Seclore, Glean announce context-aware data security integration

By Atlas Watchline Staff · Corporate · August 27, 2026

Seclore said it has integrated its ARMOR DSPM product with Glean to classify sensitive files and apply persistent controls for regulated organizations.

Seclore said on Aug. 27, 2026, that it is integrating its ARMOR DSPM product with Glean to give regulated organizations context-aware data-sensitivity classification and remediation controls.

The company said the integration is aimed at customers in financial services, healthcare, legal services and government or public-sector organizations. Seclore said the setup is designed to help teams identify sensitive information faster and apply controls that stay with the file.

ARMOR DSPM analyzes document content and metadata to assign a sensitivity level, information type and exposure risk based on the file’s actual content, according to the release. Seclore said that classification can map to frameworks including GDPR, HIPAA and India’s DPDP law.

The release said the system also embeds labels directly into source files so they remain readable by Glean. Seclore said its remediation tools include native EDRM, or enterprise digital rights management, with persistent file-level encryption and usage controls, plus access controls over opening, sharing or modifying data based on confidentiality level and context.

Seclore said the integration is available now for organizations using ARMOR DSPM and Glean.

Seclore CEO Dr. Vishal Gauri said the integration gives Glean customers sensitivity classification across indexed domains, EDRM-based protection that follows the file and a compliance posture that can be defended. Glean VP of Partnerships Zubin Irani said regulated sectors want faster AI adoption and more reassurance about how sensitive information is handled.

Glean is described in the release as an enterprise AI platform. Seclore described itself as a company specializing in enterprise data security intelligence.

Sources

• PR Newswire release

Editorial note: This article was prepared with AI assistance and includes source attribution for reader review.

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