Extract email addresses from any text. Paste, click, copy. No signup, no uploads.
🔒 Runs 100% in your browser — your data never leaves your deviceEmail extraction is a useful skill for many everyday tasks where you have permission to use the email addresses you're working with. Here are the common legitimate uses:
Pull email addresses from your own messy spreadsheet, CRM export, or address book to deduplicate and organize.
Moving from one CRM, email service, or contact manager to another — extract addresses to import to the new system.
Pull sender/recipient addresses from a forwarded email thread or bulk-forwarded support tickets you own.
Extract contact info from invoices, contracts, or business documents you own for filing and reference.
Pull example email addresses from log files, source code, or API responses for debugging.
Analyze patterns in publicly published academic papers, your own survey responses, or your own customer feedback.
This tool uses a regular expression — a pattern-matching language — to find text that looks like an email address. The pattern is the standard one used in most legitimate email validation:
[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}Translated to English, this matches:
@ symbol.com, .org, .io)This pattern handles ~99% of real-world email addresses. It deliberately does not match invalid formats like user@domain (no TLD), user @ domain.com (spaces), or @domain.com (no local part).
If you have a text file and Terminal access, this one-line command extracts all emails:
grep -Eio '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}' file.txt | sort -uThe flags: -E enables extended regex, -i makes it case-insensitive, -o prints only matches. sort -u deduplicates.
For a spreadsheet column with text containing emails, use this formula:
=TRIM(MID(SUBSTITUTE(MID(A1,FIND("@",A1)-50,100)," ",REPT(" ",100)),
FIND("@",MID(A1,FIND("@",A1)-50,100))+50-100,100))Or use Excel's Power Query: select your column → Transform → Extract → Text Between Delimiters, with custom regex matching.
import re
emails = re.findall(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}', text)
unique_emails = sorted(set(email.lower() for email in emails))Just paste and click. Use this method when you don't want to write code or formulas.
Yes, completely. No signup, no email required, no usage limits. The tool runs in your browser — no data is sent to our servers. We make no money on this page (no ads, no tracking, no upsells).
No. The extraction happens entirely in your browser using JavaScript. Your text never leaves your device. You can verify this by disconnecting from the internet after the page loads — the tool will still work.
Cleaning your own contact list, parsing email addresses from documents you own, extracting addresses from forwarded emails or support tickets, organizing your address book, migrating contact data between systems. Always have permission to use the addresses you extract.
Extracting publicly visible emails for personal organization is generally permitted in most jurisdictions. Sending unsolicited bulk email to scraped addresses violates anti-spam laws including CAN-SPAM (US), GDPR (EU), CASL (Canada), PECR (UK), and similar laws worldwide. The act of extraction is rarely illegal; the act of spamming is.
Any text you can paste — text files, Word documents, PDFs, web pages, source code, CSV files, emails. For files, open them and copy-paste the text content. For PDFs that won't copy text, you may need OCR first.
Yes, by default. The "Remove duplicates" option is enabled out of the box. Email matching is case-insensitive — Alice@Example.com and alice@example.com are treated as the same address.
The tool uses a regular expression that matches the standard email address format. It correctly identifies most common email patterns and ignores partial matches like someone @ example or malformed strings. False positives are rare; some unusual but valid addresses (with quoted local parts) may be missed.
Yes. Open the file in Excel or Google Sheets, copy the relevant cells, and paste into the extractor. For very large files (50,000+ rows), consider Python or grep instead — the browser tool can slow down with very large inputs.
The tool handles up to about 5 MB of text comfortably. For larger amounts, processing may take a few seconds. There's no hard limit, but very large pastes can slow your browser.
Last updated: April 25, 2026. This tool and page are provided free by Softlookup as a utility for legitimate email extraction tasks. We do not condone or support unsolicited bulk email or spam.