#Japan #Tokyo #Sourcenext #AI Data Masking #Privacy Software

Protect Your Confidential Information with Ikinari AI Data Masking

In an age where data breaches and privacy concerns are rampant, the need for effective data protection solutions has never been more urgent. To address this challenge, SourceNext Corporation has unveiled its latest software, _Ikinari AI Data Masking_, set to launch on May 26 (Tuesday). This innovative product, priced at ¥4,950 (including tax) for a downloadable version, provides users with the ability to mask sensitive information in PDF and text files seamlessly.

What is Ikinari AI Data Masking?

_Ikinari AI Data Masking_ serves as a robust tool for removing or redacting personal and confidential information from digital documents. Unlike traditional methods that merely delete sensitive data, this software offers a more sophisticated option by replacing real names, addresses, or other identifiable details with placeholders (e.g., “Person A” or “Address B”). This feature ensures that when generative AI accesses these documents, it maintains context while also safeguarding personal information.

Key Features of Ikinari AI Data Masking

• - Flexible Masking Options: Users can choose from several methods for masking information, including automatic detection based on categories, keyword registration, and manual masking. This versatility allows for tailored solutions to meet specific user needs.

• - Automatic Detection: The software supports the automatic detection of various types of personal information such as names, addresses, phone numbers, email addresses, credit card numbers, My Number (Japanese ID number), and driver's license numbers. While comprehensive, it’s important to note that it may not identify every piece of sensitive information.

• - Custom Keyword Detection: Users have the ability to define custom keywords, including company names or project titles, for batch deletion or replacement. The intuitive drag-and-drop functionality for word registration simplifies this process, allowing users to efficiently manage their data.

• - Masking Functionality: If any keyword is incorrectly masked, users can easily click on the affected area to lift the masking, ensuring that necessary information remains accessible.

• - Group Deletion via Dragging: For those needing to remove large portions of text or entire tables, the software's drag-and-drop feature facilitates straightforward and intuitive grouping for deletion.

• - Complete Removal of Embedded Text: Many PDF files contain hidden text data, which can lead to unauthorized access to sensitive information by AI, even after redaction. Ikinari AI Data Masking goes a step further by ensuring that such hidden data is completely removed, offering users peace of mind.

• - Batch Processing: This application allows for the efficient management of multiple files, letting users drag and drop several PDFs or text documents for speedy batch processing, while still ensuring unique attention to each file.

• - Offline Functionality: Operating entirely offline, this software ensures that confidential data remains secure without the risk of leaking to the internet, enhancing overall security.

Product Information

• - Product Name: Ikinari AI Data Masking
• - Price: ¥4,950 (tax included)
• - Developer and Support: SourceNext Corporation
• - Supports: Windows 11 / 10, MacOS Sonoma (v14.0) and above.
• - Installation size: Approximately 200MB
• - Licensing: Allows installation on up to three devices without differentiating between Windows and Mac platforms.

Copyright Notice

• - © SOURCE NEXT CORPORATION

Customer Support

For inquiries regarding purchasing or product information, please reach out to the SourceNext Customer Center via the following link: Support Page.

As privacy legislation becomes increasingly stringent across the globe, tools like Ikinari AI Data Masking will be essential for businesses and individuals striving to protect their sensitive information effectively. The launch of this software marks a significant step towards enhancing data privacy in our digital interactions.