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What is Metadact?

Metadact is a cutting-edge solution designed to cleanse metadata and mitigate the risk of data loss, specifically tailored to help organizations prevent inadvertent information leaks by removing hidden metadata from an array of documents. It integrates seamlessly with existing email platforms, guaranteeing that all outgoing attachments are automatically stripped of sensitive metadata without disrupting user workflows. Supporting various file types, such as Microsoft Office and PDFs, Metadact ensures comprehensive protection across different document categories. Administrators gain access to a centralized management dashboard that facilitates the enforcement of company-wide policies, the customization of cleaning settings, and the monitoring of usage to maintain compliance and bolster security measures. Additionally, Metadact offers flexible deployment methods, including both on-premises and cloud solutions, accommodating diverse IT infrastructures. With the ability to customize settings, organizations can maintain full command over their data protection strategies while obtaining crucial insights, thereby enhancing both workflow efficiency and security. Moreover, its intuitive design allows teams to remain focused on their responsibilities, eliminating the burden of complicated procedures and promoting a more productive environment. This innovative tool not only safeguards sensitive information but also streamlines operations, making it an invaluable asset for modern organizations.

What is Baffle?

Baffle provides robust data protection solutions designed to uphold privacy and manage data visibility, regardless of where the data comes from or where it is headed. Organizations are grappling with persistent threats from cyberattacks, particularly ransomware, as well as heightened worries about the security and integrity of their data in various environments, including both public and private clouds. As regulations around data management continue to evolve, the approaches to storing, accessing, and analyzing data have undergone significant changes, requiring businesses to adapt quickly. Baffle addresses the inevitability of data breaches by ensuring that even if a breach occurs, unprotected data remains unreachable to attackers. This proactive stance establishes a vital final layer of defense, emphasizing the importance of continuous security from the moment data is created through to its processing. The company's state-of-the-art transparent data security mesh is designed to work seamlessly with both on-premises and cloud-based data, offering multiple protection options. Furthermore, Baffle provides ongoing safeguards as data moves from its source repositories to cloud databases or object storage, enabling organizations to use sensitive information securely without compromising its integrity. This dual focus on prevention and continuous protection positions Baffle as a leader in the fight against data breaches and cyber threats.

Media

Media

Integrations Supported

Microsoft Office 2024
Microsoft Outlook
Microsoft Word

Integrations Supported

Amazon Redshift
Apache Kafka
MariaDB
MySQL
PostgreSQL
SQL Server
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Litera

Date Founded

2001

Company Location

United States

Company Website

www.litera.com/products/metadact

Company Facts

Organization Name

Baffle

Company Location

United States

Company Website

baffle.io

Categories and Features

Data Loss Prevention

Not specified

Legal

Not specified

Categories and Features

Data Loss Prevention

Not specified

Data Security

Not specified

Data Tokenization

Not specified

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