Concentric AI was awarded a patent related to its efforts to advance data security. This patent – dubbed “Methods and Systems for Optimizing Grouping for Enhanced Access Control and Risk Mitigation in an Enterprise” – is focused on optimizing user security groups and data access permissions to mitigate risk.
In particular, it protects existing IP for Concentric AI’s Semantic Intelligence data security governance platform. It recognizes how the technology protects sensitive data by optimizing user security groups and mitigating risk for enterprise access governance and security management.
Concentric AI’s invention analyzes existing security groups, user memberships and associated permissions to identify redundant, obsolete or overly permissive groups, potentially generating new security groups without impacting business continuity.
This patent follows the recently announced “Methods and Systems for Identifying Anomalous Users Exhibiting Overreaching Access Permissions to Data Objects,” “Methods and Systems for Clustering Documents based on Semantic Similarity” and “Method and Electronic Device for Managing Sensitive Data based on Semantic Categorization” patents.
“This latest patent – one of five awarded to Concentric AI – addresses a critical data security challenge: managing excessive security groups and permissions,” said Karthik Krishnan, Concentric AI’s founder and CEO. “The unchecked accumulation of security groups and redundant permissions can introduce significant risks. Our patented technology helps organizations streamline access controls, optimize security group configurations and strengthen their overall security posture.”
Concentric AI’s Semantic Intelligence solution provides advanced data security governance by discovering structured and unstructured data, spanning cloud and on-premise repositories. Its proprietary AI understands context—enabling it to detect not only PII, PCI, and PHI, but also intellectual property and critical business documents that do not follow fixed patterns. The solution classifies and tags data automatically, identifying risk from over-permissive access or inappropriate sharing. It can also take action—either autonomously or by working with an existing security stack—to secure data quickly and continuously.
