Financial reporting cut from weeks to hours

The distributor was running finance, inventory, sales and procurement across a handful of legacy systems that had never been designed to talk to each other. Every month-end close meant three finance staff manually reconciling exports from each system in spreadsheets — a process that reliably took two to three weeks before leadership saw a single trustworthy number.

Inventory decisions across the three warehouses were made on instinct rather than data. The same static reorder rule was applied to every SKU regardless of how it actually moved, which meant fast-moving items stocked out at the same time slow-moving ones sat overstocked, tying up warehouse space and cash simultaneously.

Nobody could answer a simple question — 'what's our inventory exposure in warehouse two this month?' — without a multi-day data-pull request to IT. By the time an answer came back, the number was already stale.

We replaced the patchwork of legacy systems with a single AI-enhanced ERP core unifying finance, inventory, sales and procurement, so every department finally worked from the same live numbers instead of reconciling separate exports after the fact.

On top of that core, a demand forecasting model was built per SKU rather than one blanket rule for the whole catalogue — incorporating each item’s actual sales velocity, seasonality and the specific supplier’s lead time, so safety stock is recalculated continuously instead of set once and forgotten.

Automated anomaly detection now runs against every transaction, flagging mismatched purchase orders, invoices and goods receipts the moment they diverge, instead of surfacing the discrepancy weeks later during a manual close.

Executive dashboards let leadership ask plain-language questions — inventory exposure by warehouse, cash tied up by SKU category, this month versus last — and get a live answer instead of filing a request with IT.

Finance now closes the month in days rather than weeks, and warehouse managers reorder against a live, per-SKU forecast instead of a static spreadsheet rule that treated every product the same.