Our services
Practical data, AI and automation solutions.
From data strategy to intelligent automation, we help organisations across East Africa turn data into measurable value.
Industries
Solutions for East Africa's core sectors
Practical data, AI and automation solutions shaped by real operating environments.
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Service
We build predictive models and run rigorous analysis that quantify risk, forecast demand and explain customer behaviour, so decisions rest on evidence rather than instinct.
Practical data science solutions designed to solve real business problems.
A clear and structured process to deliver data science solutions that create value.
Good models do not live in notebooks. We deliver forecasts and scores your teams use every day, with the reasoning visible so people trust and act on them.
We work with leading platforms and choose what fits your stack, budget and skills.
Banking / SACCO
A tier-2 bank cut default rates while expanding access to first-time borrowers through an explainable machine learning model, embedded directly into its loan origination workflow.
Read full case studyQuick answers to common questions about our data science services.
Less than most teams expect. Two to three years of clean transaction or operational history is often enough for a strong first model. We assess this in week one.
Yes. Data cleaning and profiling is part of every project, and we leave you with documented, reusable pipelines.
We favour interpretable models where possible and use techniques such as SHAP to show which factors drive each prediction.
Yes. We test performance across customer groups and document any trade-offs before a model goes live.
You do. All code, models and documentation are handed over at the end of the engagement.
A proof of value usually takes 6 to 10 weeks, followed by deployment into your systems.
Yes. We often work side by side with internal teams and include coaching so the capability stays with you.
Have a question your data could answer?
Book a free consultation to scope a proof of value around your highest-impact question.
