Native Retail AI explains why Ariane RDS is different from AI tools that simply sit on top of retail data and generate fluent explanations. Ariane reasons inside a pre-built model of how retail commerce actually works, called the Retail Knowledge Map, before generating any analysis.
The Retail Knowledge Map is a formal model of how commercial variables causally relate to each other, structurally rather than statistically. It defines, for example, that distribution causes traffic, that traffic causes sales, and that supplier reliability enables inventory. These are treated as rules, not inferences, so Ariane's contextual analysis reasons within these rules and cannot generate a causal explanation that violates known retail logic.
In one example, Ariane traced a sales decline in cluster B stores back to a range deletion decision made 8 weeks earlier, isolating the resulting traffic shortfall as accounting for 11 percentage points of a 14 percentage point sales decline, and issued a Range Add decision card with a $366K financial impact and a deadline before the next planogram cycle closed. In another example, Ariane identified a SKU with a price index 5 points above the shopper sensitivity threshold in its elasticity model, linked it to a 5 percentage point volume share decline over 4 weeks, and issued a price decision card projecting a 4% reprice would recover the lost share within 6 weeks for a net uplift of $869K.