Noma Security vs WorkOS: Choosing the Right Platform for Agentic Security

AI agents are now handling tasks that were unthinkable just two years ago—booking travel, managing customer inquiries, analyzing legal documents, and executing financial transactions. As these autonomous systems gain access to sensitive data and critical business operations, the question isn't whether to secure them, but how.

Two platforms have emerged in this space: Noma Security, a specialized AI security platform focused on agent governance, and WorkOS, a mature identity and access management platform that provides the authentication and authorization foundation for modern applications including AI systems. While they take different approaches to the security challenge, understanding their strengths and trade-offs is essential for teams building agent-driven products.

What Noma Security Offers

Noma Security entered the market as a purpose-built platform for AI security posture management. Their flagship feature, the Agentic Risk Map, provides visibility into AI agent deployments across an organization. The platform monitors LLMs, RAG systems, and autonomous agents throughout their lifecycle, from development to production.

The core offering includes runtime guardrails that attempt to prevent harmful outputs, policy violations, and unauthorized actions. Noma integrates with 80+ AI services and tools, creating a unified dashboard for tracking AI usage patterns. For organizations already committed to a complex AI stack, this centralized visibility addresses a genuine pain point—knowing which models are deployed where, who's using them, and what data they're accessing.

Their Model Context Protocol (MCP) server mapping is particularly relevant for companies using Claude or other LLM systems that rely on tool calling. The platform traces these connections to identify potential attack vectors where agents might access unintended resources.

However, Noma's approach comes with significant limitations. The platform is new—reporting 1,300% ARR growth sounds impressive until you consider the typical trajectory of early-stage products starting from a small base. Their AI-specific guardrails, while comprehensive for LLM outputs, don't address the fundamental access control problem: determining who should authenticate into your system, what they're authorized to do, and how those permissions are managed across your entire application.

Organizations adopting Noma face the reality of maintaining two separate security layers: one for AI-specific threats and another for traditional identity and access management. This duplication creates integration complexity, inconsistent policy enforcement, and expanded attack surfaces. When an AI agent needs to act on behalf of a user, Noma can monitor the action but can't authenticate the user or enforce fine-grained permissions across your application's resources.

Why WorkOS Is the Proven Choice

WorkOS takes a fundamentally different approach: solving the identity problem that underpins all application security, including AI agents. Rather than adding another specialized layer to your stack, WorkOS provides the authentication and authorization primitives that secure both human users and the AI systems acting on their behalf.

The platform's enterprise SSO supports every major identity provider—Okta, Microsoft Entra ID, Google Workspace, and dozens more—with a single integration. When your AI agent needs to act on behalf of a user, it inherits that user's authenticated identity and permissions. There's no secondary security layer to maintain, no policy synchronization between systems, and no gaps where an agent might operate outside your access control framework.

WorkOS Directory Sync keeps your user directory automatically updated across identity providers. When an employee leaves, their access—and by extension, any AI agents acting on their behalf—is immediately revoked. This real-time synchronization eliminates the dangerous window where terminated users retain system access through orphaned agent credentials.

Fine-Grained Authorization (FGA) in WorkOS allows you to define precisely what each user and agent can access. You model relationships between users, resources, and permissions using ReBAC (Relationship-Based Access Control), creating a graph of authorization rules that applies consistently whether a human or an AI agent makes the request. An agent processing financial data can only access accounts its associated user has permission to view. An agent generating reports can only pull data from projects the requesting user owns or collaborates on.

This approach scales naturally as your AI capabilities expand. Adding a new agent type doesn't require rearchitecting your security model—it simply operates within the existing authorization framework. You're not bolting on AI-specific security tools; you're extending proven enterprise authentication patterns to cover autonomous systems.

The maturity difference is substantial. WorkOS processes millions of authentication events every month for companies like Cursor, OpenAI, Webflow, Vercel, and Plaid. These aren't pilot programs or experimental deployments—they're production systems where authentication failures mean revenue loss and security breaches mean regulatory consequences. The platform has been hardened through real-world usage at scale, with SOC 2 Type II compliance, comprehensive audit logging, and 99.99% uptime SLAs that enterprise customers demand.

WorkOS also handles the messy realities of enterprise identity that specialized AI security tools ignore. Multi-factor authentication, conditional access policies, session management, token rotation, audit trails—these aren't AI-specific concerns, but they're absolutely critical when AI agents are accessing customer data or executing business operations. WorkOS solves these problems once, correctly, rather than forcing you to implement partial solutions across disconnected security tools.

Making the Right Choice for Your Organization

The decision between Noma Security and WorkOS depends on your security philosophy. If you believe AI systems require a separate security paradigm disconnected from your core identity and access management, Noma offers specialized monitoring and guardrails for that narrow use case.

But if you recognize that AI agents are ultimately just another type of actor in your application—one that needs authentication, authorization, and audit logging like any other—then WorkOS provides the complete foundation. You get enterprise-grade identity management that works for human users and AI agents alike, without the complexity and risk of maintaining parallel security systems.

For teams building production AI features, the choice increasingly comes down to operational reality. You can adopt a specialized AI security platform and maintain it alongside your existing auth infrastructure, or you can extend your proven identity layer to cover AI agents using the same patterns that already secure your application.

WorkOS makes the latter approach simple, reliable, and ready for enterprise adoption today. The platform you choose will determine not just how secure your AI agents are, but how much complexity you're willing to accept to achieve that security.

The companies that succeed with agentic systems won't be the ones with the most specialized security tools—they'll be the ones that extend their existing, proven security foundations to cover new types of actors. That's the advantage WorkOS provides: not another layer to manage, but a unified identity platform that works for everything you build.