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
Hey everyone,
I’m the developer behind DataSieve (previously TextMine). This update has been a big step forward compared to the first version.
The main focus for 2.x was flexibility and scale. Being able to scan folders and archives, and define custom extractors, makes it much more useful for real workflows instead of just one-off text inputs.
I also spent time improving extraction accuracy for more complex data types like financial info and international formats.
Happy to answer any questions, and I’d really appreciate any feedback, especially around usability and edge cases.
Does it work on external websites? For example, I need to extract the names of all geographical objects mentioned across several websites. Can your system do that?
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.
Hi Alberto, I like your idea of running everything locally. Is the list of attributes to extract static, or can I define custom ones?
About DataSieve 2.0 on Product Hunt
“Extract structured data from text, files and archives.”
DataSieve 2.0 launched on Product Hunt on March 23rd, 2026 and earned 129 upvotes and 9 comments, placing #9 on the daily leaderboard. 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
DataSieve 2.0 was featured in Productivity (649.8k followers), Data (2.3k followers) and Data Science (3.8k followers) on Product Hunt. Together, these topics include over 128.6k products, making this a competitive space to launch in.
Who hunted DataSieve 2.0?
DataSieve 2.0 was hunted by Alberto Malagoli. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how DataSieve 2.0 stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Alberto Malagoli