Seclore Launches ARMOR DSPM to Secure the Data Behind AI

Mumbai, June 11: Seclore, the Data Security Intelligence company, today announced the general availability of ARMOR DSPM, a new capability within the ARMOR platform designed to help organizations discover, understand, and protect sensitive data across enterprise and AI environments.

As enterprises accelerate AI adoption, security leaders face a growing challenge: understanding what sensitive data exists across the organization, where it resides, who has access to it, and whether it is adequately protected before it is consumed by AI systems. Without that visibility, organizations risk exposing intellectual property, regulated information, and other business-critical data.

While many Data Security Posture Management (DSPM) solutions focus primarily on discovering sensitive data, organizations often struggle to determine which findings pose the greatest risk, how those risks impact the business, and what actions should be taken next. ARMOR DSPM was built to address this gap by combining data discovery with contextual intelligence and remediation-driven outcomes.

At the core of ARMOR DSPM is Seclore’s Semantic Triad approach, which evaluates data through three dimensions: Content, Context, and Intent. Rather than relying solely on pattern matching or predefined rules, ARMOR DSPM seeks to understand what the data is, why it matters to the business, and how it is intended to be used. Unlike regex and pattern-matching DSPMs that simply see a string of characters, ARMOR DSPM understands what the data means to the business. That context cuts the false positives that erode analyst trust and lets security teams prioritize the exposures that pose real business risk. This enables organizations to more accurately identify sensitive assets such as intellectual property, source code, trade secrets, regulated records, and data used by AI systems.

ARMOR DSPM begins discovery and classification as soon as repositories are connected, helping organizations gain visibility into sensitive data without lengthy model training, extensive tuning cycles, or manual rule creation. The solution automatically prioritizes findings based on business risk, enabling security teams to focus on the exposures that matter most.

“Every organization is racing to put AI to work on its data. What they’ll learn quickly is that an AI agent is only as safe as the context around the data it touches,” said Dr. Vishal Gauri, CEO of Seclore. “We built ARMOR DSPM to define that context, ownership, and intent at the source. That is what turns DSPM into the foundation for agentic AI adoption, where data governs how it can be used no matter who – human or agent – picks it up.”

Designed to support AI-ready security programs, ARMOR DSPM helps organizations identify and classify sensitive data before it is accessed by AI applications, copilots, agents, and enterprise AI workflows. By providing a clearer understanding of data risk and ownership, it enables organizations to strengthen governance while accelerating responsible AI adoption.

ARMOR DSPM is also designed to move organizations beyond discovery to action. Findings can be integrated into existing security, privacy, and compliance workflows or extended into the broader ARMOR platform, where data intelligence can drive automated classification, protection, monitoring, and audit readiness. This helps organizations ensure that sensitive data remains protected throughout its lifecycle, regardless of where it is stored, shared, or used.

The solution runs within a dedicated cloud environment, with no external API calls, no data passed to third-party LLMs, and no sensitive data retained. ARMOR DSPM is currently deployable on AWS and GCP, with more hyperscalers on the roadmap, supporting organizations operating under data sovereignty and data localization mandates across 34+ countries.

The launch of ARMOR DSPM further advances Seclore’s vision of Data Security Intelligence, helping organizations gain continuous visibility into their sensitive data, understand associated risks, and take informed action as information moves across users, applications, cloud platforms, and AI systems.