Business Card Scanner
Upload business card
Capture the full card with sharp focus on name, title, and contact lines. Max 15 MB. OCR runs in your browser — nothing is uploaded.
Tip: A straight-on photo beats an angled shot for email and phone accuracy.
How to use
- Place the card on a plain, non-reflective background (white or dark gray works well).
- Hold the phone parallel to the card — avoid perspective skew that bends letter shapes.
- Capture both front and back if details are split; upload the side with the contact block you need first.
- Upload JPG, PNG, or WebP (max 15 MB) and check the preview for sharp name and email lines.
- Click Scan card and wait for OCR to complete.
- Copy name, title, company, email, phone, and URL lines into your CRM, contacts app, or LinkedIn.
FAQ
What is Business Card Scanner?
It is an OCR page optimized for small, dense contact blocks on standard business cards. You photograph or upload a card and get plain text you can paste into your address book or CRM.
Does it create vCard or Outlook contacts automatically?
Not in this version. Output is editable text. You paste into Apple Contacts, Google, HubSpot, Salesforce, or a spreadsheet import.
Is the card image sent to your servers?
No. Recognition runs locally with Tesseract.js after you select the file.
How do I improve email and phone accuracy?
Use even lighting, fill the frame with the card, keep the lens focused on the email line, and avoid glossy lamination glare. Re-shoot if `@` or `+` symbols look blurry in preview.
Can it read two-sided cards?
Upload one side at a time. Run OCR on the front for name and title, then the back for address or secondary numbers if needed.
Will it read QR codes on cards?
This page reads printed text via OCR, not QR payloads. Use a QR reader tool if the card only encodes a vCard in a code.
What about non-English cards?
English (`eng`) mode handles Latin letters common on international cards. Mixed scripts may need manual correction.
Introduction
Business Card Scanner saves time after conferences, meetups, and sales calls. Instead of typing name@company.com from a glossy card, you upload a photo and copy the recognized lines into your system of record.
The tool respects networking privacy: cards often include mobile numbers and personal emails — local OCR avoids shipping those images to a cloud OCR vendor by default.
What you typically extract
| Field | OCR tips |
|---|---|
| Full name | Largest type; usually most accurate |
| Job title | Smaller font — verify spelling |
| Company | Watch for l vs I confusion |
Critical — confirm @ and domain TLD |
|
| Phone | Check country codes and extensions |
| Website | May omit https:// — add when saving |
| Address | Multi-line; paste as one block then split |
Photography checklist
- Parallel — camera plane parallel to card reduces keystone distortion.
- Fill frame — card should occupy most of the image height.
- No flash blast — matte cards and angled light reduce hotspots on lamination.
- Both sides — scan separately if phone numbers are on the reverse.
- Stacked cards — photograph one card only; edges of other cards confuse OCR.
Workflow ideas
- CRM paste — copy block into HubSpot or Salesforce quick-create forms.
- Spreadsheet row — one paste per column after split in Sheets/Excel.
- Follow-up email — quote title and company accurately in your intro line.
- Team handoff — share text in Slack instead of a blurry photo.
Segmentation note
Business cards pack multiple lines into a small area. This variant uses OCR page segmentation suited to a single dense block of text, which often outperforms generic full-screen screenshot modes for card-sized crops.
Limitations
- Fancy fonts, embossed lettering, and metal cards may fail.
- Handwritten mobile numbers on cards need Handwriting OCR.
- No automatic duplicate detection against your existing contacts.
Privacy
Treat card photos like PII. Process on your own device, delete photos when no longer needed, and comply with your company’s data retention policy for leads.
Related tools
- Image to Text — larger documents or screen captures.
- Handwriting OCR — notes written on the back of cards.
- OCR Tools hub — all OCR entry points.