AI assistant for leadership and stores

Create consumption tables per question: daily sales by store, fiscal line item, inventory by product and branch, margin by item. Each one has its grain declared in the description in one sentence ("One row per store, per day"). Do not expose a generic table that mixes grains, and do not use a financial field from an operational table as revenue.

Start the column description with the tag: @pk for the grain key, @fk for a foreign key, @measure additive for something summable across any dimension, @measure non_additive for average ticket and percentages, @grain=daily or monthly. Then, in text: origin, calculation rule and pitfall. Document the table, not just the transformation.

"How much did we sell" is answered with net sales (gross minus discounts minus cancellations). The answer always names the metric, the period and the store. Gross only when asked.

ERP date fields stored as midnight UTC are already the business day. The AI computes today and yesterday in America/Sao_Paulo and compares directly, without converting the field. The rule is written in the column description and in the context document.

In Nekt, permissions apply to an entire layer or to a table or view, with read and edit roles. Folders in the catalog are only visual organization and protect nothing. Create one view per store (daily sales filtered to that store) and grant each manager only theirs. Use a token scoped by table for each audience's assistant.

Cancellations and cancellation attempts identify the cashier and are used for evaluation and investigation. They do not go into the store views, not even filtered to the store itself. They stay in leadership, audit and HR views.

The assistant never answers a number without running the query. It also does not decline for lack of data before reading the structure of the domain's semantic table. Metrics flagged as "to be validated" are not inferred. When the field does not exist, the answer is "data not found in this source".

Available = total quantity minus reserved, never negative. Branches that mirror the same physical inventory are aggregated by stock group, never summed. Products with unlimited stock stay out. A nonexistent product and an out-of-stock product get different answers. Product codes are standardized (for example, left-padded with zeros to 18 positions in SAP) before joining with sales.

The assistant's views run on an event right after the source table, never with a manual trigger. A monitor with its own schedule detects missing runs (for example, more than 120 minutes without a load). The answer states the date and time of the last update.

Companies in the same group can show up as separate accounts or stores. Transfers between them are neither revenue nor operating expense and are eliminated in the consolidated view. Margin comes from the official margin table, never recomputed by the AI with a different rule.