AI Cash Flow Analysis Tool — Upload Transactions, Ask

What this export contains

What usually goes wrong with it

• Cash runway calculation requires combining inflows, outflows, and balance

  Knowing 'how many months of runway do we have?' requires knowing average monthly burn, current cash balance, and expected inflows — data across multiple rows and possibly multiple sheets.

  DataMimi Ask 'what is our average monthly net cash flow over the last 6 months?' and Datamimi groups by month, sums inflows and outflows, and calculates average net flow.

• Seasonal cash flow patterns are estimated, not measured

  You know Q4 is tight but quantifying the month-by-month cash flow pattern across the last 2 years requires grouping and summing across a large transaction export.

  DataMimi Ask 'which months historically have the lowest cash position?' and Datamimi groups by month name and averages the Running Balance to surface the seasonal pattern.

• Largest outflow categories are hidden in individual transaction rows

  Your bank statement has hundreds of rows. Finding which category of spending consumed the most cash requires grouping by Category and summing — not immediately obvious.

  DataMimi Ask 'which spending categories had the highest total outflows this quarter?' and Datamimi groups by Category and sums Outflow, ranked by total.

• Cash flow forecast accuracy is never reviewed

  You built a 12-week cash flow forecast last quarter. Whether actuals matched the forecast is never formally compared — the comparison requires joining two spreadsheets.

  DataMimi Upload your forecast and actuals and ask 'which months had the biggest variance between forecast and actual cash flow?' — Datamimi compares both files.

Common questions