Extract Desk: Document Parsing & Structured Data Capture
Extract structured data from invoices, reports, and documents into your existing tools
Outcomes
- Eliminate manual data entry from vendor invoices, statements, and reports
- Reduce invoice processing errors by catching mismatches before they hit the books
- Turn a 20-minute-per-document manual task into a 2-minute review-and-approve step
- Feed extracted data directly into QuickBooks and Google Sheets without re-keying
Before & After
Before
- Bookkeeper opens each vendor invoice PDF, reads the line items, and types them into QuickBooks manually
- Monthly bank statements arrive as PDFs and someone re-enters the totals into a reconciliation spreadsheet
- Errors from manual data entry surface weeks later during month-end close
After
- Invoices are parsed automatically; the bookkeeper reviews a pre-filled summary and approves with one click
- Statement data is extracted and dropped into the reconciliation sheet within minutes of arrival
- Validation checks flag mismatches (wrong total, missing line item, duplicate invoice number) at extraction time
Workflow Map
Integrations
Exceptions Handled
- Document is a scanned image with no selectable text: routes to OCR pipeline before extraction; flags low-confidence results for manual review
- Extracted total does not match the sum of line items: halts processing and sends the discrepancy to the bookkeeper via Slack
- Duplicate invoice number detected against existing records: flags as potential duplicate and skips auto-posting to QuickBooks
- Unrecognized vendor: creates a new vendor suggestion in the review step rather than auto-creating in QuickBooks
- Multi-page document with mixed content (invoice + cover letter): extracts only the invoice pages based on content classification
- Password-protected PDF: notifies via Slack and queues for manual handling
7-Day Implementation Timeline
Audit current document flow; inventory document types, volumes, and destinations
Configure document classification rules and connect Gmail/Google Drive intake sources
Map extraction fields per document type; set up vendor matching against existing QuickBooks vendor list
Build validation rules: total checks, duplicate detection, required field verification
Wire up the QuickBooks posting logic and Google Sheets logging; configure Slack review notifications
Parallel run: documents processed by both manual and automated methods; compare extraction accuracy
Go live; first batch of real documents processed through the automated pipeline
Pricing Hint
Document extraction workflows typically fall within the Grow plan. High-volume processing (100+ documents/month) may need Scale.
View pricing plans →Frequently Asked Questions
PDF (native and scanned), images (JPG, PNG), and email body text. Native PDFs extract the fastest and most accurately. Scanned documents go through an OCR step and flag low-confidence fields for review. Book a 15-min Fit Call to test with your actual documents.
Yes. The extraction model adapts to different invoice layouts. After the first few documents from a new vendor, accuracy improves as the system learns where that vendor places key fields. Unusual formats get routed for manual review until the pattern is established.
Every extraction goes through validation (total vs. line items, duplicate checks) and then human review before posting to QuickBooks. Nothing hits your books without your bookkeeper approving it.
The same pipeline supports any structured document. During onboarding, we configure which document types you process and where each type's data should land. Book a 15-min Fit Call to walk through your document mix.
How It Works
When a vendor invoice, bank statement, or expense report lands in your inbox or Google Drive, the workflow picks it up, figures out what kind of document it is, and extracts the structured data: vendor name, invoice number, line items, amounts, tax, and total. It then validates the extraction (does the total actually match the line items? have we seen this invoice number before?) and sends a clean summary to your bookkeeper in Slack alongside the original document. The bookkeeper reviews, approves, and the data posts to QuickBooks Online and your tracking spreadsheet. The original document moves to an archive folder.
Why It Matters
Manual data entry from documents is slow, error-prone, and nobody’s favorite task. A single transposed digit in an invoice amount can cascade through your books and surface as a reconciliation headache weeks later. The problem is not that bookkeepers are careless. The problem is that re-keying data from one format into another is fundamentally a machine task being done by a human. Automating the extraction and validation steps means your bookkeeper spends their time on judgment calls (is this expense coded correctly? does this vendor bill look right?) instead of typing numbers.
What You Get on Day Seven
By the end of implementation week, incoming documents flow through an automated parse-validate-review pipeline. The parallel run on Day 6 puts automated extractions next to manual entries so your bookkeeper can verify accuracy before the switch. From that point forward, a 20-minute manual task becomes a 2-minute review, and validation catches errors before they reach your books instead of after.
Learn More
Ready to automate this workflow?
Book a 15-minute fit call. We will walk through your setup, confirm the integrations, and map out your 7-day go-live plan.
Extract Desk: Document Parsing & Structured Data Capture
Book a 15-min Fit Call