"AI" is the buzzword of the year, but in the world of paid media, generic AI chat bots aren't enough. You need AI that understands data, context, and money.

At Pace, we didn’t just want to build a calculator; we wanted to build an analyst. That is why we built our intelligence layer on top of Google’s Gemini Large Language Model (LLM) via the Genkit framework. Here is how Pace uses advanced AI to make your budget go further.

Context-Aware Recommendations

Most "automated rules" in ad platforms are binary: If CPA > $50, pause ad.

Pace uses Gemini to understand the nuance. Our Budget Optimization Flow doesn't just look at one metric; it ingests a holistic view of your campaign:

• Current monthly budget vs. actual spend.

• Days remaining in the month.

• Historical campaign performance.

• Your specific user-defined goals (e.g., Maximize Clicks vs. Target ROAS).

We construct a detailed prompt for Gemini containing this live data. The AI analyzes the scenario and returns a structured recommendation, explaining why a change should be made.

The "Reasoning" Engine

One of the biggest fears marketers have about AI is the "Black Box"—the machine makes a change, and you don't know why.

Because we leverage Genkit and Gemini, Pace provides the reasoning behind the recommendation.

Example: "Increase budget on Campaign A by 15% because its CPA is 20% below target and search volume is trending up, while maintaining the overall account cap."

Automatic Pacing Adjustments

It isn't just about advice; it's about action. Pace can interpret these AI insights to automatically pause campaigns that are dangerously over budget or re-enable them when a new month begins.

By combining the raw computational power of our Next.js backend with the cognitive reasoning of Gemini, Pace gives you the best of both worlds: mathematical precision and strategic intelligence.

Experience the power of Gemini in your ad account. Try Pace today and let AI handle the heavy lifting.