Monroya.ai
Turning AI visibility into continuous verified actions
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Monroya.ai - Turning AI visibility into continuous verified actions

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AI isn't just changing search—it's changing how buyers choose vendors. Monroya.ai helps you understand what AI says about your business, why competitors are recommended instead, and what actions actually improve your visibility. Every verified optimization builds a smarter, evidence-based playbook unique to your company, so you're not guessing how to win in AI search—you're measuring it continuously.

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Maker
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Every conversation about AI search seemed to focus on rankings and mentions. But that's not how buyers think. When someone asks ChatGPT, Claude, Gemini, or Perplexity for the best CRM, cybersecurity platform, or marketing agency, they're not looking at search results—they're looking at recommendations. We realized companies had no way to understand why AI recommended one brand over another, or what they could do to improve those recommendations. That felt like a much bigger problem than simply tracking mentions. So we built Monroya.ai to help companies understand their entire AI buyer journey—not just whether they're visible, but how AI evaluates and recommends them. What problem are you trying to solve? Marketing teams are entering a new world where AI assistants are becoming the first stop in the buying process. The challenge is that most companies have no idea: What AI is saying about their brand Which competitors are being recommended instead Which sources AI appears to trust What changes actually improve visibility over time Most tools stop at reporting. We wanted to build a platform that helps companies move from observation to optimization. Instead of asking, "Did our mentions go up?" The better question is: "What should we do next, and did it actually work?" 🚀 How did your approach evolve while building Monroya.ai? Our first prototypes looked a lot like everyone else's. Dashboards. Charts. Mention tracking. The more customer interviews we did, the more we realized reporting wasn't the real problem. People didn't want another dashboard. They wanted direction. That changed everything. Today, Monroya.ai doesn't just surface AI visibility—it prioritizes actions, recommends when to validate them, and helps companies build an evidence-based playbook from what actually improves their results. We're also being intentional about what we don't claim. If something hasn't been verified, we don't present it as fact. Recommendations become stronger as more evidence is gathered, because trust matters more than flashy metrics. We think AI optimization will become one of the biggest categories in marketing over the next few years, and we want Monroya.ai to help define what "good" looks like. I think that's what makes Monroya.ai different. It's not another AI visibility dashboard. It's an optimization platform designed to answer the question every marketer eventually asks: "Now that I know where I stand... what should I do next?"

Turning AI visibility into verified actions sounds more useful than another monitoring dashboard. What qualifies as a verified action?

Maker

Hi  

Fair to ask, since "verified action" could mean a lot of things if I don't define it.

Concretely: we don't just say "publish an FAQ page" and call it done. We flag the specific prompt where you're absent, recommend a specific content change tied to that prompt, then recommend when to re-scan that exact prompt (as certain actions take longer to show up then others) to check if it moved — cited, named, or neither. If it didn't move, we say so, and that becomes new information rather than a quiet miss.

So "verified" means: recommendation → change made → re-scanned against the same prompt → outcome logged, not assumed. If we haven't re-scanned yet, we show it as pending, not resolved.

Maker

A few people have asked what makes different from the other AI visibility tools launching right now — fair question, since there are a lot of us.

Here's the honest answer: most tools in this space, including our early prototypes, stop at reporting. You see a number, a mention count, a citation rate. What you don't get is whether anything you do about it actually works.

We built around a different question: not "did our mentions go up," but "what should we do next, and can we prove it worked."

That means two things in practice:

  1. Every recommendation ships with a way to verify it — we don't hand you a generic content checklist, we track whether the specific change moved the specific number.

  2. If something hasn't been verified yet, we say so. We'd rather show you "unverified" than dress up a guess as a fact. In a category full of confident-sounding dashboards, we think that honesty is the actual differentiator.

Happy to go deeper on how the verification loop works if anyone's curious — genuinely think this is the part of AI visibility tooling most people are skipping right now.