AI for retail and e-commerce in Africa
African retail runs on thin margins and WhatsApp conversations. The winners forecast demand instead of guessing, and answer every customer at the moment of intent — not the next business day.
What we hear
- Stock-outs and overstock from spreadsheet forecasting
- Customer questions at all hours across WhatsApp, social and web
- Generic promotions that ignore what each customer actually buys
- Order status queries drowning the support inbox
Where AI moves the numbers
Demand forecasting
Store- and SKU-level forecasts that respect seasonality, promotions and local events.
WhatsApp commerce agent
Catalogue questions, order tracking and re-orders handled conversationally, 24/7.
Related use case →Personalized offers
Recommendations and promotions matched to each customer’s actual behaviour.
Back-office automation
Supplier reconciliation, price-file processing and reporting without the month-end fire drill.
Related use case →Common questions
We have messy data — is that a problem?
It is normal. Every engagement starts with a data assessment; useful models are regularly built from imperfect POS and inventory data, and we tell you honestly when they cannot be.
Does this work for smaller retailers?
Yes — agents are priced by scope, and a WhatsApp commerce agent is often viable well before enterprise-scale ML is.
Let's talk retail & e-commerce
Book a 30-minute call — we'll map the highest-value AI play for your organisation.