How Netsleek Is Redefining Digital Discoverability for the AI Era

Search isn’t disappearing.

But the way people discover organizations is changing.

For years, businesses have measured digital success by familiar benchmarks: higher rankings, stronger keyword performance and increased website traffic. Those metrics still matter. According to Ruan Masuret and Juanita Martinaglia, however, they’re no longer the only indicators of whether an organization will be discovered in an AI-driven world.

“One of the biggest changes we’ve noticed is that AI is increasingly sitting between organizations and the people trying to find them,” the Netsleek co-founders said. “For a long time, search engines mainly helped people navigate the web. You searched for something, received a list of links and decided for yourself which websites you trusted enough to visit. Today, AI is beginning to take on more of that interpretation itself.”

It’s a subtle shift, but one they believe changes the relationship between organizations and their audiences in a fundamental way.

Instead of simply returning webpages, AI systems are increasingly bringing information together from multiple sources, interpreting it and presenting users with synthesized answers. In many cases, those systems are also deciding which organizations deserve to be included, cited or recommended.

“That changes the role of search quite significantly because discovery becomes less about finding information and more about evaluating it.”

That realization didn’t happen overnight.

“There wasn’t a single moment where we looked at each other and said, ‘This changes everything.’ It was something we started noticing gradually over time.”

Working in digital marketing and SEO, Masuret and Martinaglia repeatedly encountered organizations with technically sound websites, quality content and strong search visibility that weren’t consistently appearing in AI-generated responses. At the same time, they noticed other organizations surfacing prominently in AI answers, even when traditional ranking signals alone didn’t seem to explain why.

“That really sparked our curiosity. We kept asking ourselves what AI systems were actually evaluating beyond rankings. What was influencing whether an organisation was included, cited or recommended?”

Those questions became the foundation of Netsleek.

The founders weren’t interested in declaring SEO obsolete. In fact, they continue to emphasize that traditional SEO remains essential. Strong technical foundations, quality content and well-structured websites still form part of the broader discovery ecosystem. What interested them was the layer beyond those fundamentals—the one that seemed to influence how AI systems interpreted organizations before deciding whether to include them in a response.

As their research progressed, one idea became increasingly clear: the language surrounding search was no longer fully capturing what they were observing.

“We found ourselves talking less about rankings and more about discoverability. Visibility asks whether people can find your website. Discoverability asks whether AI systems can clearly understand who you are, what you do, where you operate and whether there is enough confidence in the available information to understand your organisation accurately and surface it when you’re genuinely relevant.”

That distinction sits at the heart of Netsleek’s philosophy.

For decades, digital marketing has focused on helping organizations become visible. AI Search introduces another challenge: helping intelligent systems develop enough confidence to understand an organization accurately in the first place.

That thinking eventually led to one of Netsleek’s original contributions to the AI Search conversation: The Selection Layer framework in AI Search.

“The Selection Layer framework in AI Search really grew out of the questions we kept asking ourselves during our research. We understood how information could be retrieved, but retrieval alone didn’t seem to explain why some organisations were consistently appearing in AI-generated answers while others weren’t.”

The framework proposes a simple but important distinction. Retrieving information and selecting information are not necessarily the same process. An AI system may identify hundreds of relevant organizations for a particular topic, yet only a small number ultimately appear in the answer presented to a user.

“Somewhere between retrieval and the answer itself, there appears to be an evaluation process that determines which organisations are sufficiently relevant, trustworthy and contextually appropriate to include, cite or recommend. Our framework refers to that conceptual stage as the Selection Layer.”

The idea naturally led the founders toward another area of research: trust.

“One of the things we’ve become increasingly interested in through our research is the difference between information simply existing online and information that appears to give AI systems confidence. Those aren’t necessarily the same thing.”

Rather than searching for a single ranking factor or universal trust signal, Masuret and Martinaglia describe confidence as something that develops from the overall consistency of an organization’s digital presence.

“We don’t believe there’s a single trust signal or a checklist that guarantees visibility in AI Search. Different AI systems almost certainly evaluate information differently, and their approaches will continue to evolve. From our perspective, confidence appears to develop from the overall consistency and quality of information available about an organisation rather than from any one individual factor.”

That perspective shifts the conversation away from isolated optimization tactics and toward something much broader. Editorial coverage, structured information, independent references and corroboration across multiple trusted sources all contribute to how AI systems build confidence and understanding.

The founders often compare it to how people make decisions in everyday life. A business can describe its own expertise, but credibility is strengthened when respected third parties consistently reinforce that same story. They believe AI systems are increasingly developing confidence in much the same way.

That is also why Netsleek places such a strong emphasis on entity clarity and semantic content architecture. While those concepts may sound technical, their purpose is remarkably practical: helping AI systems reduce ambiguity.

“The easier an organisation is to understand, the easier it becomes for AI systems to connect the right information, develop confidence in what they’re seeing and accurately represent that organisation when it’s genuinely relevant.”

For larger organizations, that challenge becomes even more significant.

Years of acquisitions, archived websites, product launches, leadership changes and independent media coverage often create enormous digital footprints that have been developed over decades. Human readers can usually distinguish between outdated information and current messaging. AI systems don’t always have that same context.

Rather than encouraging organizations to simply publish more content, Masuret and Martinaglia suggest that many businesses may benefit from improving the clarity, consistency and connectedness of information that already exists across their digital ecosystem.

The founders’ collaborative approach reflects that same philosophy.

Martinaglia’s background in digital marketing, SEO and content strategy continually asks how emerging ideas translate into practical business outcomes. Masuret approaches many of the same questions from a research and systems perspective, exploring the broader mechanics shaping AI-mediated discovery.

Together, those perspectives create a continuous cycle where research informs client strategy, and real-world implementation raises new questions that drive future research.

“We don’t see research and client work as separate activities. They continually inform one another.”

That mindset has also influenced Netsleek’s research into WebMCP and what the founders describe as the emerging agentic web.

Historically, websites have been built primarily for people. Looking ahead, Masuret and Martinaglia believe organizations will increasingly need to consider how those same websites communicate with intelligent AI systems capable of retrieving information, comparing services and potentially completing tasks on behalf of users.

“We don’t see this as replacing websites. If anything, we think websites become even more important.”

Rather than serving only as destinations for human visitors, they believe websites will increasingly function as trusted digital interfaces for both people and AI systems.

Throughout the conversation, one message surfaced again and again.

The future of AI Search isn’t about abandoning the fundamentals.

It’s about expanding them.

“The first thing we’d encourage organisations to do is recognise that AI Search isn’t simply another marketing channel. It’s changing the way people discover, evaluate and engage with businesses, and that means it’s becoming a broader business consideration rather than just a marketing one.”

For organizations wondering where to begin, the founders offer surprisingly practical advice.

Look beyond rankings.

Ask whether an AI system looking across everything publicly available about your organization would develop a clear, accurate and consistent understanding of who you are. Consider whether your information is reinforced by credible third-party sources. Evaluate whether your digital footprint reduces ambiguity—or creates it.

Those, they suggest, are becoming some of the most important strategic questions organizations can ask.

Technology will continue to evolve. AI platforms will change. New methods of discovery will emerge.

But Masuret and Martinaglia believe one principle will remain.

“Ultimately, we think the future belongs to organisations that invest in being genuinely understood. Technology will continue to evolve, AI platforms will change and new ways of discovering information will emerge, but organisations that are clear, credible, well-corroborated and consistently understood will always be in the strongest position to earn trust from both people and AI systems.”

Perhaps that’s the most compelling takeaway from Netsleek’s research.

The future of digital discoverability isn’t simply about being found.

It’s about being understood.

www.netsleek.com