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Axora

Secure AI from access to action.

Axora helps enterprises govern AI access, protect agent actions, and validate the systems they rely on.

Abstract AI access network

AI is moving from answers to actions.

AI now accesses APIs, uses tools, and acts across connected systems. Every new connection introduces a security decision: who can access it, what it can do, and whether its controls hold under attack.

The Axora Model

Three control points. One security portfolio.

Organize enterprise AI security around the decisions that shape access, execution, and trust.

Axora model access control artwork

Products

Security for the way enterprise AI operates.

Start with the control point most relevant to your current workflow.

AgentGuard product artwork

AgentGuard

Protect AI before it acts.

Review supported agent components before trust, evaluate high-risk actions before execution, and apply policy-driven runtime control across supported integration paths.

Explore AgentGuard
Axora Router product artwork

Axora Router

One organized entry point for enterprise AI access.

Bring enterprise AI API usage into a unified entry point, allocate access and usage quotas across employees and teams, and support organization-wide usage management.

Coming Soon
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Axora Red Team

Test the boundary before you rely on it.

Evaluate AI systems, agents, and connected workflows through scoped adversarial scenarios, then turn the findings into priorities for remediation and retesting.

Explore Red Team

Why Axora

More AI capability. Clearer control.

Security should not reduce the value of AI. It should make that value safer to use. Axora helps organizations give AI greater access, more tools, and more autonomy while keeping rules, boundaries, and human authority clear.

  1. Enable, don’t restrict.

    Make valuable AI autonomy safer to deploy without turning every action into friction.

  2. Human authority by design.

    Keep approvals, exceptions, accountability, and final authority clear.

  3. Prove the boundary.

    Start with a real workflow, identify the relevant control point, and define what useful evidence looks like.

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