand forecasting engine integrated directly into their warehouse workflow.
"We went into peak season with confidence for the first time. Xorus built something our ops team actually uses every single day."
A B2B SaaS startup serving African SMEs was losing 8% of its subscriber base monthly. Leadership had no visibility into which users were at risk until they had already cancelled. We built a full churn prediction and intervention system.
"Our CS team now reaches out to at-risk accounts before they even think about leaving. That shift alone has been transformational."
A regional education NGO operating across 6 countries was struggling to quantify programme impact for donor reporting. Data was spread across field offices with no unified view. We designed and built their entire impact data infrastructure from scratch.
"For the first time, we could walk into a donor meeting and show — not just tell — what our programmes achieve. It changed everything."
A growing African streaming platform had rich viewing data but no system to act on it. Content acquisitions were based on gut feel, and subscriber growth had plateaued. We built an audience intelligence layer to drive both content strategy and personalisation.
"We stopped guessing what our audience wanted. Xorus showed us exactly who was watching what — and why. Our content budget works twice as hard now."
A private hospital group with 4 facilities had no unified view of patient flow, bed utilisation, or staff efficiency. Decisions were made from end-of-month reports that arrived too late to act on. We built a real-time operational analytics system.
"We can now see what's happening across all four hospitals at once. Patient care improved because our team isn't flying blind anymore."
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