Secure with Guardrules and RBAC

Reliable AI systems require strong controls over what agents can receive, what they can produce, and who can manage them.
Our platform provides built-in guardrails and role-based access control to ensure agents operate safely and within defined policies.

Guardrules

Guardrules protect both the inputs sent to agents and the outputs they generate.

Input Guardrules

Input guardrules act as the first line of defence, filtering or constraining user inputs before they reach the agent.

They can be used to:

  • Block harmful or malicious prompts
  • Enforce topic boundaries
  • Require specific information from users
  • Prevent prompt injection attempts

Output Guardrules

Output guardrules monitor and control the responses generated by the agent.

They help prevent:

  • Inappropriate or harmful responses
  • Off-topic answers
  • Reputational or compliance risks

Guardrules can operate in two modes:

Detection Mode

Allows the agent to respond normally while logging rule violations for evaluation and review.

Prevention Mode

Stops or modifies responses when a rule is triggered, returning a controlled message to the user.

In multi-agent systems, guardrules failures can also halt downstream agent execution, preventing unsafe outputs from propagating through the network.

Role-Based Access Control (RBAC)

Security also requires control over who can create, manage, and deploy agents. The platform uses a project-based access model, where agents and knowledge resources live inside secure projects.

Within each project you can assign roles such as:

  • Administrators – full configuration and management rights
  • Users – controlled access to operate and interact with agents

This ensures that teams can collaborate safely while maintaining clear ownership and governance over AI systems.

Secure by Design

By combining guardrules for behavioural control with RBAC for operational governance, the platform provides a foundation for building AI systems that are both powerful and safe to deploy in real-world environments.

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