New product gives organizations a governed path to using AI with sensitive data, with full data sovereignty, compliance coverage, and integration into the ARMOR data security intelligence platform

Seclore has launched ARMOR AI DLP to help organizations use AI tools without exposing sensitive business information during daily operations. The announcement comes as companies continue increasing the use of tools like ChatGPT, Claude, and Gemini across departments and internal workflows. Many security and compliance teams are now trying to keep pace as employees connect AI services to customer records, internal systems, financial information, and operational data.

For enterprise security leaders, the bigger issue is no longer whether AI adoption will happen. The bigger concern is how organizations maintain oversight once sensitive information starts moving through external AI platforms and connected workflows.

What Happened

Seclore introduced ARMOR AI DLP as part of its broader ARMOR security platform.

According to the company, the platform is designed to protect sensitive information while users’ enterprise applications and AI systems exchange information in real time.

Before information reaches external AI systems, the platform masks sensitive business data using protected tokenized values. AI systems can still process requests and generate responses without directly viewing original business information.

When the response returns, the original values are restored inside the enterprise environment.

The company released two versions of the product:

  • ARMOR AI DLP Portal for employee access to public AI tools with centralized governance and logging
  • ARMOR AI DLP API for embedding protection controls into enterprise applications, AI workflows, and retrieval environments

The platform supports both cloud and on-premises deployments and includes controls designed for regulated industries and sovereign data environments.

According to Seclore, the platform aligns with several compliance requirements, including:

  • GDPR
  • HIPAA
  • India DPDP Act 2023
  • Saudi PDPL
  • UAE data protection regulations
  • CCPA and CPRA

Seclore also stated that existing customers using ARMOR DSPM, ARMOR DAC, and ARMOR EDRM can extend current policy controls into AI environments without major operational changes.

Why This Matters

AI adoption inside enterprise environments is moving quickly, and many governance programs are struggling to keep up.

Employees are already using AI assistants, public AI platforms, autonomous workflows, and connected AI applications during everyday business activity. At the same time, organizations are building internal AI systems connected to customer information, financial systems, healthcare data, and operational platforms.

That creates a very different security challenge compared to older enterprise environments.

Traditional DLP platforms were originally designed around email endpoints, file transfers, and controlled applications. AI environments behave differently because information can move continuously between prompts, APIs, external services, and automated workflows.

As more businesses expand AI usage, security teams are paying closer attention to concerns such as:

  • Sensitive information exposure
  • Regulatory compliance
  • Data residency requirements
  • External AI access
  • Prompt visibility
  • Oversight across AI workflows

The issue becomes even more important in industries where organizations must maintain tighter control over how information is processed, stored, and shared.

That reality is beginning to shape enterprise buying decisions.

Most organizations do not want to block AI usage completely. Instead, they are trying to find practical ways to support AI adoption while still maintaining operational oversight and compliance visibility.

Who Should Care

  • CISOs
  • Data Protection Teams
  • Compliance Leaders
  • AI Governance Teams
  • Security Operations Teams
  • Cloud Security Teams
  • Enterprise Architecture Teams

Impact on Buyers

This launch reflects several broader shifts taking place across enterprise AI security markets.

1. Enterprise Data Protection Is Evolving

Organizations are starting to realize that AI environments create new ways for sensitive information to move across business systems.

That is increasing interest in security platforms designed to protect information while AI interactions are actively happening, instead of reviewing activity later.

2. Visibility Across AI Usage Remains Limited

Many enterprises still do not have centralized oversight into how employees use external AI services, AI agents, and connected AI tools inside operational environments.

Because of that, organizations are paying more attention to areas such as:

  • AI governance
  • Real-time data protection
  • AI interaction visibility
  • Prompt level controls
  • Data residency management
  • Runtime policy enforcement
  • Compliance tracking

3. Buyers Want Security That Fits Existing Workflows

Most organizations are not looking to slow AI adoption. Instead, they want security controls that fit naturally into existing workflows without disrupting employees or requiring major infrastructure redesigns.

Ease of deployment, operational simplicity, and compatibility with existing environments are becoming important factors during buying decisions.

Demand Signal

The launch of ARMOR AI DLP reflects rising demand across AI governance and enterprise data protection markets.

Many businesses are looking for solutions to preserve visibility, compliance, and operational control without reducing productivity as they continue to increase the use of AI.

That is increasing interest in technologies connected to:

  • AI data protection
  • AI governance
  • Prompt security
  • Data sovereignty management
  • Runtime AI controls
  • AI workflow visibility
  • Enterprise AI compliance

The conversation inside the market is also shifting.

Organizations are no longer focused only on identifying AI-related risks after deployment. Many now want protection controls that work during live AI interactions as activity happens.

  • AI Governance
  • Enterprise AI Security
  • Data Sovereignty
  • Runtime AI Protection
  • Prompt Security
  • AI Compliance Management
  • Data Security Intelligence

What Security Leaders Should Do

Security and compliance teams should review how much visibility currently exists across AI usage inside enterprise environments.

In many organizations, AI adoption expanded across departments faster than governance programs could adapt. External AI services, plugins, datasets, and automated workflows may already exist across operational environments without centralized oversight.

Organizations should also review whether existing DLP systems can properly monitor AI interactions with external AI tools, autonomous workflows, and cloud-based AI environments.

As AI-driven operations continue expanding, older security models built around static applications and traditional endpoints may provide limited visibility into real-time AI activity.

Security leaders should work more closely with legal compliance, engineering, and business teams so AI governance becomes part of operational planning instead of only becoming a policy discussion after deployment.

The bigger challenge ahead may not be AI adoption itself.

The real challenge is maintaining visibility, control, and compliance as AI systems become more deeply connected to enterprise operations.

CyberTech Intelligence POV

At CyberTech Intelligence, this launch reflects how quickly AI governance is becoming part of mainstream enterprise security planning.

Organizations increasingly understand that AI adoption introduces operational and data protection challenges that older security architectures were never designed to handle.

That becomes even more important as autonomous AI systems, retrieval environments, and AI-powered workflows continue expanding across enterprise operations.

The platforms attracting the most attention right now are generally the ones helping organizations apply governance controls directly inside AI interactions while keeping operations efficient and manageable.

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Learn how integrated video security, access control, and real-time alerts may increase visibility while decreasing operational complexity. 

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Source – prnewswire 

Brand Covered- Seclore, ChatGPT, Claude, and Gemini

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