Concentric AI vs. Microsoft Purview

Broad coverage and support across cloud and on-premises environments

Context-aware AI discovers and categorizes structured and unstructured data; each unstructured data record is scanned in its entirety and  with high accuracy for detecting PII/PCI/PHI, IP and other business-critical data

Supports Microsoft MIP labels, Google labels, custom metadata labels, retention labels to implement and enforce data retention policies

Uses data context to dynamically monitor and protect data across multiple GenAI use cases including GenAI assistants such as Copilot, public GenAI, and proprietary GenAI workloads

Users can set and enforce data retention policies, (e.g., review, archive, or delete) directly in the platform to ensure regulatory compliance

Identifies duplicate and near duplicate data, which can be deleted or archived within the platform

Discovers data being shared externally; remediation policies can be created

Provides complete visibility into a data record’s life cycle, including origin, transformations, flow, and usage across the organization

Automated remediation actions performed natively in the platform, including classification/labeling, moving/deleting/copying data, or defining permissions

Multiple tiers of managed services available that can include implementation, training, classification, deduplication, policy creation, reporting, and more

Limited support for non-Microsoft environments

Relies on pattern-based discovery or trainable classifiers that require hundreds of document samples

Can only apply MIP labels and only to data that resides within the Microsoft environment

Requires MS365 E5 or MS365 E5 Compliance subscription; different processes required to protect Mac vs. PC; cannot mask sensitive text in prompts

Can only delete data once defined retention schedule is over

Cannot detect duplicates or near duplicates

Does not autonomously remediate external file sharing

Does not support context-aware lineage tracking for unstructured data

Falls short in applying classification labels and does not offer permission or entitlement remediation. Lacks automated data management functions

Lacks dedicated customer success support, which may result in a much less customized experience and self-service approach