Cards arrange information for people, not databases. OCR.now produces a text draft and a review method; it does not silently guess which line is a person, company, role, or address.
Cards are arranged for people rather than databases. This route recognizes the text but keeps field assignment and VCF creation as explicit human-reviewed steps.
Recognition is only the first stage. Use OCR Review for Diacritics, Names and Punctuation for the relevant control checks and Numeric OCR Validation for Dates, Totals and Identifiers for values that must be exact. If the output structure changes, compare Bilingual OCR with JPG to Text.
Check identity and communication characters exactly
| Review point | Likely failure | Validation action |
|---|---|---|
| Identity | Company, person, and role lines are confused | Classify each visible line before mapping fields |
| Contact tokens | Plus signs, dots, and extensions disappear | Verify phone and email character by character |
| Multiple languages | Parallel contact blocks merge | Map each region and retain the preferred source spelling |
Assign each visible line to a verified contact field
Separate person name, company, and role deliberately.
Verify plus signs, country codes, extensions, dots, and underscores.
Create the vCard only after every field is reviewed in a contacts application.
Business card entry scenario
For a card with a logo above a person name, do not assume the largest recognized word is the contact. Identify the organization, person, and role from their visible placement. Check the country code, extension, email punctuation, and web domain before saving the record.
When the card is too ambiguous for automatic mapping
Enter short cards manually when review takes less time than correcting extraction. Use a contact-management or card-scanning system when duplicate detection, consent, CRM mapping, and vCard generation are required.