Unstructured Data Security
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Unstructured Data Security
Additional Info
| Company | Mage Data |
| Website | magedata.ai |
| Company size (employees) | 50 to 99 |
| Headquarters Region | North America |
Overview
Mage is an innovative data security platform designed to safeguard both structured and unstructured data across diverse enterprise landscapes. With a comprehensive suite of patented solutions, including data discovery, classification, and masking, Mage ensures robust security and regulatory compliance. Leveraging a zero-trust, no-code approach, it empowers organizations to mitigate risks and confidently share data. Purpose-built for large enterprise implementations, Mage seamlessly integrates with existing IT infrastructure, providing a holistic solution to address data security challenges. Recognized for its tailored architecture and ability to reduce sensitive data risk by up to 95%, Mage is a leader in enterprise-wide data protection.
Key Capabilities / Features
With robust support for various file types including text files, PDFs, Docx, and PPT, Mage offers from simple redaction to realistic anonymization methods with consistent masking rules applied across databases and files. It seamlessly integrates with various data sources such as Azure Data Lake Storage, S3, Onedrive, SharePoint, local, or network file stores. Mage's approach to processing, whether streaming or batch, optimizes performance based on file size. Mage's unstructured masking is GenAI ready, facilitating anonymization for interactions with public AI models like chatGPT. It supports custom NLP models for sensitive data identification in unstructured data stores. Its ability to create custom data classifications using pattern-based, repository matching, and NLP-based detection ensures reliable data protection. Consistent masking rules ensure uniformity across structured and unstructured data, guaranteeing data security and compliance across the board.
How we are different
1. Comprehensive Data Security Across Structured and Unstructured Data
Mage stands out by offering a unified approach to securing both structured and unstructured data. Whether it’s data from databases, text files, PDFs, Docx, or PPT files, Mage ensures consistent anonymization using the same rules. This guarantees that data will be masked identically across different data stores, maintaining data integrity and security. The platform integrates seamlessly with various sources like Azure Data Lake Storage (ADLS), OneDrive, SharePoint, AWS-S3 buckets, Azure-BLOB files and local or network file stores.
2. Advanced Natural Language Processing (NLP) Integration
Mage utilizes sophisticated Natural Language Processing (NLP) through open-source software to effectively parse and secure unstructured files. This feature allows Mage to go beyond simple redaction, offering realistic data anonymization. Mage's platform is GenAI ready, enabling the anonymization of sensitive data when interacting with public large language models (LLMs) like ChatGPT. For enterprises looking to train their own LLMs, Mage provides de-identified training data, enhancing privacy and security during the model training process. Additionally, custom NLP models can be integrated to identify and protect sensitive data within unstructured data stores.
3. Customizable and Reliable Data Classification
Mage offers superior data classification capabilities by combining pattern-based detection, repository matching, and NLP-based detection. This hybrid approach makes Mage more reliable than competitors that rely solely on NLP or pattern-based methods. By enabling the creation of custom data classifications, Mage ensures that data security measures are precisely tailored to the unique needs of each enterprise. This customization enhances the accuracy and effectiveness of data protection efforts, making Mage a robust solution for diverse and dynamic data environments.
