Enforce Control Across Every AI Agent and Application
Apply governance, policy enforcement, and real-time controls as AI agents and applications use data, invoke tools, and execute actions.
AI Is Moving From Language To Action.
Are You Ready? See what recent attacks revealed and how to secure agents in 2026.
AI Autonomy Is Outpacing Enterprise Control
AI agents and applications operate across enterprise data, tools, and workflows with growing autonomy. Governance must account for what AI systems can use, expose, and execute in every business context.
AI Systems Make Autonomous Decisions
Agents can act with limited human involvement.
They interpret instructions, reason across context, invoke tools, and execute multi-step workflows.
Result
AI can take actions that violate policy, exceed authority, or create operational risk.
AI Actions Span Data, Tools, and Business Systems
Every AI action can carry business risk.
AI applications and agents use data, invoke tools, trigger workflows, and interact with critical enterprise systems.
Result
Security teams need consistent controls wherever AI uses data, invokes tools, or performs actions.
Sensitive Data Flows Through AI Interactions
Sensitive data moves through prompts, files, outputs, and agent actions.
Traditional data controls are not designed to understand conversational intent or agent behavior.
Result
Confidential, regulated, or proprietary data can be exposed before security teams can stop it.
Static Policies Can’t Control Dynamic AI Behavior
The same action can be safe in one context and risky in another.
AI behavior changes based on user intent, retrieved context, tool responses, and multi-step reasoning.
Result
Governance requires real-time, context-aware enforcement that stops unsafe behavior without blocking productive AI use.
Govern AI Autonomy Across the Enterprise
Apply real-time controls that enforce policy across data use, tool invocation, and autonomous action, from employee AI usage to enterprise applications and agents.
Govern AI Access and Actions
Apply consistent governance across the AI agents, applications, and AI tools used throughout your organization. Define which AI systems can use specific data, invoke approved tools, connect to enterprise systems, and perform actions based on policy, context, and business need.
- Define granular policies by AI system, user, data type, and action
- Govern access to enterprise tools, SaaS platforms, APIs, and MCP servers
- Control which operations AI agents can perform across workflows
- Apply consistent governance across employees, applications, and agents
Bring Governance, Policy Enforcement, and Protection Together for Every AI Interaction
Enforce AI Policies at Runtime
Turn governance policies into enforceable controls. Inspect AI interactions inline, evaluate intent and context, and apply policies at the point where prompts, outputs, tool calls, tool responses, and agent actions occur. Stop policy violations before they affect users, data, or business operations.
- Enforce governance policies across prompts, outputs, and agent actions
- Block, redact, flag, or log activity based on risk and policy
- Apply context-aware controls without retraining models or rewriting prompts
- Update policies centrally as AI usage, systems, and risks evolve
Prevent Data Exposure and Unsafe Execution
Protect sensitive data and business workflows as AI systems operate. Detect confidential, regulated, or proprietary data in AI interactions, prevent unauthorized disclosure, and enforce controls that stop unsafe actions, tool abuse, and rogue agent behavior.
- Detect sensitive data in prompts, files, outputs, and tool responses
- Prevent unauthorized disclosure across AI interactions and workflows
- Stop tool misuse, unauthorized actions, and unsafe autonomy
- Protect AI applications and agents with policy-based controls
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