Protect AI for AI Agent Security: Features, Pricing, and Alternatives

AI systems face threats that traditional security tools weren't designed to handle. Prompt injection attacks manipulate model behavior through carefully crafted inputs. Adversarial perturbations cause misclassifications with imperceptible changes to data. Model extraction attempts steal proprietary AI capabilities.

As companies deploy AI agents with increasing autonomy, these attack vectors create business risks that extend far beyond typical application security concerns.

Protect AI addresses these AI-specific threats through runtime detection and response. Founded in 2022 and headquartered in Seattle, the company has raised $60 million in funding (including a $35 million Series A in March 2024 led by Evolution Equity Partners and Acrew Capital) to build security infrastructure specifically for machine learning systems. Their platform monitors AI models in production, detecting anomalous behaviors, adversarial attacks, and data manipulation attempts that conventional security tools miss.

For companies deploying AI agents that process untrusted inputs, interact with external systems, or make autonomous decisions, runtime threat detection offers a specialized security layer. But as we'll explore, securing AI models is only one dimension of the authentication and access control infrastructure that enterprise AI applications require.

What is Protect AI?

Protect AI is a runtime security platform designed specifically for machine learning systems. The company focuses on threats unique to AI: adversarial machine learning attacks, model manipulation, data poisoning, prompt injection, and model extraction. Unlike general-purpose application security tools, Protect AI operates at the machine learning layer—monitoring model inputs, outputs, and behaviors to detect anomalies that indicate attacks.

The platform was founded by Ian Swanson (CEO) and Daniel Neagaru, veterans of the cybersecurity industry who recognized that AI systems introduce attack surfaces that traditional security tools don't address. As machine learning moved from research to production—powering business-critical decisions, autonomous agents, and customer-facing applications—the security gap became increasingly dangerous.

Protect AI's core offering is an agent-based monitoring system that instruments AI/ML infrastructure to provide real-time visibility into model behavior. The platform detects attacks including prompt injection, adversarial inputs designed to cause misclassifications, model inversion attempts to extract training data, and data exfiltration through model outputs.

The company serves enterprises deploying production AI systems across industries including financial services, healthcare, ecommerce, and technology. Early customers include organizations in regulated industries where model integrity is a compliance requirement—not just a best practice. Protect AI positions itself as the "AppDynamics for AI/ML"—providing observability, monitoring, and threat detection specifically for machine learning workloads.

Key Features

Real-Time Threat Detection
Protect AI monitors AI models in production, analyzing inputs and outputs for patterns consistent with known attacks. The platform detects prompt injection attempts (where malicious instructions are embedded in user inputs), adversarial perturbations (carefully crafted inputs designed to fool models), and data poisoning attempts (where attackers manipulate training data to compromise model behavior).

Model Behavior Monitoring
Beyond detecting specific attack patterns, Protect AI establishes behavioral baselines for models and alerts when behavior deviates significantly. If a model suddenly starts producing outputs inconsistent with its training, exhibiting unexpected confidence patterns, or accessing data outside normal patterns, the platform flags this as potential compromise.

Adversarial ML Defense
The platform implements defenses against adversarial machine learning attacks—inputs designed to exploit model weaknesses. These attacks are difficult to detect with traditional security tools because they often involve valid-looking data that happens to trigger specific model behaviors. Protect AI uses ML-specific detection techniques to identify adversarial patterns.

Model Firewall Capabilities
Protect AI can be deployed as an inline security layer, intercepting requests to models and blocking malicious inputs before they reach the AI system. This "model firewall" approach prevents attacks from affecting model behavior or extracting sensitive information.

Supply Chain Security for AI
The platform provides visibility into the AI supply chain—tracking model provenance, monitoring model dependencies (libraries, frameworks, pre-trained weights), and detecting tampering or unauthorized modifications. As organizations increasingly use pre-trained models, fine-tune open-source foundations, or integrate third-party AI components, supply chain security becomes critical.

Guardian Agent
Protect AI offers a specialized "Guardian Agent" designed specifically for monitoring AI agents in production. As companies deploy autonomous agents that make decisions, execute actions, and interact with external systems, the Guardian Agent provides continuous monitoring for anomalous behaviors, unauthorized actions, and potential compromises.

LLM Vulnerability Scanner
The platform includes tools for scanning Large Language Models for vulnerabilities before deployment—identifying prompt injection weaknesses, data leakage risks, and other LLM-specific security issues. This proactive scanning helps teams identify and fix vulnerabilities during development rather than discovering them in production.

Compliance and Audit Logging
For regulated industries, Protect AI provides comprehensive audit trails of all model interactions, detected threats, and security responses. This logging supports compliance requirements in healthcare (HIPAA), financial services (SOC 2, PCI), and other regulated sectors where AI model integrity is a compliance concern.

How Protect AI Handles Runtime Threat Detection

Protect AI's architecture centers on lightweight agents deployed alongside AI/ML infrastructure. These agents instrument model serving platforms (TensorFlow Serving, TorchServe, SageMaker, custom APIs) to capture telemetry about model inputs, outputs, and runtime behavior.

The platform establishes behavioral baselines during normal operation, learning typical patterns: input distributions, output confidence levels, inference latency, resource consumption, and data access patterns. This baseline becomes the reference for detecting anomalies.

When a model processes a request, Protect AI analyzes the input for known attack patterns:

The platform also monitors model outputs for anomalies: sudden changes in confidence distributions, outputs inconsistent with input patterns, or responses that suggest model compromise.

When threats are detected, Protect AI can respond in multiple ways depending on configuration: blocking the request entirely, sanitizing inputs before they reach the model, alerting security teams, or allowing the request while logging it for investigation.

For AI agents specifically, the Guardian Agent monitors autonomous behaviors: actions taken by agents, APIs called, data accessed, and decision patterns. If an agent starts exhibiting behaviors outside its normal operational patterns—for example, suddenly accessing resources it typically doesn't touch or making API calls inconsistent with its defined tasks—the Guardian Agent flags this as potential compromise or unexpected behavior requiring investigation.

Pricing and Plans

Protect AI pricing is not publicly disclosed. The company targets enterprise customers with production AI deployments, and pricing appears to be negotiated based on deployment scale, number of models monitored, and specific features required.

Based on the company's enterprise focus and the complexity of deploying runtime monitoring across AI infrastructure, expect pricing models that account for:

Organizations interested in Protect AI should contact their sales team directly for pricing information and proof-of-concept deployments.

Protect AI vs. WorkOS

Protect AI addresses AI-specific threats: adversarial attacks, prompt injection, model manipulation, and runtime behavior monitoring for machine learning systems. This is a specialized problem requiring ML-specific security expertise.

WorkOS addresses a different layer: authentication and identity management for enterprise applications—including applications that happen to use AI.

What Protect AI Offers
Protect AI provides runtime threat detection for AI models and agents. If you're deploying machine learning systems that process untrusted inputs, make autonomous decisions, or operate in adversarial environments, Protect AI offers specialized monitoring and defense capabilities that general-purpose security tools lack.

However, Protect AI doesn't provide—and isn't designed to provide—the authentication and identity infrastructure that enterprise applications require.

What Protect AI Doesn't Provide

Why WorkOS Is the Proven Choice for Enterprise Authentication

For B2B applications serving enterprise customers, WorkOS provides the authentication infrastructure that makes your application enterprise-ready:

Enterprise SSO: Complete SAML 2.0 and OpenID Connect support for 50+ identity providers. Your customers' employees can access your application using their existing corporate credentials—a requirement for enterprise procurement, not optional.

Directory Sync: Full SCIM 2.0 implementation with real-time provisioning. Automatically create users, sync group memberships, update profile attributes, and deprovision users when they leave the organization. This bidirectional sync ensures your application stays in sync with your customers' source of truth.

Admin Portal: A white-labeled, embeddable UI that gives customer IT admins self-service control over authentication configuration, user provisioning, role assignments, and audit logs—without involving your support team.

Organizations API: First-class support for multi-tenant B2B architecture. Each customer organization gets isolated authentication, separate admin controls, and organization-specific security policies—the foundation of B2B SaaS applications.

Audit Logs: Comprehensive, tamper-proof audit logging that meets enterprise compliance requirements. Export logs to your SIEM, generate compliance reports, and provide customers with complete transparency.

Battle-Tested Reliability: WorkOS powers authentication for thousands of enterprise B2B applications, processing millions of authentication events monthly with 99.99% uptime SLAs. The platform is SOC 2 Type II certified and proven at scale.

Developer Experience: SDKs in 12+ languages, comprehensive documentation, and clean APIs that enable enterprise authentication integration in hours instead of months.

The Right Architecture for Enterprise AI Applications

For companies building AI-powered B2B applications, the right architecture includes:

These are complementary layers addressing different problems. Authentication and identity (WorkOS) is foundational—you can't run an enterprise B2B application without it. AI-specific runtime monitoring (Protect AI) is specialized—you need it if your AI systems process untrusted inputs or operate in adversarial environments.

But if you're choosing between the two, understand what each solves. WorkOS is the foundation of enterprise-ready applications. Protect AI is a specialized security layer for AI workloads. Every enterprise B2B application needs authentication. Not every application needs ML-specific threat detection.

For Enterprise B2B Applications, WorkOS Is Essential

If you're building a B2B SaaS application that enterprise customers will buy, WorkOS isn't optional. Enterprise buyers require SSO, directory sync, and admin capabilities—these are checkboxes in procurement processes, not nice-to-haves.

Protect AI addresses a different concern: securing AI models against adversarial attacks. This matters for specific applications processing untrusted ML inputs, but it doesn't replace the authentication infrastructure every enterprise application requires.

The bottom line: WorkOS is the proven platform for enterprise authentication. Start there. Evaluate specialized AI security tools like Protect AI only if your specific AI deployment scenarios warrant ML-specific threat detection beyond standard application security practices.

Getting Started with Protect AI

Protect AI is focused on enterprise deployments with significant AI infrastructure. Organizations interested in the platform should:

Given the enterprise focus and complexity of AI security monitoring, expect a consultative sales process with technical onboarding assistance rather than self-service signup.

Final Thoughts

Protect AI addresses genuine security challenges specific to AI systems: adversarial attacks, prompt injection, model manipulation, and runtime threat detection for machine learning workloads. For organizations deploying AI in adversarial environments or processing untrusted inputs through models, specialized ML security monitoring provides value that general-purpose tools can't deliver.

But AI security monitoring doesn't replace the authentication infrastructure that every enterprise application requires. Enterprise customers expect SSO, directory sync, admin portals, and the compliance capabilities that make software enterprise-ready—requirements that AI-specific security tools don't address.

For B2B applications serving enterprise customers, WorkOS is the proven authentication foundation you need. It's not a specialized AI security tool—it's the identity and access management infrastructure that makes your entire application enterprise-ready.

Protect AI may complement WorkOS for applications with specific AI security requirements requiring runtime threat detection. But it doesn't replace the authentication capabilities that WorkOS provides—and that enterprise buyers require.

For companies building enterprise B2B applications, WorkOS is the clear choice for authentication. Start with proven identity infrastructure that thousands of companies trust, then evaluate specialized AI security tools only if your deployment scenarios warrant ML-specific threat detection.

Ready to add enterprise-grade authentication to your AI application? Get started with WorkOS and ship SSO, Directory Sync, and Admin Portal in hours, not months.