Upload PDF or scanned statements and get date / description / amount rows you can actually trust: each value links back to its exact spot on the page, running balances are cross-checked automatically, and anything suspicious is flagged for a one-click review before it reaches your spreadsheet.
Drop in one statement or a whole batch (200 files queue fine) — PDFs and scans both work.
The bank-statement Field Set extracts date, description, debit/credit and balance per row, anchored to the page. Balance math is verified: if a row breaks the running balance, it turns yellow.
Clear the few flagged rows against the highlighted source snippets, then export a summary table to Excel, CSV or a QuickBooks-ready file.
Opening balance + transactions must equal closing balance. When they do not, the offending rows are flagged with the delta — the classic transposed-digit error is caught before export.
Each extracted value links to its box on the original page. A value that cannot be found in the source text is marked "not in source" and never silently exported.
Export a CSV pre-formatted for each tool's bank-statement import — column names and order match what their import wizards expect, with debits and credits signed correctly — or a full summary table to Excel/CSV.
The export switch delivers only rows that passed checks or were human-confirmed, and counts what was excluded — an audit trail instead of a leap of faith.
Every accountant who has cleaned up a year of statements knows the failure mode: the converter outputs a beautiful spreadsheet with one silently transposed amount, and the error only surfaces weeks later when the books refuse to reconcile. Generic PDF-to-Excel tools optimize for looking right; bookkeeping needs being right, and the difference is exactly one wrong digit.
OhMyOCR attacks the problem structurally. Every extracted amount is anchored to its pixel region on the statement — a value that cannot be located in the source text is flagged as “not in source,” never exported silently. Then the running-balance check recomputes opening balance + transactions against the printed closing balance: if they disagree by even one cent, the rows involved turn yellow with the delta shown. You review a handful of flags with the original snippets beside you, not five hundred numbers on faith.
Batches are the native unit: drop in twelve months of statements, and files become reviewable the moment each one finishes — no waiting for the whole queue. The cross-file review flow chains the flagged rows across the batch (J/K/Enter), and the batch page shows exactly how many files are verified versus still carrying flags.
When the flags are cleared, the Export Center produces one summary table for the entire batch — your Field Set columns plus source_file and status for every row — as Excel, CSV, or a QuickBooks-ready 3-column file with debits signed negative. A verified-only switch excludes any row that still carries an unresolved flag and tells you how many it excluded: the export is an audit trail, not a leap of faith.
Upload the statement, pick the built-in Bank statement Field Set (it is preselected if you arrive from this page), run extraction, clear any yellow flags against the highlighted page snippets, then export Summary Excel or CSV.
Generic converters hand you a table and hope it is right. OhMyOCR anchors every value to the page, cross-checks running balances, and explicitly flags what needs human eyes — you review five flags, not five hundred numbers.
Yes. Scans go through OCR first; the extraction and balance checks work the same. Low-confidence regions are flagged with image snippets so you can verify against the original in one glance.
Yes — a QuickBooks-compatible 3-column CSV (Date, Description, Amount) with correct signs for debits and credits, which QuickBooks imports directly. To be precise: .qbo bank-feed files are a different format we don't generate — the CSV route covers the same import. Xero and Wave have their own dedicated export formats, matching each import wizard's expected columns.
Documents are processed through our own pipeline, never used to train AI models, and you can enable auto-deletion of originals N days after processing. There is also a zero-LLM rules mode for extraction.
Word ↔ Word / PDF
How to Compare Two Word Documents
A vs B → Redline
Compare PDF Files for Differences
Original + Translation
Translate Scanned PDFs & Documents, Side by Side
PDF → Excel
Extract Tables from PDF to Excel
Image → Excel
Image to Excel Converter
Image → Text
Image to Text Converter
PDF → Text
PDF to Text Converter (OCR)
Document Parsing
Document Parsing OCR
Image Translation
Image Translator with OCR
Handwriting → Text
Handwriting to Text Converter
Screenshot → Text
Screenshot to Text
Math → LaTeX
Photo of Math to LaTeX
Image → Word
Image to Word Converter
PDF → Markdown
PDF to Markdown Converter
Receipt → Text / Excel
Scan Receipts into Excel, CSV & QuickBooks
Journal → Searchable text
Digitize Your Handwritten Journals
Letters → Archive
Transcribe Old Letters and Family Papers
Scan → Searchable PDF
Make Scanned PDFs Searchable (and Bates-Numbered)
日本語 → English
Translate Japanese PDFs — with the original in view
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