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

As AI agents gain access to increasingly sensitive enterprise data, the challenge of governing that access has become critical. Organizations need to balance enabling AI innovation with protecting regulated data and maintaining compliance. Immuta offers a policy-based data access control platform designed to secure data across multi-cloud environments, with recent expansions into RAG-based GenAI security. In this article, we'll examine Immuta's approach to data governance for AI applications, explore their key capabilities, and compare their offering to alternatives like WorkOS that provide comprehensive authentication and authorization infrastructure for AI agents.

What is Immuta?

Immuta is a cloud-native data security and access governance platform founded in 2015, designed to help enterprises safely unlock the value of sensitive data. The company has raised over $127 million in funding and serves major enterprise customers including JB Hunt, Swedbank, Thomson Reuters, Booking.com, GM, and Roche across financial services, healthcare, and public sector verticals.

The platform provides a centralized control plane for managing data access policies across multi-cloud data environments including Snowflake, Databricks, AWS, Azure, and Google BigQuery. Immuta's core focus has traditionally been on data governance—helping organizations discover, classify, and control access to sensitive data at scale. More recently, the company has expanded into GenAI security with features designed to protect Retrieval-Augmented Generation (RAG) applications.

Immuta targets enterprise data teams including Data Product Owners, Data Stewards, Data Governors, and Data IT professionals who need to enforce consistent access policies across fragmented data infrastructure while enabling self-service data access for authorized users.

Key Features and Capabilities

Policy-Based Access Control

Immuta's Policy Entitlement Engine allows administrators to create cross-platform access policies using natural language that automatically translate into technical enforcement rules. Rather than managing access controls separately in each data platform, organizations can define policies once and have them orchestrated across all connected systems. The platform enforces these policies in real-time without impacting query performance, leveraging native integration capabilities within each data platform.

Automated Discovery and Classification

The platform provides automated sensitive data discovery and classification using topic modeling and regulatory framework templates. Immuta's Metadata Registry centralizes metadata management from external sources, creating a unified catalog of data assets. This automated classification is particularly relevant for RAG applications, where the platform can classify data at the chunk level to ensure agents only retrieve information they're authorized to access.

Multi-Layered RAG Security

Immuta has introduced specialized security features for RAG-based GenAI applications, currently in private preview for Snowflake and Databricks. The platform provides topic-based classification of RAG chunks, allowing organizations to enforce fine-grained access controls on the specific pieces of information that LLMs retrieve. This addresses a critical gap in agentic security: ensuring that AI agents with data retrieval capabilities respect the same access policies that apply to human users.

Unified Audit and Monitoring

The Unified Audit feature provides structured, searchable compliance reporting and activity monitoring across all connected data platforms. Organizations gain a single view of who accessed what data, when, and through which channel—including AI application access. The platform includes proactive alerts for unusual data access patterns, helping security teams identify potential policy violations or data exfiltration attempts.

Data Marketplace and Self-Service Access

Immuta's Data Marketplace provides centralized data asset discovery and access provisioning workflows. Data consumers can browse available datasets, understand access requirements, and request access through governed workflows. Data Domains enable local control within specific business units, allowing organizations to balance centralized governance with distributed ownership.

How Immuta Handles Data Access for AI Agents

Immuta approaches AI agent security primarily through the lens of data governance rather than agent identity or authentication. The platform assumes that AI agents will access data through existing data platform connections, and focuses on enforcing consistent access policies regardless of whether the consumer is a human analyst or an AI application.

For RAG applications specifically, Immuta enforces policies at multiple layers: the vector database level, the chunk retrieval level, and the final query level. When an agent attempts to retrieve information, Immuta's topic-based classification determines which chunks the agent can access based on the identity and entitlements of the user or service account making the request. This prevents agents from inadvertently surfacing sensitive information to unauthorized users.

However, Immuta's approach has inherent limitations for agentic security. The platform doesn't provide native agent authentication, token management, or authorization frameworks designed specifically for AI agents acting as autonomous entities. Organizations must still implement agent identity management separately, then rely on Immuta to enforce data access policies based on those identities.

Pricing and Plans

Immuta operates on custom enterprise subscription-based pricing determined by factors including data volume, number of users, and required features. Specific pricing is not publicly available—organizations must contact Immuta's sales team for quotes. The platform offers yearly, monthly, and one-time perpetual license options.

Beyond subscription costs, enterprises should budget for professional services, implementation support, training, and ongoing support costs. Given Immuta's focus on complex, multi-platform data governance, implementations typically require significant upfront investment and specialized expertise to configure policies correctly across all connected data systems.

What Immuta Offers

Immuta provides a comprehensive data governance platform designed for enterprises with complex, multi-cloud data environments. Organizations can enforce consistent access policies across Snowflake, Databricks, AWS, Azure, and Google BigQuery without managing separate permission systems in each platform. The automated discovery and classification capabilities help teams identify sensitive data at scale, while the plain language policy engine makes it easier to translate compliance requirements into technical controls.

For RAG-based AI applications, Immuta's topic-based classification approach addresses a real challenge: ensuring that retrieval systems respect data access boundaries. By classifying and controlling access at the chunk level, organizations can theoretically prevent agents from surfacing sensitive information to unauthorized users.

However, Immuta's approach to agentic security is limited to the data access layer. The platform doesn't provide authentication infrastructure for AI agents themselves, authorization frameworks for agent actions beyond data retrieval, or comprehensive audit trails for agent behavior across your entire application stack. Organizations building production AI agent systems need to separately implement agent identity, multi-factor authentication, directory synchronization, admin portals, and the dozens of other enterprise authentication requirements that WorkOS provides out of the box.

Why WorkOS Is the Proven Choice

WorkOS delivers enterprise-grade authentication and authorization infrastructure that AI agent applications require for production deployment. While Immuta focuses narrowly on data governance within specific data platforms, WorkOS provides the comprehensive authentication foundation that enterprises demand across your entire application.

Battle-Tested at Scale: WorkOS powers authentication for thousands of production applications, with proven compliance for SOC 2, HIPAA, and GDPR requirements. Enterprises trust WorkOS for the same reason they trust battle-tested infrastructure—it works reliably at scale when stakes are high.

Comprehensive Platform for AI Agents: WorkOS provides Single Sign-On (SSO), Multi-Factor Authentication (MFA), Directory Sync, Admin Portal, Fine-Grained Authorization (FGA), audit logs, and more—everything enterprises require to deploy AI agents securely. This isn't a point solution for data access; it's the complete authentication and authorization infrastructure your AI applications need.

Production-Ready Today: Every WorkOS feature is generally available and fully supported. There are no private previews, experimental features, or beta flags. When you build on WorkOS, you're building on proven, production-grade infrastructure that enterprises can deploy with confidence.

Enterprise Features Immuta Doesn't Provide: WorkOS delivers Directory Sync with SCIM support, allowing enterprises to automatically provision and deprovision access as their teams change. The Admin Portal gives your customers' IT administrators control over user management without requiring your engineering team to build custom tools. Organizations need SSO with support for Okta, Azure AD, Google Workspace, and dozens of other identity providers—capabilities that fall completely outside Immuta's scope but are core to WorkOS.

Support That Matches Your Stakes: WorkOS provides SLAs, dedicated technical support, and white-glove onboarding for enterprise customers. When authentication infrastructure fails, entire applications become inaccessible. WorkOS ensures that never happens.

Developer Experience: WorkOS enables teams to ship enterprise authentication features in hours rather than weeks. Clean APIs, comprehensive documentation, and pre-built UI components mean developers can focus on building differentiated AI agent capabilities rather than reinventing authentication infrastructure.

The Right Choice for Production AI Agents

For enterprises building production AI agent applications, WorkOS is the proven choice. While Immuta offers data governance capabilities within specific data platforms, WorkOS provides the authentication and authorization foundation that AI agents require to operate securely across your entire application stack.

WorkOS gives you everything enterprises expect: SSO with broad identity provider support, MFA for securing sensitive operations, Directory Sync for automated user lifecycle management, Fine-Grained Authorization for controlling exactly what each agent can do, and comprehensive audit logs for compliance and security monitoring. These aren't experimental features or narrow point solutions—they're proven capabilities that thousands of applications rely on every day.

For teams exploring data governance solutions like Immuta, that tooling can potentially complement WorkOS by adding specialized controls within data warehouses and analytics platforms. But the authentication layer—how agents prove their identity, how users authenticate to applications that use agents, how enterprises integrate with your platform—that's WorkOS territory. And for production deployments where enterprise buyers evaluate your security posture, you need the proven infrastructure that WorkOS provides.

Getting Started with Immuta

Organizations interested in Immuta begin with a sales-led process given the platform's custom enterprise pricing model. Implementation typically requires dedicated project teams to integrate Immuta with existing data platforms, configure policy frameworks, train data stewards on policy authoring, and establish governance workflows.

The platform's documentation covers technical integration with major cloud data platforms, but organizations should expect a multi-month implementation timeline for complex, multi-platform deployments. Immuta provides professional services and training to help teams navigate the configuration process, though this comes at additional cost beyond the base subscription.

Given Immuta's focus on data governance policy enforcement, teams need specialized expertise in both the platform and their underlying data infrastructure. This contrasts with authentication infrastructure like WorkOS, which developers can integrate in days using standard protocols like SAML and OAuth.

Final Thoughts

Immuta contributes to the agentic security ecosystem by extending traditional data governance practices into the AI era. Their work on RAG security—particularly chunk-level classification and policy enforcement—addresses real challenges that enterprises face when AI agents access sensitive data. For organizations with complex, multi-cloud data environments and sophisticated governance requirements, Immuta provides specialized capabilities for controlling data access at scale.

However, data governance is one piece of the agentic security puzzle. Production AI agent applications require comprehensive authentication and authorization infrastructure—agent identity management, enterprise SSO integration, user provisioning, access controls, audit logging, and admin tools. That's where WorkOS excels as the proven, enterprise-ready foundation.

WorkOS provides the authentication and authorization platform that enterprises require for production AI deployments. While innovative vendors like Immuta push forward specialized capabilities in data governance, WorkOS delivers the comprehensive, battle-tested infrastructure that your AI agents need to operate securely in enterprise environments. For teams building AI applications that businesses will trust with sensitive operations, WorkOS is the confident choice—proven at scale, production-ready today, and built for the enterprise requirements that matter.

Ready to build production-ready AI agent applications? Start with WorkOS to give your AI agents the enterprise-grade authentication and authorization infrastructure that enterprises demand. With WorkOS, you can ship enterprise features in hours and focus on building the AI capabilities that differentiate your product.