Before AI can answer anything about your shop, something has to be writing it down
The most common reason an AI tool disappoints a business owner is not the AI. It is that the business was never recording the thing they wanted answered.
How retailers and distributors use AI across stock, sales, customer messages, and the day-to-day of running a counter or a warehouse.
The most common reason an AI tool disappoints a business owner is not the AI. It is that the business was never recording the thing they wanted answered.
We could have shipped Rai as a beautiful dashboard nobody logs into. Instead it answers on WhatsApp, in English, Swahili or Sheng, because adoption is not won by features - it is won by removing the reasons not to ask.
A quick demonstration: a badly-lit, angled photo of a carbon-copy delivery note, turned into clean typed data in seconds. Stage 2 works on real paper, not just tidy files - with one thing you must always check.
Comparing supplier quotes by eye is slow and easy to get wrong - different formats, hidden extras, different units. Upload them and get one clear table in two minutes. A simple, repeatable stage 2 win.
A wrong number delivered confidently is worse than no number at all. The reason AI tools get business figures wrong is not that the model is stupid - it is that your database does not mean what its table names say. This is the fix.
Most shop owners already have the data they need to run a tighter business. It is just locked inside a system that only answers the questions someone built a report for. Rai is an AI analyst that answers the questions you actually ask - in plain language, from your own numbers.
A walk through writing a whole product catalogue with an AI assistant - the messy input, the prompt that worked, the output, and the ones we had to fix. This is stage 1: AI as a fast, capable assistant you brief and check.
We build the systems we write about - for retail, clinics, workshops and property businesses across Africa. Tell us what you run, and we will tell you honestly where AI would help and where it would not.