Primary Access Control

Primary Access Control is a policy enforcement platform that governs how human users and autonomous AI agents interact with enterprise data. It enables organizations to define and enforce granular, attribute-based access control policies across workspaces, applications, and lateral agent-to-agent communication channels. Core capabilities include: - Workspace-level enforcement: Policies govern how human users and autonomous agents read, write, move, copy, and share data, regardless of application, device, or location. - East-west enforcement: Controls lateral communication between AI agents, applications, data sources, and enterprise systems. - Application-level enforcement: Extends attribute-based policies to new or thick applications by incorporating Policy Information Point (PIP) and Policy Enforcement Point (PEP) touchpoints. - Data masking and tokenization: Sensitive information can be automatically masked, tokenized, or restricted based on the identity and context of the requesting actor. - Real-time access revocation: Access can be revoked dynamically as user, agent, or threat conditions change. - Automatic encryption: Sensitive data is encrypted automatically based on policy. - Dynamic policy management: Administrators create and modify policies through the Primary Management Console to govern employees, applications, copilots, and autonomous agents across roles, functions, and contexts. - Continuous contextual evaluation: Policies continuously evaluate identity, context, behavior, and risk to adapt in real time. The platform is designed to govern both human and non-human (agentic) identities, addressing the access control challenges introduced by autonomous AI agents operating within enterprise environments.