The same invoice number gets posted twice — once as
3/04/2026 for $1,250.00, again as
2026-03-04 for 1250 — so your AR aging
report double-counts the receivable and your team chases a balance
that was never really open. DataTools standardizes every invoice
date, due date, and amount, lowercases client emails, then removes
the double-entered invoice numbers — taking a real open-invoices
export from 26 rows to 21, five duplicate invoices
removed — all on your own machine, with nothing uploaded.
The same invoice number posted twice — once in MM/DD/YYYY, once in ISO — lands in two rows and gets counted twice. Your 60-day bucket looks worse than it is, and the receivables total overstates what's actually owed.
What it costs: overstated AR, a balance sheet that won't reconcile, and a controller asking why.
When a duplicate invoice number shows as still-open, a collector emails the client about a balance that doesn't exist. The client pushes back, trust erodes, and your team burns a morning untangling it.
What it costs: wasted collections hours + an awkward "please disregard" to the client.
Every cloud-based cleaner wants you to upload your full receivables ledger — client names, amounts, contact emails. That's a data-handling review your firm doesn't want to run. DataTools is desktop-only — no upload, no DPA, no review.
What it costs: weeks of review per tool, or just not cleaning the data at all.
Invoice dates arrive as 3/4/26, 2026-03-04, and Mar 4 2026; due dates are just as mixed. Sort by date and the buckets are wrong, so the wrong invoices show up in the wrong aging column.
What it costs: 1–3 hours per close reconciling dates by hand, every period.
Client names come in mixed casing and emails arrive as Billing@ClientCo.com in one row and billing@clientco.com in another — so the same client looks like two, and reminders go out twice or not at all.
What it costs: duplicate dunning, missed reminders, and a client list that won't group.
When one of the two twin rows has a blank status, you can't tell if the invoice is open, partial, or paid — so it either gets dropped from the aging report or counted at the wrong stage.
What it costs: misclassified receivables and an aging report you can't trust.
The demo below loads a 26-row open-invoices export with five
double-entered invoice numbers — the same invoice posted twice in
different date and amount formats (3/04/2026 vs
2026-03-04, $1,250.00 vs 1250),
client emails in mixed case, and one blank invoice status. Click
Run pipeline and watch the 5-step pipeline (text
clean → format → missing → column map → dedup) standardize both date
columns to ISO, coerce amounts to numbers, lowercase the emails, and
collapse 26 rows to 21 — backfilling the blank status from its twin
row so the aging report is accurate.
Match on invoice number, drop the second posting, and keep one canonical row per invoice — backfilling a blank status, due date, or amount from its twin so nothing accurate is lost when the duplicate goes.
Coerce every invoice date and due date to ISO and every amount to a clean number, so the aging buckets sort correctly and the receivables total ties out to the ledger.
Lowercase client emails and fix name casing so each client groups as one. Send remit-to reminders once, to a clean contact list — not twice because two rows looked like two clients.
Your billing system exports 3/04/2026. The re-post of
the same invoice has 2026-03-04. The amount is
$1,250.00 in one row and 1250 in the other.
DataTools reads each row, normalizes both date columns to ISO,
coerces the amount to a number, and then matches on invoice number
to keep exactly one canonical row per receivable.
$1,250.00 and 1250 resolve to the same value — no false mismatch between twin rows.Your aging report is only as good as the export under it. Every double-entered invoice number is a receivable counted twice — it inflates the aging buckets, overstates the total owed, and sends collections after balances that aren't really open. DataTools catches them once, before the report runs, by matching on invoice number with the date and amount noise already standardized away.
Cloud cleaning tools require you to upload your AR ledger — client names, invoice amounts, remit-to contacts. That ledger is sensitive client financial data, and once it's on someone else's server, your firm owns a data-handling problem you didn't need. DataTools is a desktop app. There is no upload step.
Match on invoice number; keep one canonical row per receivable and backfill blanks from the twin.
Smart quotes from copy-paste, NBSP from spreadsheet exports, BOM from Excel.
Invoice and due dates to ISO, amounts to clean numbers, client emails lowercased.
Detect TBD, (unknown), — and backfill blank invoice statuses on dedupe.
Project to your aging-report schema, coerce amount to a number, reorder fields for import.
Save the cleanup as JSON. Drop next period's open-invoices export on it. Same dedupe, automated.
Available when 3+ bundles ship. Includes everything in the Accounts Receivable pack plus the Bookkeeper and Accounts Payable / 1099 bundles. Save $48.
Coming when readyNo — it cleans the export before you run the aging report or import it back. Most billing systems will happily hold two postings of the same invoice number; DataTools catches the double-entered invoice so it never inflates a single aging bucket.
It matches on invoice number after the date and amount formats are standardized away. So a posting dated 3/04/2026 for $1,250.00 and its twin dated 2026-03-04 for 1250 are recognized as one invoice — and only one canonical row survives.
It's backfilled. If one twin row has a blank status and the other says open, the surviving row inherits open — so no real receivable drops off the aging report just because the duplicate carried the better data.
Yes. The licence is per-operator, not per-client. Run it on every client's open-invoices export for the same $49.
A row-by-row CSV: every modified cell with its original value, new value, and which rule fired — every date coerced to ISO, every amount normalized, every duplicate invoice removed. A separate JSON file describes the pipeline that produced it, so the cleanup reproduces deterministically and your client can verify it on their machine.
Try the live demo above on the sample open-invoices export before you buy. If DataTools doesn't fit your workflow within 14 days, email for a refund — no questions asked.
One $49 download. Standardizes invoice dates, due dates, and amounts, lowercases client emails, removes the double-entered invoices your aging report was counting twice, and saves a pipeline you can re-run on next period's open-invoices export.
Get DataTools for Accounting — $49 →