Mage Data

Secure enterprise sensitive data and automate compliance across production, testing, and AI pipelines with unified discovery, masking, and guardrail controls.

data provision

About Mage Data

Mage Data is an enterprise data security and privacy platform designed to automate data discovery, masking, test data management, and compliance across hybrid and multi-cloud environments. The platform acts as a unified data security fabric, identifying sensitive elements across databases, file storage, endpoints, and cloud infrastructure, while applying consistent security policies to protect critical data throughout its entire lifecycle. The system operates via a single policy engine, allowing organizations to configure protection rules once and enforce them across production databases, testing environments, and AI pipelines. In production settings, it delivers role-based dynamic data masking at query time without requiring proxies, accompanied by real-time database activity monitoring and database firewalls. For software delivery, it facilitates test data management through context-preserving static masking, synthetic data generation, intelligent subsetting, and database virtualization to deliver rapid, secure database clones for CI/CD workflows. In addition to traditional database security, Mage Data provides dedicated data security and privacy guardrails for artificial intelligence. It inspects prompts and file uploads in under 100 milliseconds to mask sensitive records before they reach public large language models, monitors AI interactions to detect Shadow AI, and anonymizes training datasets prior to model training. Pre-configured compliance templates help automate adherence to global regulations such as GDPR, HIPAA, PCI DSS, DPDP, and CPRA. The platform is tailored for security engineers, database administrators, compliance officers, and DevOps teams within highly regulated sectors such as banking, insurance, healthcare, government, and retail. Unlike modular security stacks assembled through disparate vendor acquisitions, Mage Data provides a natively built, integrated architecture accessible through a conversational interface, ensuring minimal configuration overhead and rapid deployment across over 100 enterprise integrations.

Mage Data pros & cons

Pros

Native unified platform avoids the integration friction of stitched-together security tools.
Fast sub-100ms inspection allows real-time prompt masking without disrupting AI workflows.
Broad compatibility supporting over 28 connectors and 100+ datastore integrations including Oracle, SAP, Snowflake, and BigQuery.
Reduces test environment storage footprints by up to 90% via database virtualization and subsetting.

Cons

Public pricing details are not disclosed and require scheduling a direct sales consultation.
Comprehensive enterprise feature set may involve significant configuration for smaller teams without dedicated security personnel.

Mage Data use cases

DevOps and QA teams can automatically provision masked, virtualized test datasets into CI/CD pipelines within minutes while retaining referential integrity.
Data privacy and compliance officers can streamline audits and ensure compliance with GDPR, HIPAA, or DPDP using pre-built automated regulatory workflows.
Enterprise AI and security leads can deploy guardrails to prevent proprietary data or PII from being leaked into public LLM prompts and model training datasets.
Database administrators can protect production data by applying zero-proxy dynamic masking, database activity monitoring, and automated query firewalls.

Mage Data features

pre-configured compliance reporting for gdpr, hipaa, pci dss, and 50+ regulations
shadow ai discovery and llm activity auditing
context-aware database firewalls and real-time database activity monitoring
database virtualization and intelligent subsetting preserving referential integrity
static data masking and synthetic data generation for testing
zero-proxy dynamic data masking at query time for production databases
sub-100ms prompt inspection and masking guardrails for llms and ai
ai-powered sensitive data discovery and cataloging with lineage tracking

Mage Data FAQs

What is Mage Data and what core security problems does it solve?

Mage Data is a unified data security platform that automates sensitive data discovery, classification, test data management, production database defense, and AI privacy governance. It eliminates data exposure risks across production, non-production, and AI environments under a single policy engine.

How does Mage Data secure data used in artificial intelligence and LLMs?

The platform provides AI usage guardrails that inspect and mask sensitive data in prompts and uploads with sub-100ms latency without outright blocking users. It also secures training datasets, monitors interactions to uncover Shadow AI, and enforces response controls for copilots and internal agents.

Does Mage Data require proxy architectures for dynamic data masking?

No, Mage Data enforces role-based dynamic masking and redaction directly at query time without using proxy layers, protecting live production databases without introducing proxy-related performance latency.

Which regulatory compliance standards does Mage Data support?

It provides out-of-the-box policies and automated reporting for more than 50 global privacy regulations, including GDPR, HIPAA, PCI DSS, DPDP, CPRA, PIPEDA, PDPA, and IRDAI.

How does Mage Data facilitate Test Data Management (TDM)?

It provides database virtualization, intelligent data subsetting while maintaining referential integrity, and static data masking to generate secure, compliant test environments in minutes while decreasing storage consumption by up to 90%.

Ratings & reviews

No reviews yet. Be the first to share how Mage Data worked for you.