Is my data sent to the cloud when using DataSieve?

No, all data processing is performed locally on your device, with no data sent to the cloud, ensuring privacy and security.

What file formats does DataSieve support for input?

DataSieve supports text, PDF, EPUB, CSV, JSON, Word files (DOCX), and various archives like ZIP, among others.

Can I create custom data extraction patterns in DataSieve?

Yes, you can define and save your own custom extractors to extract specific data types tailored to your needs.

On which platforms is DataSieve available?

DataSieve is available on iPhone, iPad, and Mac, as indicated in the product information.

How does DataSieve handle privacy and data security?

It runs entirely locally with no cloud processing, and only collects non-identifiable diagnostic data as per the privacy policy.

DataSieve 2.0

Extract structured data from text, files and archives.

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What is DataSieve 2.0

DataSieve 2.0 is an application designed to extract structured data from unstructured text, files, and archives, transforming it into clean, usable data within seconds. It supports various input formats including text, PDFs, EPUBs, CSV, JSON, and Word files, allowing users to extract multiple data types like emails, phone numbers, URLs, and dates in a single scan. All processing is done locally on the device, ensuring privacy with no cloud dependency or tracking.

Key Features

Extract multiple data types simultaneously (e.g., emails, phone numbers, URLs, dates)

Support for various input formats including PDF, EPUB, CSV, JSON, Word files, and archives

Local processing with no cloud or tracking for enhanced privacy

Define and save custom extractors for personalized data patterns

Drag and drop functionality for files and folders for easy use

Use Cases

Developers extracting data from logs, code comments, or configuration files for analysis
Analysts cleaning and organizing data from reports, documents, or spreadsheets to streamline workflows
Researchers pulling key information from academic papers, datasets, or text sources for insights
Writers gathering contact details, references, or dates from large text files for content creation
Startups processing customer feedback or documents to quickly extract actionable data for decision-making

Why do startups need this tool?

Startups often deal with large volumes of unstructured data from sources like customer feedback, documents, and files, requiring quick extraction of key insights to drive decisions. DataSieve enables them to efficiently extract emails, dates, URLs, and other data types, saving time and reducing manual effort. Additionally, its local processing ensures data privacy and security, which is critical for startups handling sensitive information without relying on external cloud services.