Geostar pioneers GEO as traditional SEO faces 25% decline from AI chatbots, Gartner says
The moment Mack McConnell knew everything about search had changed was last summer, during the Paris Olympics. His parents had turned to him independently and without any reason ChatGPT to plan their daily activities in the French capital. The AI recommended specific travel companies, restaurants and attractions – companies that had won a new kind of visibility lottery.
“It was almost like this intuitive interface that older people were as comfortable with as younger people,” McConnell recalled in an exclusive interview with VentureBeat. “I could just see that the companies were now being recommended.”
That observation has now become the basis Geostera Pear VC-backed startup committed to helping businesses navigate what may be the most significant change in online discovery since Google’s founding.
The company, which recently emerged from stealth with impressive early customer acquisition, is betting that the rise of AI-powered search presents a major opportunity to reinvent how businesses are found online. The global AI search engine market alone is expected to grow from $43.63 billion in 2025 to $108.88 billion in 2032.
Already the fastest growing company in PearX’s newest cohortGeostar is quickly approaching $1 million in annual recurring revenue in just four months – with just two founders and no employees.
Why Gartner predicts traditional search volume will decline by 25% by 2026
The numbers tell a grim story of disruption. Gartner predicts that traditional search engine volume will fall by 25% by 2026largely due to the rise of AI chatbots. Google’s AI overviews now appear billions of searches monthly. Researchers at Princeton University have found that optimizing these new AI systems can increase visibility up to 40%.
“Search used to mean making Google happy,” McConnell explains. “But now you have to optimize for four different Google interfaces – traditional search, AI mode, Gemini and AI overviews – each with different criteria. And on top of that, ChatGPT, Claude and Perplexity each work differently.”
This fragmentation creates chaos for companies that have spent decades perfecting their Google search strategies. A recent one Forrester study found that 95% of B2B buyers plan to use generative AI in future purchasing decisions. Yet most companies remain woefully unprepared for this shift.
“Anyone who isn’t on this now is losing,” said Cihan Tas, co-founder and Chief Technology Officer of Geostar. “We’re seeing lawyers now getting 50% of their clients through ChatGPT. It’s such a huge shift.”
How language models read the internet differently than search engines once did
What Geoster and a growing number of competitors calling Generative Engine Optimization, or GEO, represents a fundamental departure from traditional search engine optimization. While SEO focused primarily on keywords and backlinks, GEO requires an understanding of how large language models parse, understand, and synthesize information across the Internet.
The technical challenges are formidable. Every website must now function as what Tas calls “its own little database,” which can be understood by dozens of different AI crawlers, each with unique requirements and preferences. Google’s systems draw from their existing search index. ChatGPT relies heavily on structured data and specific content formats. Perplexity shows a clear preference for Wikipedia and authoritative sources.
“Now the strategy is actually concise and clear and answers the question, because that’s directly what the AI is looking for,” Tas explained. “You’re actually tuning into a somewhat intelligent model that makes decisions in the same way we make decisions.”
Consider schema markup, the structured data that helps machines understand web content. Although only 30% of websites currently implement a rich schema, research shows that properly formatted pages are 36% more likely to appear in AI-generated summaries. Yet most companies don’t even know what schema markup is, let alone how to implement it effectively.
Within Geostar’s AI agents that continuously optimize websites without human intervention
Geostar’s solution embodies a broader trend in enterprise software: the rise of autonomous AI agents that can take action on behalf of companies. The company integrates what it calls “environmental agents” directly into customer websites, continuously optimizing content and technical configurations and even creating new pages based on patterns learned across the customer base.
“Once we learn something about the way content is performing, or the way a technical optimization is performing, we can propagate that same change to the rest of the users so that everyone in the network benefits,” McConnell said.
For RedSifta cybersecurity company, this approach delivered a 27% increase in AI mentions within three months. In one case, Geostar identified an opportunity to rank for “top DMARC vendors,” a high-value search term in email security. The company’s agents created and optimized content that achieved a first-page ranking on both Google and ChatGPT within four days.
“We’re doing the work of an agency that charges $10,000 a month,” McConnell said, noting that Geostar’s prices range from $1,000 to $3,000 a month. “AI creates a situation where for the first time you can take action as an agency, but you can scale as software.”
Why linkless brand mentions matter now more than ever in the AI age
The implications of this shift extend far beyond technical optimizations. In the SEO era, a listing without a link was essentially worthless. In the age of AI, that calculus has been reversed. AI systems can analyze vast amounts of text to understand sentiment and context, meaning brand mentions on Reddit, in news articles, or on social media now directly influence the way AI systems describe and recommend companies.
“If the New York Times mentions a company without linking to it, that company would actually benefit in an AI system,” McConnell explains. “AI has the ability to do massive analysis of large amounts of text, and will understand the sentiment surrounding that mention.”
This has created new vulnerabilities. Research from the Indian Institute of Technology and Princeton has found that AI systems show a systematic preference for third-party sources over brand-owned content. A company’s own website may have less influence in shaping the perception of AI than what others say about it online.
The changing landscape has also disrupted traditional measures of success. Where SEO focused on rankings and click-through rates, GEO must consider what researchers call impression metrics: how prominently and positively a brand appears in AI-generated responses, even if users never click through to the source.
A growing market as SEO veterans and new players rush to dominate AI optimization
Geostar is certainly not the only one who sees this opportunity. Companies like it Firelight, In depthAnd Good are all racing to help businesses navigate the new landscape. The SEO industry, worth approx $80 billion worldwideis trying to adapt, while established players like Semrush and Ahrefs rush to add AI visibility tracking features.
But the company’s founders, who previously built and sold a Y-Combinator-backed e-commerce optimization startup called Montobelieve that their technical approach gives them an edge. Unlike competitors who largely provide dashboards and recommendations, Geostar’s agents actively implement changes.
“Everyone is using the same solutions that have worked in the past era and just saying, ‘We’ll do this for AI instead,’” McConnell argued. “But when you think about what AI is really capable of, it can actually do the work for you.”
The stakes are high, especially for small and medium-sized companies. While large companies can afford to hire specialized consultants or build in-house expertise, smaller companies risk becoming invisible in AI-mediated searches. Geostar sees this as its biggest market opportunity: Nearly half of America’s 33.2 million small businesses are investing in SEO. Of the roughly 418,000 law firms in the U.S., many are spending money between $2,500 and $5,000 monthly on search optimization to stay competitive in local markets.
From Kurdish village to PearX: the unlikely partnership building the future of search
For Tas, whose journey to Silicon Valley began in a small Kurdish village in Turkey with a population of just fifty, the current moment represents both opportunity and responsibility. His mother’s battle with cancer prevented him from completing college, leading him to teach himself how to code and eventually team up with McConnell — whom he worked with for an entire year before they ever met in person.
“We’re not just copying and pasting a solution that already existed before,” Tas emphasized. “This is something that is different and uniquely possible today.”
Looking ahead, search’s transformation appears to be accelerating rather than stabilizing. Industry observers predict that search functionality will soon be embedded in productivity tools, wearables and even augmented reality interfaces. Each new surface will likely have its own optimization requirements, further complicating the landscape.
“Soon the search will be in our eyes and in our ears,” McConnell predicted. “When Siri breaks out of her prison, what Jony Ive and OpenAI build together will be a multimodal search interface.”
The technical challenges are accompanied by ethical challenges. As companies do their best to influence AI recommendations, questions arise about manipulation, fairness and transparency. There is currently no regulatory body or established best practices for GEO, creating what some critics describe as a Wild West environment.
As companies grapple with these changes, one thing seems certain: the era of simply optimizing for Google is over. Instead, a much more complex ecosystem is emerging in which success requires us to understand not only how machines index information, but also how they think about it, synthesize it, and ultimately decide what to recommend to people looking for answers.
For the millions of companies whose survival depends on online discovery, mastering this new paradigm isn’t just an opportunity – it’s an existential necessity. The question is no longer whether to optimize for AI search, but whether companies can adapt quickly enough to remain visible as the pace of change increases.
McConnell’s parents at the Olympics were a preview of what is already becoming the norm. They didn’t look for tour companies in Paris. They didn’t scroll through the results or click on links. They simply asked ChatGPT what to do – and the AI decided which companies deserved their attention.
In the new economy of discovery, the companies that win won’t be the ones that score the highest. They are the ones AI wants to recommend.
