How to replace Boolean search with AI curation

If you've ever spent an afternoon adjusting a Boolean search string, only to find your monitoring is still pulling in irrelevant articles, you know the frustration.

Add a keyword. Exclude a phrase. Adjust the logic. Run the search again. You might get closer, but there's usually more cleanup waiting on the other side.

The problem isn't necessarily your search. Keywords can find the right words without understanding whether an article actually matters to your organization.

AI curation takes a different approach. Instead of building increasingly complicated search strings, you can define what matters in plain language and let AI help evaluate and organize the coverage.

Here's what that shift looks like in practice.

1. Start with what you're actually trying to track

Before changing anything, take a look at the searches you're already using.

Maybe you're tracking a product launch, keeping an eye on competitors or trying to see how often your executives appear in industry coverage.

Whatever the goal, it's worth asking whether your current searches are giving you what you need.

It also helps to pull a few examples of articles you'd include and a few you'd leave out. Think about why each one belongs in your monitoring or not.

You don't need to redo everything at once. Start by getting clear on what you actually need your monitoring to tell you.

2. Explain what matters instead of listing keywords

When you're launching a new product, you want to know more than how many articles mention its name. You want to understand who's covering it, how it's being described and whether the conversations you care about are gaining traction.

Take Muck Rack's launch of Generative Pulse, our AI visibility solution that helps PR teams understand how their brands appear in AI-generated answers.

For a launch like this, the communications team might want to track product announcements, coverage comparing AI visibility solutions, commentary from company spokespeople and broader conversations about generative engine optimization (GEO).

This is a simplified example, not Muck Rack's actual monitoring setup.

The search might capture some relevant coverage, but it could also miss articles that use different terminology. Or it might bring in a story where Muck Rack is mentioned briefly but the topic has little to do with AI visibility.

Now think about how you'd explain the same monitoring goal to a colleague.

You'd probably describe the coverage you care about, the competitors and topics you want to follow and the stories that shouldn't count.

That's the difference. The Boolean string tries to anticipate which words will appear. The plain-language version explains what the team actually wants to understand.

And that's the thinking behind AI curation.

A simple template to try

When defining relevance for your own organization, think about three things.

These examples are meant to help you think through your monitoring priorities, not serve as instructions to paste directly into a product.

With Muck Rack's Curation Engine, that organizational context helps determine whether incoming coverage is relevant. Articles are marked Approved or Rejected, and Muck Rack's Media Intelligence team helps set up and refine the curation process.

3. Add the context you'll need when it's time to report

Getting the right articles is a good start. But once you've found them, what else do you need to know?

For our Generative Pulse example, we'd probably want to understand how the product is being portrayed, whether it's the focus of the story and which competitors or spokespeople are mentioned alongside it.

That's where sentiment, prominence and tags come in.

Sentiment helps us understand how Generative Pulse is portrayed within an article, whether that's Positive, Negative, Neutral or Balanced.

Prominence helps distinguish stories focused on Generative Pulse from broader AI industry coverage where the product gets only a passing mention.

Tags let us organize coverage by things like competitor products, spokespeople and key messages.

Curation Engine evaluates sentiment at the entity level, classifies prominence as Primary, Significant or Passing and automatically applies tags based on what matters to the organization.

Once those details are captured consistently, it's easier to understand what's happening across your coverage without manually sorting everything before every report.

4. Check whether the results actually make sense

Moving beyond Boolean doesn't mean you stop checking your monitoring.

AI can help evaluate coverage, but it still needs the right context to work with.

Once you have a more structured set of results, take a look at what you're getting:

• Relevance: Are these actually the articles you want to track?
• Sentiment: Does the classification match how your brand is portrayed?
• Prominence: Is your brand the focus of the story or just mentioned in passing?
• Tags: Are the right products, competitors, spokespeople and messages being captured?

Pick a few articles from your results and compare them with the priorities you defined at the start. For example, if our Generative Pulse monitoring keeps pulling in unrelated Muck Rack coverage, that's a sign we may need to revisit how relevance is defined.

This is also where the human side matters.

Curation Engine combines AI-powered analysis with Muck Rack's Media Intelligence team, which helps configure and refine the system around each organization's needs.

The goal isn't to take PR professionals out of the process. It's to give them more time to focus on the work that actually needs their expertise.

Less time searching, more time understanding

Replacing Boolean isn't just about writing a better prompt. It's about defining what matters to your organization and using that context to get coverage that's relevant, organized and ready for analysis.

That means less time maintaining searches and cleaning up results, and more time understanding what your coverage is actually telling you.

Want to see what this looks like in practice? Explore Curation Engine to learn how Muck Rack turns media coverage into structured, analysis-ready intelligence.