Every field extracted correctly, or caught
Invoices, IDs, receipts, forms — AI-extracted text validated against the source image. Field-level accuracy verified by human reviewers before it enters your pipeline.
What reviewers see
Source image shows "Acme Corp" (no period). AI extraction added trailing period. Minor but will cause matching failures in ERP import. Corrected to "Acme Corp".
Source shows $4,280.00. AI extracted $4,280.00 but the "8" in source is partially obscured by a fold mark. Verified: correct value is $4,280.00 (confirmed by line-item sum: $3,200 + $480 + $600 = $4,280). Extraction was actually correct — fold mark created visual uncertainty but values reconcile.
Built for document processing
Invoice processing
AI-extracted invoice fields validated against source images for accounts payable automation.
ID verification
Verify AI-extracted data from passports, driver's licenses, and government IDs for KYC compliance.
Form processing
AI-extracted form fields from applications, registrations, and surveys validated for completeness and accuracy.
What human reviewers catch
OCR engines are fast but error-prone on the details that matter most. Reviewers check each extracted field against the source image and correct the failure modes below.
Misread digits
Transposed or swapped characters in totals, dates, and account numbers. Common confusions include 0/O, 1/l/I, 5/S, and 8/B — a single wrong digit cascades into financial or compliance errors.
Missed fields
Extraction sometimes drops fields entirely when confidence is low, leaving silent gaps. Reviewers check completeness against the source document and flag any field that was skipped or partially captured.
Table structure errors
Multi-column tables, line items, and merged cells frequently break layout detection. Reviewers reconstruct the intended row and column relationships so line-item totals reconcile with the grand total.
Handwriting ambiguity
Cursive, signatures, and filled-in form values resist confident machine reading. Human reviewers disambiguate based on context, stroke patterns, and surrounding field values.
Built for every document workflow
Reviewers are matched to document type so field-level checks use the right domain knowledge — from AP automation to clinical records.
Invoices
Vendor details, line items, totals, tax, and PO numbers validated for accounts payable automation and ERP import.
Forms
Structured fields from applications, registrations, intake documents, and surveys checked for completeness and accuracy.
Receipts
Merchant names, dates, amounts, and expense categories from crumpled or low-contrast receipt images.
ID documents
Passports, driver's licenses, and government IDs verified for KYC compliance and identity verification flows.
Medical records
Patient demographics, diagnoses, and medication fields extracted from clinical documents with field-level verification.
Legal contracts
Clause text, dates, parties, and defined terms extracted from multi-page agreements and scanned filings.
Submit OCR tasks via API
Send the source image alongside your AI extraction and review criteria. Verified Workflows routes the task to a document specialist, checks every field against the image, and returns corrections with a verdict. Standard turnaround is 24 hours; express delivers in 1–4 hours.
curl -X POST https://api.verifiedworkflows.com/v1/tasks \
-H "Authorization: Bearer $VW_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"type": "ocr",
"source_image_url": "https://cdn.example.com/invoice-04821.png",
"extraction": {
"invoice_number": "INV-2026-04821",
"total": "4280.00",
"vendor": "Acme Corp."
},
"criteria": ["field_accuracy", "completeness"],
"depth": "standard",
"turnaround": "standard"
}'The response includes a per-field match or mismatch verdict, reviewer annotations explaining each correction, and an overall pass / corrections needed / fail decision. Webhooks fire when the review completes so downstream pipelines can consume verified data immediately.
Stop shipping 0s that look like Os
Our reviewers catch what your OCR pipeline shrugs off: transposed invoice numbers, checkbox states the model flipped, the handwritten signature line it quietly skipped. Upload a document and get a field-by-field diff against the source — usually back in under 90 minutes.
Start building free Try the sandbox with a sample W-9