As enterprises move from experimental chatbots to autonomous agents that can “act,” the security surface area has expanded exponentially. To address this, Zenity has officially launched its end-to-end security and governance platform on the AWS Marketplace, offering native integration with Amazon Bedrock AgentCore.
Closing the “Agentic Security Gap”
While Amazon Bedrock provides the framework for building agents, the flexibility of AgentCore (including its deep control over memory and orchestration) can create visibility blind spots. Zenity fills this gap by mapping agent intent to enterprise risk models.
Key Security Capabilities:
- Real-Time Behavior Monitoring: Unlike traditional filters, Zenity tracks the “chain of thought” to prevent indirect prompt injection and unauthorized memory access.
- Deterministic Runtime Controls: Set hard boundaries on what an agent can do (e.g., “Block all refunds over $1,000”) that remain enforced even as the agent’s underlying model evolves.
- Full-Lifecycle Observability: Gain a unified view of all agents across the organization, including “Shadow AI” agents deployed outside official IT channels.
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Strategic Advantage for AWS Customers
The availability on AWS Marketplace allows organizations to use existing AWS commercial relationships and cloud credits to procure Zenity. This streamlines the “security-by-design” approach for developers using Bedrock, allowing them to focus on agent logic while security teams maintain oversight via a single control plane.
“Enterprises are building agents that read emails, move money, and touch customer data,” says Ben Kliger, CEO of Zenity. “Those agents are where business value is created—and where risk shows up first. We are making it as simple to secure these agents as it is to secure your cloud infrastructure.”
The Shift to Agent-Centric Security
Traditional security tools (like EDR or WAF) are not designed to understand AI intent. Zenity’s presence in the AWS ecosystem represents a shift toward “Agent-Centric Security,” where the focus is not just on inputs and outputs, but on the autonomous decisions an agent makes in a multi-step workflow.