AI agents do not behave like traditional software. Securing them means moving beyond access and protocols to govern autonomous systems in real time.
AI agents are like digital employees, with roles, access, data, and the ability to make decisions in pursuit of goals in real time. The minimum viable definition of an agent is a large language model equipped with at least one tool. The tool can be anything from an API to an MCP to a SaaS connector.
Agents can chain tools, make instant decisions, and have the capability to impact operations at a speed and call orders-of-magnitude beyond any employee or team.
Agents are unpredictable, and their decisions do not follow a specific logic chain, meaning the requirements for controls, behavioral observability, and contextual governance are critical.
Even if you test agents pre-deployment, the risks and behaviors won't remain the same. Know which agents are in use, by which teams, and for what work, so you can guide adoption and governance.
Geordie gathers data directly from where your agents operate: across code, cloud, and endpoint, and across the architectures and tool connections in your environment. That coverage gives your team a continuous view of agent behaviour and risk that static policies and access controls can't provide.
Most organisations don't have an accurate view of which agents are running, what they're connected to, or how their configurations change over time. Geordie automatically discovers every agent across your cloud, code, and endpoint environments and maintains a continuously updated map of their full configuration.
Permissions define what an agent can do. Behaviour tells you what it does. Geordie maintains an auditable record of every decision, tool call, and data access across your agent fleet. Behavioural baselining and anomaly detection identify when something falls outside expected bounds.
Agent risk emerges from sequences of actions, context, and downstream consequences, not individual transactions. Geordie analyses activity and configuration using proprietary risk and threat modelling, with findings mapped to relevant standards.
Agents deliver value by operating continuously and autonomously. Geordie evaluates each decision in context, applying controls directly at the agent level so operations continue uninterrupted.
Endpoint and network security was built around human-initiated activity. When agents operate machine-to-machine, that traffic can bypass traditional choke points entirely, or arrive without the context needed to evaluate it. You can see that something happened, not what it means.
Cloud security tools cover workloads within their perimeter. Agents don't stay in one perimeter. They operate across cloud, endpoint, and code simultaneously, and any activity involving external tools, APIs, or third-party services happens outside any single provider's visibility boundary.
Identity and access management tells you what an agent is permitted to do. It doesn't tell you what it does, in what sequence, or what the downstream consequences are. A permission check at the start of a session says nothing about the actions that follow it.
MCP gateways intercept at the point of tool invocation, evaluating each request without the context of what the agent has already done or is working toward. That means the risk that emerges from sequences of actions remains invisible. Gateways introduce deployment friction and binary controls. Coverage is also partial: shadow AI, user-coded tools, hard-coded integrations, and direct API calls fall entirely outside the gateway's view.
What you can do with agents you trust
When your agents are understood, approved with evidence, and operating under controls that work at their level, your organisation can deploy faster, expand further, and build on what's working. That's what Geordie makes possible.
“We're seeing the iceberg that rocked the Titanic — weeks in advance rather than the moment it appears on screen. We're able to take a snapshot of the entire ecosystem and have adult, grown-up conversations about what's responsible and what's not. We can quantify everything now.”
