Existing vendor risk management processes were designed for static software and services, not for autonomous, evolving AI Agents that act independently in real-time. AI Agents introduce new, continuously changing risks that vendor management frameworks aren’t built to monitor, control, or adapt to post-deployment.

Most risk assessments for software focus on pre-contract assessments (such as for security and compliance standards maintained by the vendor), periodic audits or questionnaires, and service legal agreements with static control reviews. However, AI Agents are non-deterministic and keep learning, adapting, and acting after procurement, sometimes in unpredictable ways. This creates contextual risks that are dynamic and operational.

Unlike a traditional bounded service where the risk can be managed at the contract or infrastructure layer, AI agents act autonomously after deployment and in production environments, where decisions may have real-world impacts (e.g., financial trades, safety actions, content generation) which can be irreversible or difficult to unwind. 


Traditional vendor and third-party risk management is focused on infrastructure, access, and contractual obligations. AI risk is about behavioural alignment and decision-making over time, which can’t be managed by static assessments.

Geordie is built for simplicity, requiring only an API connection or optional code scanning to deploy. It layers effortlessly into your existing systems. No heavy lifts. No added complexity.

Geordie fits into your systems with ease. With just an API connection or code scanning, you get up and running. No disruptions, no extra complexity.

Geordie is designed for fast, low-friction deployment.

It requires only an API connection and/or optional code scanning to get started. There’s no need for heavy integrations or major system changes, so you can add controls and oversight without adding complexity to your existing enterprise stack.

Managing AI agents in separate platforms creates silos, making it difficult to track, assess, and control risk consistently. Just like managing risks across cloud, endpoints, and code, looking at AI agents in isolation can lead to blind spots.

Some risks only become visible when you view systems together. Without a unified perspective, it’s easy to miss combined or cascading risks that emerge across platforms.

Geordie gives you cross-system oversight so you can manage AI agent risks holistically, not in disconnected pieces.

For example:
An AI agent generating customer responses might be safe on its own. But if it starts pulling in data from another AI system, like an autonomous pricing agent, you could unintentionally create compliance, reputational, or financial risks that neither system flagged individually.

Geordie helps you monitor and control AI agents across platforms and use cases, giving you the full picture so you can catch combined risks before they escalate.

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We use advanced encryption, real-time monitoring, and comply with major industry standards, ensuring your data is safe at all times

AI agents aren’t like traditional software.


With standard software, issues often happen in closed systems you can halt a process, roll back a transaction, or restore a backup to fix a problem.

AI agents, especially autonomous ones operating in the real world (like financial trading, infrastructure management, or multi-agent coordination), can take actions with immediate and sometimes irreversible consequences.

Stopping the software isn’t enough if the action has already happened.


That’s why AI risk management needs more than just autonomous detection and response. It requires preemptive controls to guide decisions before actions are taken and post-decision interventions to adjust or mitigate impacts after actions occur, similar to how we manage human risk in complex systems.Geordie is built for this kind of continuous, real-world AI governance, rather than just process-level control.