Built for bookkeepers, by a bookkeeper

Who built this

Hi, I'm Kendra. I'm an IRS Enrolled Agent, which is the federal license to represent taxpayers before the IRS, and a former Lead Bookkeeper on the QuickBooks Live team. I've been doing QBO cleanups for over 7 years now, with 5 of those years at Intuit. The product is shaped by what I learned in those rooms.

The methodology that drives the diagnostic comes from real cleanup files I've scoped by hand, mispriced more times than I'd like to admit, and eventually systematized into a category-by-category framework. That framework is what the detector library and the hour estimation post run on.

Why LedgerClean exists

Bookkeepers lose money on cleanup engagements because so often they price before they scope. A potential client describes a “little catch-up,” the bookkeeper quotes from gut, and the file turns out to be a 30-hour reconstruction at an 8-hour price. Every experienced bookkeeper has stories about this.

The fix isn't a smarter quote. It's a structured diagnostic that runs before the quote, on the prospect's actual file, that returns severity-weighted findings, an hour estimate the bookkeeper can defend, and a branded proposal PDF the client can sign. That's what LedgerClean does. Upload 6 to 8 standard QBO exports, get the diagnostic in about a minute, send the proposal, win the engagement.

How it's built

Eight deterministic detector categories run on every uploaded file: bank feed status, uncategorized transactions, duplicates, chart of accounts, reconciliation gaps, balance sheet anomalies, A/R and A/P aging, and owner-related transactions. The detectors are pure code, not AI guesses; they run the same way every time, and you can audit them.

On top of the detectors, an AI validation layer (Claude) reviews findings for obvious false positives, drafts a contextual summary, and produces step-by-step fix procedures and journal entry memos for each issue category. The AI never modifies your client's books. You execute every fix yourself; LedgerClean's job is to make sure you know exactly what to fix and in what order.

Who it's for

Professional bookkeepers handling client QBO files. If you sell cleanup engagements, run a fixed-fee or range-quote pricing model, or just want a defensible hour estimate before you commit to a price, LedgerClean is built for you. If you're an SMB owner looking to fix your own books without a bookkeeper, LedgerClean is not the right tool; we're built for the professional, not the end client.

Trust and data handling

Uploaded files are stored in a private bucket per project, processed to generate the diagnostic, and then the source files are deleted. We don't train any model on your data, we don't share it with third parties beyond the AI provider for the validation pass, and we never write back to your client's QBO. See the Privacy Policy for the full details.