Use the free Regex Data Extractor below: your data never leaves your browser — all work happens on your device, and nothing is uploaded to any server.
Long text hides useful details. A support thread may hold three email addresses, a contract may bury five dates, and a copied chat log may mix prices, phone numbers, and links in one wall of text. Reading it all by eye is slow, and copying items one by one invites mistakes. The Regex Data Extractor scans pasted text in one pass with built-in regular expressions and pulls out emails, URLs, dates, and numbers into tidy groups.
Regular expressions, often called regex, are patterns that describe the shape of text. An email pattern looks for characters, then an @ sign, then a domain. A date pattern looks for four digits, a dash, two digits, a dash, and two digits. The tool runs four of these patterns at once, so one paste returns four kinds of findings. You do not need to learn regex syntax to use it, and you do not need to install anything or upload your text.
To use it, paste any text into the box. The sample shows the expected mix: sentences that contain emails, a link, a date, and plain numbers. Tick the kinds of data you want, and leave the rest off if you only need one kind. The duplicate option is on by default, which keeps each found item once. Switch it off when you want to count how often an item appears, for example how many times one email address shows up in a thread.
The results appear grouped by kind, each with a count. Emails come first, then URLs, then dates, then numbers, in the order you ticked them. Press Download results to save the grouped list as a text file. That file is easy to paste into a spreadsheet or a ticket, and it keeps the groups separate so you do not have to sort them again by hand.
Every pattern has honest limits, and knowing them saves confusion. The email pattern finds common addresses, but it will also match a mistyped address that merely looks like one, and it will miss unusual addresses with rare characters. The date pattern finds ISO dates like 2025-03-14 and slash dates like 05/03/2024, but it cannot tell whether 05/03 means May 3 or March 5. The number pattern finds whole numbers and decimals, but it also finds the parts of dates, so a date like 2025-03-14 also appears as numbers. That overlap is expected when patterns run independently.
Privacy deserves a note here. Pasted text often contains other people’s contact details, and this tool is designed so that text never leaves your browser. Nothing is uploaded, nothing is stored, and closing the page clears the paste from view. Even so, treat extracted emails with care: collecting addresses from text you do not own can break privacy rules and spam laws. Use the tool for your own records, your own tickets, and text you have a right to process.
People use this extractor to pull contact details from their own notes, to gather links from a long document, to list the dates mentioned in meeting notes, and to collect figures from a report for checking. It is a first pass, not a final audit. After extraction, check the items that matter before you act on them, because a pattern match is a strong hint, not a verified fact.
How to extract data with regex
- Paste your text into the box.
- Tick the data kinds you want: emails, URLs, dates, numbers.
- Leave duplicate removal on for a clean list, or off to count repeats.
- Press Extract data and check the grouped results and counts.
- Press Download results to save the list.
Frequently asked questions
Do I need to know regex? No. The patterns are built in. You only paste text and tick boxes.
Why does a date also appear as numbers? The patterns run independently, so date digits match the number pattern too. Turn numbers off when you only want dates.
Does it verify that an email is real? No. It checks the shape of the address, not whether the mailbox exists.
Is my pasted text uploaded? No. Everything runs in your browser, and nothing is sent or stored.
Use the extractor as a fast first pass over messy text. It finds the structured items in seconds, and your own judgment turns those items into a clean list you can trust.