AI Tool for Inventory Analysis — Upload Stock File, Ask

What this export contains

What usually goes wrong with it

• Identifying slow-moving inventory requires manual filtering

  Your inventory export has 2,000 SKUs. Finding which items haven't sold in 90 days requires adding a formula column, filtering by date, and sorting — a 20-minute task before you see any insight.

  DataMimi Ask 'which SKUs have had zero sales in the last 90 days?' and Datamimi reads your Last Sale Date column and returns the list — no formula column needed.

• Reorder point alerts are buried in a column nobody checks

  Your stock export has a Reorder Point column but checking it against Current Stock for every SKU requires a formula or conditional formatting that gets cleared when the file is updated.

  DataMimi Ask 'which items are below reorder point?' and Datamimi compares Current Stock to Reorder Point for every row and returns the flagged SKUs immediately.

• Supplier lead times affect reorder timing but are in a separate file

  Your stock levels are in one spreadsheet and supplier lead times are in another. Combining them to calculate actual reorder urgency requires a VLOOKUP between files.

  DataMimi Upload your inventory and supplier files together (Starter plan and above) and ask 'which below-reorder-point items have a lead time over 14 days?' — Datamimi cross-references both files.

• Overstock ties up cash but is invisible until you sort the right column

  Identifying which categories have the most excess inventory requires sorting by days-of-stock, a calculated field that doesn't exist in the raw export.

  DataMimi Ask 'which categories have more than 180 days of stock on hand?' and Datamimi calculates days-of-stock from your sales velocity columns and ranks the overstock.

Common questions