Assessing whether your data is ready enough

Almost every mid-sized business we meet believes its data is not ready for AI. Almost every one of them is partly right, and it rarely matters as much as they think.

Readiness is not a property of the whole data estate. It is a property of one use case. For reconciliation, you need the ledger, the bank feed and the rules. For forecasting, you need clean actuals and a view of the drivers. You do not need a lakehouse.

In Prove we test the use case on your real data, gaps and all, and measure what the gaps cost. That turns a vague data strategy into a short list of fixes that pay for themselves, in the order that matters.