Case Studies

When tourists arrive on Ko Lanta's pristine beaches, they're not thinking about medical emergencies. But when someone needs urgent care—maybe a diving injury or a severe sunburn—they're often far from home, don't speak the local language, and need help fast. The clinic had a solid local reputation, but international visitors weren't finding them. Traditional search results were dominated by larger hospitals in Phuket, even though the clinic was closer and perfectly equipped for tourist medical needs. By publishing the clinic to public knowledge graph infrastructure with precise coordinates and location data, we made it discoverable in a way that actually matters: when someone asks ChatGPT "Where can I get medical help near Ko Lanta?" the clinic now appears in the answer. The structured data helps AI systems understand this isn't just any clinic—it's specifically located on the island, making it the practical choice for travelers who can't easily reach mainland facilities.

Forest Lake is one of those growing suburbs where new families are moving in faster than infrastructure can keep up. The clinic serves a community that's increasingly tech-savvy—parents who ask Siri where to find a pediatrician, or use ChatGPT to research local healthcare options. The problem? When people searched for "medical clinic near me" through AI assistants, they were getting recommendations for big hospital systems in Minneapolis, 30 minutes away. The clinic was invisible, even though it was right in their neighborhood. We published the clinic with complete geographic data—not just the address, but coordinates that AI systems use for location-based reasoning. Now when someone asks about healthcare in Forest Lake, the clinic appears because AI can actually understand where it is relative to the searcher. It's not about keywords anymore—it's about being in the knowledge graph that AI systems query.

Palo Alto is ground zero for people who live and breathe technology. The patient base here doesn't just use AI assistants—they work at the companies building them. When they need healthcare, they're asking ChatGPT or Claude, not scrolling through Google results. The clinic was competing against Stanford's massive healthcare system and dozens of other providers. In traditional SEO, that's an uphill battle. But in AI-powered search, it's different—if you're properly represented in the knowledge graphs that AI systems use, you can compete on equal footing. We structured the clinic's data so AI systems could understand its location, services, and context within Palo Alto's healthcare ecosystem. The result? When tech workers ask AI assistants about local medical services, the clinic appears alongside the big players. Being in the knowledge graph infrastructure means being in the same structured knowledge base that AI systems query to answer questions.

Rose Law Firm has been a fixture in Little Rock for decades. They've built their reputation the traditional way: word of mouth, community involvement, and consistent results. But they noticed something changing—fewer people were calling after finding them on Google. More potential clients were asking friends, "What did ChatGPT say when you asked about lawyers in Little Rock?" The firm realized that as search behavior shifts toward AI assistants, they needed to be where AI systems look for information. Traditional websites and directories aren't enough anymore—AI systems query structured knowledge graph infrastructure. By publishing the firm to public knowledge graphs with proper legal industry classification and location data, we ensured they'd be discoverable when people ask AI assistants about legal services in Arkansas. The firm's established reputation now extends into the AI era—when someone needs legal help in Little Rock, AI systems can recommend them based on structured knowledge, not just web page rankings.

Strom Law Firm specializes in areas like personal injury and workers' compensation—practice areas where people often need help urgently and don't have time to research extensively. These potential clients are increasingly turning to AI assistants with questions like "What should I do after a car accident in South Carolina?" or "How do I find a workers' comp lawyer?" The firm needed to be part of those conversations. But if they weren't in the knowledge graphs that AI systems query, they were missing out on these high-intent inquiries. We published the firm with comprehensive data linking it to South Carolina's legal system and geographic entities. Now when someone asks an AI assistant about legal services in Columbia, the firm appears because the AI can reason about location, practice areas, and jurisdiction—all structured in the knowledge graph. It's not about being the first result on Google anymore—it's about being in the knowledge base that AI uses to answer questions.

The Detroit metro area has no shortage of law firms, and competition for visibility is fierce. The Sam Bernstein Law Firm had built a strong local presence, but they were concerned about staying visible as more people use AI assistants instead of traditional search. The firm's leadership understood that AI assistants work differently—they synthesize information from knowledge graphs, not just rank websites. If the firm wasn't in those knowledge graphs, they'd be invisible to a growing segment of potential clients. We published the firm with precise location data and proper linking to Michigan's legal and geographic entities. The structured data enables AI systems to include the firm when answering questions about legal services in Farmington Hills or the broader Detroit area. It's a different kind of visibility—not about ranking higher, but about being part of the structured knowledge that AI systems use to provide answers.

Alanya attracts property buyers from all over the world—Germans, Russians, Brits, Scandinavians. These international buyers often start their search by asking AI assistants in their native language: "Where should I buy property in Turkey?" or "What's the real estate market like in Alanya?" The agency had a great website and strong local presence, but they were missing these international inquiries because they weren't in the knowledge graphs that AI systems query across languages. We published the agency with location coordinates and proper geographic linking, making it discoverable when AI systems answer questions about real estate in Alanya. The structured data works across languages—when someone asks in German or Russian, AI systems can still find the agency because location and industry data are universal in knowledge graphs. It's opened up a new channel of international inquiries they weren't reaching before.

The Australian property market moves fast, and buyers are increasingly using AI assistants to research markets, neighborhoods, and agencies before they even start looking at listings. Stone Real Estate noticed that when people asked AI assistants about real estate in Australia, they weren't appearing in the answers. The agency realized that being discoverable in AI-powered search isn't just about having a good website—it's about being in the knowledge graph infrastructure that AI systems use to answer questions. If you're not in the structured knowledge bases that AI systems query, you're not in the conversation. We published the agency with comprehensive location and industry data, linking it to Australia's geographic and real estate entities. Now when someone asks an AI assistant about real estate agencies in Australia, Stone Real Estate appears because the AI can reason about their location and services from structured knowledge. It's a fundamental shift—from competing on website rankings to being part of the knowledge base that AI uses.

Cronulla is a competitive Sydney suburb where every real estate agency is fighting for visibility. Highland Property had built a strong local reputation, but they were concerned about staying relevant as property buyers increasingly use AI assistants to research neighborhoods and find agencies. The agency's leadership saw that AI assistants work differently from traditional search—they synthesize information from knowledge graphs. If Highland Property wasn't in those knowledge graphs, they'd miss out on these high-intent inquiries. We published the agency with precise location coordinates and complete address data, linking it to geographic entities within the knowledge graph ecosystem. The structured data enables AI systems to include Highland Property when answering questions about real estate in Cronulla or the Sutherland Shire. It's not about outranking competitors on Google anymore—it's about being in the structured knowledge infrastructure that AI systems use to provide answers. When someone asks about property in Cronulla, the agency appears because the AI can reason about their location from the knowledge graph.