3 AI Agents for Marketing, Built Live: Webinar Recap

What happens when marketing reporting stops being the end of the workflow—and becomes the starting point for action?

In a recent webinar, “Beyond Reporting: 3 AI Agents Built Live,” NinjaCat CEO Paul Deraval demonstrated how AI agents for marketing can automate workflows by building three agents live for budget pacing, anomaly detection, and QA.

No slideware. No hypothetical AI use cases. Just agents being built around the kinds of workflows marketing teams already manage every day.

From Reporting to Action

For years, marketing teams have invested in getting their data into one place, building reports, and making performance easier to understand.

AI agents open up the next step: putting that data to work.

Instead of waiting for someone to review a report, spot an issue, decide what needs to happen, and manually execute the next task, an agent can be given a specific job and continuously work against the data already flowing through your organization.

The goal isn't to replace the marketer making the decision. It's to change where their time goes: from assembling and checking the work to reviewing, approving, and improving it.

Three Agents. Built Live.

The budget pacing agent monitors spend against budget targets and performance signals, helping surface accounts that are overspending, underspending, or otherwise drifting off plan.

The anomaly detection agent looks across marketing performance data for unusual changes that warrant attention, giving teams a faster way to spot potential issues without manually checking every account or campaign.

The QA agent applies defined rules to marketing data and account structures to identify inconsistencies and exceptions that would otherwise require repetitive manual review.

What mattered wasn't simply that AI could perform these tasks. It was how quickly Paul could move from defining a job to creating a functioning agent around it—without turning each workflow into a development project.

For teams managing marketing at scale, that distinction matters. A task that's manageable across five accounts can become hours of repetitive work across 50 or 500. Specialized AI agents can take on more of that continuous monitoring and analysis while marketers stay in control of the decisions that require their judgment.

How Do AI Agents Fit Into Existing Marketing Workflows?

Perhaps the most important idea from the webinar: the move to AI agents doesn't require abandoning the reporting infrastructure you've already built.

Your existing data, workflows, and marketing expertise become the foundation.

That's what makes the expansion from reporting to agents interesting. Reporting answers what happened? Agents can help teams move toward what needs attention, what should happen next, and what can we do about it?

The result is a shorter distance between the analyze → optimize → act cycle.

Why Watch the Full Demo?

AI agents can sound abstract until you see one being built.

The recording gives you the practical version: how an agent goes from a defined job to a working part of a marketing workflow, how multiple agents can be orchestrated around different responsibilities, and where human oversight fits into the process.

If you're already using NinjaCat for reporting—or simply wondering what AI agents could realistically take off your team's plate—this is a useful look at what's on the other side of the dashboard.

→ Book a demo

‍