Secure and Govern Every AI Agent

End-to-end AI agents governance with real-time policy enforcement.

The Challenge

AI agents can access systems, execute tools, and trigger workflows autonomously. Without runtime governance, they may exceed permissions or be manipulated through prompt injection.

The Solution

The Guardian Agent enforces policy-driven controls over agent behaviour, tool access, and execution permissions, ensuring AI operates within secure, auditable enterprise boundaries.

Discovery of Your AI Agents

The Guardian Agent - Discovery Layer provides full visibility into agent activity across both user and developer environments.

Guardian Agent discovery layer showing connected AI tools and agents
AI Guardian Agent firewall scope and protected agent environment
AI Guardian Agent Scope

The Guardian Agent secures the full spectrum of agent activity, covering both home-grown and third-party agents. It protects internally developed agents and MCP servers that you build and publish, ensuring they operate under strict policy, authentication, and runtime controls.

Core Capabilities

MCP Server Governance

  • Controls AI agents connected via MCP
  • Regulates tool and system access
  • Enforces permission boundaries

Tool Access Enforcement

  • Define which tools agents can use
  • Restrict access to sensitive systems
  • Prevent unauthorized data retrieval

Runtime Behavior Monitoring

  • Monitor agent decision pathways
  • Detect abnormal execution patterns
  • Prevent automated misuse

Prompt Injection Defence

  • Detect malicious prompt manipulation
  • Block adversarial instruction overrides
  • Prevent unauthorized workflow trigger

Audit & Traceability

  • Full execution logs
  • Agent activity trace mapping
  • Governance reporting for compliance

How It Works

Five-step process for secure Guardian Agent governance

AI Agent Instruction

User prompts, agent context, and operational instructions enter the workflow.

Tool / MCP Layer

APIs, MCP servers, integrations, and tool execution requests are orchestrated.

Policy Decision

Actions are approved, denied, escalated, or logged based on governance policy.

Execution Monitoring

Runtime telemetry, audit trails, and operational visibility are continuously tracked.

Use Cases

Protect your organization across multiple scenarios

Secure internal AI automation workflows

Govern database query agents.

Control DevOps AI assistants

Prevent AI agent lateral movement

Enforce Zero-Trust AI architecture

FAQ Quick Access

Frequently Asked Questions

Can we restrict agents per department?
Yes. Policies can be role and environment-specific.
Does this prevent prompt injection attacks?
Yes. The Agent Layer actively detects and blocks adversarial prompts.
Can it control what the tools are allowed to do?
Yes, it can control which tools are allowed to do what

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