PDF and CSV bank statements → QuickBooks-ready transactions, in seconds. Every cleaned line is one click from the original source line in the source PDF — so when the partner or the IRS asks "where did this number come from?", the answer takes two seconds, not twenty minutes.
Built for solo accountants and small-firm bookkeepers. No credit card. No demo call. We email you when the private beta opens.
Want to feel it first? Play with the live demo → Three sample statements, click-through audit trail, no signup.
"I have some clients with monthly credit card statements that don't connect straight into my QuickBooks bank feed. I was wondering if there is an easier way to do this instead of manually entering and categorizing all the transactions from csv/pdf?"
Drag a PDF or CSV. Within ~30 seconds you have a normalized transaction table — dates ISO-8601, amounts signed, vendors canonicalized, categories suggested. The part you can't get from any of the other PDF-to-QBO tools: a one-click audit trail back to the source line.
| Date | Vendor | Category | Amount | |
|---|---|---|---|---|
| 2026-03-12 | Amazon | Office Supplies | −42.99 | 🔍 source |
| 2026-03-13 | United Airlines | Travel | −418.20 | 🔍 source |
| 2026-03-14 | Staples | Office Supplies | −87.41 | 🔍 source |
03/12 AMZN MKTP US*A1B2C3 800-279-6620 WA 42.99-
In-app, this panel renders the actual PDF page with the source line highlighted in yellow. (Static text shown here for the demo.)
{
"date": "2026-03-12",
"amount": -42.99,
"vendor": "Amazon",
"category": "Office Supplies",
"confidence": 0.94
}
Revert any single transformation. Edit manually. Or sign off.
A live demo with three sample statements (Chase Sapphire, BofA Business Checking, Wells Fargo SMB). Click any 🔍 to see source-line traceback in action.
Most of the existing PDF-to-QBO tools transform the data and hand it back to you as a black box. That works fine — until a reviewer flags a transaction and you spend twenty minutes flipping back to the original PDF, eyeballing column positions, and trying to re-derive how a $42.99 line item became "Office Supplies." Or worse — you don't catch a mis-classified line at all because you stopped looking.
Ledgerline is built for the moment you have to defend the work. Every cleaned line points back to the exact source — the file, the page, the bbox, the raw extracted text, the named transformations applied. So review takes minutes instead of hours. And the broken-windows-theory question — "if I have to verify one line, do I have to verify all of them?" — never starts.
Public posts from accountants and small-business owners describing the workflow we replace. Quoted verbatim; sources linked.
"If someone isn't paying attention to details like dates being wrong, old tick marks still being there, or notes that haven't been applicable for years, how can you trust they're going to pay attention to the details that actually matter?"
"I spend 2–3 hours every month cleaning bank statements before I can use them in Excel. Different date formats, garbage vendor names, amounts with parentheses… Am I the only one dealing with this? What's your workflow?"
"I thought to myself, no way this workbook isn't riddled with errors. I chased down every link and formula…"
Three quotes, three audiences, one pattern: the data lands clean enough — but the reviewer still has to re-perform the work to trust it. Ledgerline closes that loop with a per-line audit trail back to the source PDF.
Pricing below reflects the founding-cohort beta. Final pricing locks once we exit private beta.
| Your option | What it costs | What you get |
|---|---|---|
| Manual entry into QBO | $0 cash + 30–60 min/statement |
You eyeball every line. Defensible, but slow — and your hourly rate is the cost. |
| BanklyAi / generic PDF-to-QBO converters | $15–$50/mo per user |
Fast extraction. No audit trail. When a reviewer flags a line, you re-open the PDF. We benchmarked: when the visible PDF amount and the hidden text-layer amount disagree, these tools silently use the text-layer one — a $3,210 payroll deposit lands in your CSV as $32,104.50 with no warning. |
| ChatGPT / Claude on a redacted CSV | $0–$20/mo if you already pay for the AI |
Works for one statement. You redact PII by hand each time, paste in your import template, paste the result back. No traceback to the source PDF, no reconciliation check, no per-client memory. |
| Hubdoc / Dext / Receipt Bank | $20–$45/mo per user, often bundled with Xero |
Receipt-capture-first. Bank-statement support is secondary; audit trail is per-document, not per-line. |
| Ledgerline — founding (private beta) | $X/mo solo seat · locked for life |
Full app + the audit-trail differentiator. Beta cohort gets founding pricing for the lifetime of the account. |
Beta pricing is filled in for the cohort once we have ~20 waitlist signups and confirm willingness-to-pay in 5–10 short calls. Per-seat pricing for firms (2+ seats) is a v1.1 question.
The first 20 firms on the waitlist get private-beta access, founding pricing locked for life, and a 20-minute call with the builder to shape the v1 vendor + category defaults around your client mix.
No spam. One email when the beta opens. We'll ask 3 questions: what accounting software you use, how many client bank statements you process per month, and what your biggest current pain is.
Same input (PDF or CSV statement), same output (QBO-ready transactions). The difference is the audit trail — every cleaned line is one click from the source line in the source PDF, with the named transformations spelled out. The other tools transform the data and hand it back as a black box. We hand it back with a paper trail.
We ran two competitor parsers (BankStatementConverter and BanklyAi) against a 12-statement adversarial set. On clean US PDFs both tools clear ~95–100% row accuracy. On harder PDFs the failure modes diverge: BanklyAi silently returns zero transactions on multi-account, OCR-required, or non-US statements (no warning). BSC silently uses the hidden text-layer amount when it disagrees with the visible PDF amount — turning a $3,210 payroll deposit into $32,104.50 on every row. BSC at least fails loudly on redaction stripes (the only loud failure in the matrix). None of them surface a per-line audit trail back to the source PDF cell. Try the demo to see the audit-trail flow.
For one client, one month, ChatGPT-on-CSV works fine. The cost shows up at scale: you redact PII for every statement by hand, you re-paste your import template each time, you copy the AI's answer back into Excel — and when a reviewer flags a line you have nothing to point at. No source-PDF link. No named transformation. No reconciliation check. Ledgerline runs the same extraction with a per-client vendor memory, an end-to-end reconciliation banner, and the audit trail the AI doesn't give you.
v1: any text-extractable PDF (most major US banks — Chase, BofA, Wells, Capital One, Amex, plus most regional banks and credit unions) and any CSV export. Image-only / scanned PDFs work via an LLM fallback at slightly higher per-statement cost. We'll publish a tested-format list before beta opens; if your bank isn't on it, you can send a redacted sample at signup and we'll add it.
Hosted SaaS in v1, US-region. Data is encrypted at rest, retention is configurable per account, and we never train models on your data. On-prem / self-hosted deployment is a stretch goal for v1.1 if there's demand from regulated firms — flag it on signup if it matters.
v1 is export-and-import (QBO IIF / CSV / Excel). Direct QBO API push is on the v1.1 roadmap once we validate the export workflow with the founding cohort.
v1 ships QBO-flavored exports. Xero CSV is straightforward to add — likely v1.1. Sage and FreshBooks depend on customer demand; flag your tool on signup.
Yes — two ways. (1) The live demo shows the click-through audit-trail flow on three sample statements, no signup. (2) The private beta is free for 30 days, no card required, with your own statements.
An independent team focused on a single problem: making bank-statement workpapers reviewable in minutes instead of hours. Every founding-cohort account gets a direct line for feature requests, bug reports, and beta feedback.