Procurement, stock and payables ran across branches on disconnected sheets. The same supplier and SKU carried different rates, stock moving between branches got 'stuck in transit', and book stock drifted from physical — forcing spreadsheet workarounds and blind purchasing.
Before building anything, we mapped the operation. These are the findings that shaped what we built.
Supplier and SKU rates were inconsistent across branches, weakening negotiation and inflating cost.
Inter-branch transfers had no paired in-transit tracking — stock went 'missing' between locations.
Book vs physical stock drifted continuously, discovered only at year-end audit.
The data foundation, and the AI agents that turn it into decisions and action.
A centralised supplier master with rate and tax mapping and supplier-wise purchase orders locks in negotiated pricing — the clean procurement data the agents act on.
Reconciliation agents run continuously over a dual-ledger inventory, detecting and surfacing book-vs-physical drift and 'stuck-in-transit' stock as exception tasks — ending the phantom-stock problem that forces spreadsheet workarounds.
An agent turns procurement data into signals — MSQ violations where dispatched quantities fall below minimums, and supplier price-drift over time — so buyers negotiate on evidence and working capital is released from the right stock.
Measured against the baseline the audit established — before and after, on the metrics that move the P&L.
Start with a Business Transformation Audit — a structured working session where we map where AI changes your P&L, prioritised by impact.