STOP RE-TYPING WHAT YOUR
DOCUMENTS ALREADY SAY.

Invoices, quotes, purchase orders, intake forms, contracts, work orders, packing slips, delivery confirmations, customer applications, and most structured business documents. We handle PDFs, scanned images, photos taken on a phone, and email attachments. If your documents follow a recognizable layout or have consistent fields, we can build extraction for them.

Field-level accuracy on clean documents typically lands in the 95 to 99% range after the pipeline is tuned. Scanned or photographed documents land lower because OCR adds noise. The pipeline routes any field below a confidence threshold to a human review queue before posting, so the data that reaches your system of record is validated. We do not promise 100% because nobody can deliver it honestly.

No. The pipeline replaces the manual data entry step, not the judgment step. Your bookkeeper still reviews the books, categorizes edge cases, and handles anything the system flags. Most bookkeeping clients use this to free up the hours that used to go into typing invoice numbers and amounts into QuickBooks, so the bookkeeper can spend that time on actual accounting work.

Every field has a confidence score. Anything below the threshold goes into a human review queue where one of our operators corrects it before the document is posted to your system. The corrected field also goes back into the model to improve accuracy on the next batch. Errors that slip past review get caught at the next reconciliation and we trace the root cause.

Most builds go live in 4 to 6 weeks from kickoff. Week one is workflow mapping and document type cataloguing. Weeks two and three are extraction pipeline build and integration to your system of record. Week four is human review queue setup and parallel testing against your manual process. Weeks five and six are tuning until accuracy hits the agreed threshold.