Umai Retail expands Retano SCM with Leonardo AI and planner-controlled replenishment tools
In an update dated October 16, 2026, Retano reports that Umai Retail is extending its use of Retano SCM with the Leonardo AI assistant, a demand forecast control panel, event and promotion planning, and local assortment management. Umai operates more than 170 stores in Kyrgyzstan with an overall range of around 20,000 items. The vendor says Leonardo explains forecast and replenishment recommendations, while planners retain forecast controls and store managers decide local assortment changes within centrally defined matrices. Retano reports these capabilities and workflows, but does not demonstrate measured reductions in stockouts, inventory or planning cost attributable to this extension. This is AI-assisted, controlled replenishment rather than evidence of autonomous decision-making.
Illustrative grocery-store photograph, not an Umai Retail location or Retano interface. Photo: Khaya Motsa / Pexels. Source: https://www.pexels.com/photo/grocery-store-worker-stocking-shelves-with-vegetables-40240972/ - License: https://www.pexels.com/license/
The meaningful change is not that a replenishment platform has an AI assistant. It is that Umai Retail's expanded workflow, as described by Retano, connects explanations and forecast diagnostics to decisions owned by planners and store managers.
For retail supply chain leaders, this approach creates value only if the reasons behind forecast and assortment recommendations are actionable, local overrides are traceable, and subsequent outcomes can be compared with the assumptions used to make the decision. In a network spanning diverse store formats, centrally generated replenishment orders need a way to accommodate local events without giving every user unrestricted authority over the planning model.
The trade-off is control versus speed and consistency: more local discretion can improve responsiveness but can also create contradictory assumptions and weak accountability. The primary failure mode is an apparently explainable AI interface that generates many recommendations without improving stock availability, margin or inventory economics. Retano describes functionality and proposed controls, not independently measured gains or fully autonomous replenishment.