Spreadsheet errors come in two kinds. Loud errors like #REF!, #N/A and #DIV/0! are easy to see. Quiet errors are worse: a hard-coded number inside a formula, a SUM range that misses the last row, or text in a numeric column. Those produce wrong answers that look right.
Plumb is built on a simple idea: the data your business runs on should be trustworthy before anyone draws conclusions from it. Cleaning, checking and reshaping data should not need macros, scripts or a weekend. Plumb keeps your files private, shows every change it proposes, and lets you approve fixes instead of hunting for problems by hand.
How Plumb helps: Data auditing
Plumb's data auditing checks a workbook for both kinds. It lists formula errors, inconsistent formulas within a column, numbers stored as text, values that break a column's pattern and statistical outliers, and links each finding to the exact cell.
How It Works
Run through loud errors first, then systematically look for quiet ones.
- Find formula errors: Home > Find & Select > Go To Special > Formulas, tick only Errors.
- Trace a suspicious result with Formulas > Trace Precedents to see which cells feed it.
- Check for inconsistent formulas: Excel's green triangle warnings often flag a formula that differs from its neighbours.
- Use Formulas > Show Formulas (Ctrl+`) to spot hard-coded numbers where references should be.
- Validate types: =ISTEXT() on numeric columns catches numbers stored as text.
- Sanity-check totals against an independent source, such as a system report.
- In Plumb: upload the workbook and review the audit report, grouped by severity, with links to each cell.
Where This Helps
Financial models
Catch broken references and hard-coded overrides before a forecast goes to leadership.
Shared trackers
Find rows where teammates typed text into numeric columns.
Monthly close
Verify that totals reconcile and no rows were left out of a range.
Try Plumb in early access
Plumb is in early access. Join the waitlist on tryplumb.pro to get an invite. Early access covers Excel (.xlsx), CSV and JSON files, and we are adding more sources as people ask for them. Your files are processed privately and are never used to train models.
Catch the quiet errors
Now you have a repeatable way to do it, by hand or with Plumb. Join the waitlist and tell us what your data looks like; we read every reply.
Join the waitlist