EnforceAuth Launches First AI-Native Security Fabric to Govern Autonomous Software Decisions

New Platform Addresses Critical Authorization Gap for AI Agents and Automated Workflows; Opens Free Enterprise Waitlist for Early Adopters

EnforceAuth launched its AI Security Fabric, the first authorization platform purpose-built to govern decisions made by AI agents, automated workflows, and machine identities in real time. The company is now accepting enterprise organizations onto a waitlist for production access.

Enterprise security faces a structural problem: AI systems and autonomous software are making thousands of consequential decisions per second, accessing customer data, executing transactions, modifying infrastructure, yet operate outside the policy controls designed for human users. Traditional Identity and Access Management (IAM) answers “who can log in?” but cannot evaluate “should this AI agent access this customer’s financial records to complete this specific workflow right now?”

Modern security failures increasingly involve permitted actions, not unauthorized access.”

— Mark Rogge

“The next generation of incidents won’t come from bad authentication, but from uncontrolled decisions made by authorized systems,” said Mark Rogge, Founder & CEO of EnforceAuth. “Security must shift from asking ‘who is allowed in?’ to ‘is this specific action allowed, right now?’ Our platform is built for that exact question in the age of AI autonomy.”

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The EnforceAuth AI Security Fabric delivers:

Decision-Centric Authorization Architecture

Every action, whether initiated by a human, AI agent, or automated system, is evaluated as a discrete authorization decision with full context: actor identity, delegation chain, resource sensitivity, operational conditions, and business policy. This model extends authorization beyond static role assignments to dynamic, contextual enforcement.

Native Support for Non-Human Autonomy

Purpose-built for environments where software operates independently. Handles delegation chains, scoped authority, ephemeral permissions, cross-system workflows, and auditable machine decision-making without retrofitting human-centric models.

Enterprise-Grade Policy Enforcement

Founded by the team that defined policy-as-code and enterprise authorization standards, EnforceAuth provides unified policy management across applications, infrastructure, data platforms, and AI workloads with real-time enforcement and complete audit trails.

The platform addresses escalating pressure from regulators, boards, and audit committees as organizations deploy AI agents that access sensitive data and execute business processes. EnforceAuth provides the authorization layer required to govern AI autonomy with the same rigor applied to human access.

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