DataSieve: Text to Data
Extract emails, dates, and URLs instantly and privately
128 followers
Extract emails, dates, and URLs instantly and privately
128 followers
DataSieve extracts structured data from text, files and archives instantly and privately. Find emails, dates, URLs, and more, all offline on your device. Supports JSON, HTML, Excel, Word, PDF, EPUB, ZIP, and other formats. Fast, accurate, and private.
This is the 2nd launch from DataSieve: Text to Data. View more
DataSieve 2.0
Launching today
DataSieve helps you turn unstructured text into clean, usable data in seconds.
Drop in text, files, folders, or even archives, and extract what you need in one pass. Emails, phone numbers, URLs, dates, financial data, and more. Everything runs locally on your device, with no cloud and no tracking.
What you can do
- Extract multiple data types at once
- Process text, PDFs, EPUBs, CSV, JSON, Word files, and more
- Export results to JSON, XLSX, DOCX, and more
- Define your own custom extractors
Free Options
Launch Team
Vologram Messages—Amaze, Engage, Connect
Vologram Messages—Amaze, Engage, Connect
@jonathan_alonso That's not supported yet. I'm planning to support extracting data from images in the next major release, and that will cover also images inside PDFs.
Vologram Messages—Amaze, Engage, Connect
@alberto_polini You can define custom ones using regexes!
Nice — structured data extraction is one of those problems that sounds simple until you actually try it. How does it handle ambiguous fields? For example, does it distinguish between a phone number and a fax number in unstructured text? Asking because I work on a similar challenge with voice-to-form mapping.
Vologram Messages—Amaze, Engage, Connect
@webappski as of now, the app doesn't distinguish between phone numbers and fax numbers. Structured data extraction is not easy indeed!