Earlier AI tools responded to prompts.
Agents take action.
Agentic AI introduces a class of threats existing security stacks were never built to handle.
- Security teams today try to manage these new risks with existing tools.
- But traditional security tools weren’t built for autonomous agents.
- They can’t detect sensitive data movement across multi-step tool chains, stop prompt injections or unsafe outputs mid-session, or surface in-build vulnerabilities before an agent ships.
- What’s needed is a platform that continuously secures the entire Agentic AI ecosystem in your enterprise: the agents your employees use today, plus the agents your teams build and run.
Set guardrails for how your teams use and build AI agents.
See and control every AI agent your employees use, in real time.
Discover every AI agent in use across your organization, including unsanctioned tools, agents embedded in SaaS applications, and shadow MCP servers employees connect without IT oversight.
Stop prompt injection attempts, unauthorized data access, and policy violations in real time, with continuous inspection of agent interactions based on intentions, agent identity, data sensitivity and more.
Prevent sensitive data from leaking to the web, third-party models, or other agents, with policies enforced based on user account type, real-time data classification, and the specific agent intentions being invoked.
Know what every agent you build can reach, and what it’s doing.
Uncover and monitor every MCP server, tool call, and data exchange between agents and enterprise systems, so nothing operates outside your line of sight.
Ensure no agent operates outside defined boundaries with full visibility for agent identity, MCP tool access, and data flow across your entire build environment.
Detect when sensitive information crosses system boundaries before it becomes a breach, by tracking cross-call data lineage across multi-step agent workflows.
Battle test your AI agents before you deploy.
Know your guardrails hold under adversarial pressure, with simulated prompt injection and jailbreak attempts that stress-test defenses before deployment.
Surface real vulnerabilities and CVEs before they reach production, by executing agent code paths end-to-end in a controlled environment.
Ensure harmful, misleading, or unsafe content never reaches users or connected systems, with every agent output validated against Safe Output Governance policies.
Monitor and govern every agent communication.
Ensure no errant agent call reaches your enterprise systems, with every tool call, API invocation, and data retrieval verified and controlled through the MCP Gateway.
Catch prompt injection, data leakage, and policy violations before they impact your agents or users, with every model interaction inspected in real time through the LLM Proxy.
Deploy in minutes with Zero-Touch Onboarding across popular MCP clients and servers, with a custom MCP registry, role-based endpoint controls, and full observability into every agent call.
Your business is ready for AI agents.
Now your security team can be, too.
“The shift from AI as a tool to AI as an actor demands security purpose-built for AI from the ground up.
If agents can act across enterprise systems, governance has to exist at the point of execution.”
Tas Jalali
Head of Cybersecurity
AC Transit
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