Invoice & Document Data Extraction With Checks, Into Your SystemsKrystian Siek
PDFs, scans and phone photos of invoices, receipts, POs or forms turned into checked, structured data, sent to Excel, Google Sheets, your accounting export or your database.
Who it's for: finance and operations teams that still retype documents, or whose current extraction makes mistakes nobody catches.
What it does
Every extracted value traced to its place on the page, so a reviewer can check it in one click.
Scans read twice (vision model + OCR) and compared.
Totals, VAT, IBANs and routing numbers checked in code, not by the model.
A risk gate for bank-detail changes, duplicates and PO mismatches, with a review queue for anything unsure.
Proof: Docket, my live invoice intake product. Published eval: 99.2% of fields right across 8 countries, about 3 s per document. Try it with your own invoice at adaptivesystems.dev/docket/try.
Process: you send 20–50 of your real documents; I measure accuracy on them first, then build and hand over with the test set.
FAQs
Example work
Starting at$1,000
Duration2 weeks
Tags
Data Extraction
Python
AI Automation
Document AI
Invoice Processing
Optical Character Recognition
Service provided by
Krystian Siek Watford, UK
Invoice & Document Data Extraction With Checks, Into Your SystemsKrystian Siek
Starting at$1,000
Duration2 weeks
Tags
Data Extraction
Python
AI Automation
Document AI
Invoice Processing
Optical Character Recognition
PDFs, scans and phone photos of invoices, receipts, POs or forms turned into checked, structured data, sent to Excel, Google Sheets, your accounting export or your database.
Who it's for: finance and operations teams that still retype documents, or whose current extraction makes mistakes nobody catches.
What it does
Every extracted value traced to its place on the page, so a reviewer can check it in one click.
Scans read twice (vision model + OCR) and compared.
Totals, VAT, IBANs and routing numbers checked in code, not by the model.
A risk gate for bank-detail changes, duplicates and PO mismatches, with a review queue for anything unsure.
Proof: Docket, my live invoice intake product. Published eval: 99.2% of fields right across 8 countries, about 3 s per document. Try it with your own invoice at adaptivesystems.dev/docket/try.
Process: you send 20–50 of your real documents; I measure accuracy on them first, then build and hand over with the test set.
FAQs
Example work
$1,000