AI adoption is moving faster than most governance models can keep up.
Across the enterprise, teams are deploying AI agents to improve productivity, automate tasks, and accelerate delivery. But many of those agents are hard to track, poorly documented, or invisible outside the team that launched them.
That creates a simple problem with serious consequences: you can't govern what you can't see.
With Ardoq's Import Builder and AI Lens Solution, organizations can bring AI agents into a governed, contextualized view of the enterprise. The result is better visibility, faster oversight, and more confident AI decision-making.
It's worth being clear about scope. AI agents are one category of AI system, but they are among the fastest-moving and hardest to track. Unlike traditional AI systems that go through established procurement and documentation processes, agents are often spun up quickly by different teams across numerous platforms.
They are not isolated pilots. They are showing up across business units, embedded in workflows, and increasingly connected to critical systems and data.
For CIOs, enterprise architects, and governance teams, that creates real challenges:
When discovery is manual, governance is always playing catch-up.
Ardoq closes that gap by combining Import Builder with AI Lens, our Enterprise AI Management Solution.
Using Import Builder, teams can connect Ardoq to enterprise AI platforms such as Google Vertex AI, Microsoft Foundry, Amazon Bedrock, or any other platform with a standard API, and pull AI agent metadata directly into Ardoq. That information flows into the architecture graph, where it becomes part of a broader architecture and governance view.
The Import Builder can also be configured to classify ingested agents correctly, so they sit alongside other AI system types in your repository rather than existing as a separate, disconnected list.
Once imported, agents can be linked to the underlying AI capabilities they rely on, such as large language models, multimodal models, and applied AI platforms, as well as the broader business and technical capabilities they support. The agents you discover are immediately useful within Ardoq's broader AI management model, not just visible.
What that looks like in practice:
This is not about importing data for the sake of it. It’s about understanding where your AI agents are, what they connect to, and what happens if something changes.
Getting AI agents into a governed model opens up a set of capabilities that are hard to achieve any other way.
A current, connected inventory gives teams a clearer picture of which agents exist, where they are deployed, and how they fit into the wider technology environment. It becomes much easier to spot unmanaged deployments, reduce blind spots, and have an honest conversation about what the organization is actually running.
When agents are visible in context, governance work gets more tractable. Teams can assess ownership, dependencies, and potential risk without chasing information across teams and spreadsheets. Compliance and security stakeholders can work from a shared, up-to-date view instead of piecing things together from multiple sources.
Visibility across the agent landscape is also a portfolio management tool. Organizations can identify overlapping experiments, duplicated capabilities, and poorly aligned initiatives. That makes it easier to redirect investment toward higher-value use cases and cut waste across the AI portfolio.
The challenge of scaling AI is not just adoption; it is control. When teams have a clear picture of what has already been deployed, decisions about what to build next are better informed. Discovery gives leaders a clear view of the current landscape rather than a best guess.
Manual documentation can’t keep up with the pace of AI change. To govern AI agents effectively, organizations need a way to continuously discover what exists, classify it correctly, and place it in the right business and technology context.
That is what combining Ardoq’s Import Builder and AI Lens Solution makes possible. It gives enterprise teams a practical path from fragmented, incomplete AI visibility to a governed approach where oversight, prioritization, and decision-making are all working from the same picture.
Learn about all our latest AI developments and capabilities at Ardoq Labs.