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40% of your agents are a critical risk. Read the CISO Playbook for Securing AI Agents

Announcing our Series D to fuel agentic productivity, securely

Secure your Google Vertex AI Agents from Buildtime to Execution

Govern every Vertex AI agent as it connects to data, moves across services, and acts on your behalf.

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Secure your Agents

Why are your teams using Google Vertex?

Unlike prebuilt AI assistants available with Gemini, Vertex AI lets users quickly build and deploy agents with custom AI models designed for the task at hand.

Automate complex workflows

Orchestrate multi‑step tasks like ticket triage, infra changes, CRM updates, and HR workflows.

Accelerate delivery

Use agents to write and review code, streamline processes, and improve customer experience.

Empower the workforce

Let non‑developers build workflows and agents without waiting on central engineering.

When Vertex AI agents act, who's watching?

Unmonitored Vertex agents silently spread risk across every application they access and every data connection they make.

Sensitive data access

An over‑permissioned HR or finance agent can query classified internal knowledge across apps like Google Drive.

Code destruction risks

Vertex-connected agents can change or delete source code, pipelines, or IaC in GitHub/Cloud Build, turning one misconfiguration into rapid, production-impacting damage.

Data leaks at machine speeds

Business teams can expose CRM or ticket data as agents autonomously generate and share content externally.

Fragmented agent monitoring

Similar agent use cases can run in Vertex, Copilot, and Bedrock; without unified governance, fragmented policies and logs hide risky cross‑platform behavior.

Google's native controls weren't built for agentic risk

Vertex AI agents move fast, connect broadly, and act autonomously, exposing gaps in Google's built-in security.

Secure your agents

Siloed visibility across tenants

No single view of which agents, MCP servers, and models are running across your tenants.

No single control plane

Native logs weren't built to capture risky tool calls and cross-service actions, especially from agents running outside Foundry on platforms like Claude.

Over-permissioned agents

Agent permissions are scattered across every app they touch. Without a unified view, you can't know your true exposure until something goes wrong.

Privilege escalation

Agents act on behalf of users but aren't always bound by the same limits. Without a full identity graph, you won't know when an agent quietly exceeds the access its user was granted.

Bring enterprise governance to every Vertex AI agent

Map, monitor, and control every Foundry agent from a single governance layer.

Inventory every Foundry AI agent

Maintain a continuous system of record for every AI agent, including the MCP servers they invoke, the LLMs behind them, and the applications they connect to.
Shadow AI and auditability: Find unsanctioned agents including their connections and executions.
Track every agent: Map agents and know their blast radius no matter the platform they are built on.

Real-time risk assessments for your agents

Automatically identify high-risk factors across your agent inventory, from unauthenticated MCP servers to over-privileged agents, so you understand and reduce exposure before an incident occurs.
Secure new agents by default: Automatically assess new and updated agents for risky scopes and unsafe tool chains.
Prioritize your security: Sort risks by criticality to consistently govern agents across every AI platform your teams deploy.

Remove unsanctioned agent connections

Trace every Vertex agent’s connections and compare to approved apps and MCP servers to reduce the blast radius and prevent data exposure.

Review MCP connections: Remove unapproved agent connections to risky MCP servers.
Protect sensitive systems: Limit agent access to only approved systems.