Structured Data & Semantic Schema
Make your content legible to machines and models.
Where your brand shows up in AI.
Measure how the major assistants cite and represent your brand week over week — then optimize what they cite and catch what they get wrong.
- Cited mentions tracked across the major LLMs
- Competitor benchmarks + week-over-week deltas
- Hallucination + misrepresentation alerts
Public large language models like ChatGPT, Claude, and Gemini learn from the open web—but they don't understand it unless it's structured. At LLM.co, we help your brand speak the language of machines through properly implemented semantic data and schema markup. The result? Your brand is more findable, more accurately represented, and more likely to be cited or surfaced by AI across the internet.
Why Structured Data Matters for LLM Visibility
Structured data (like schema.org markup) gives AI models the context they need to understand who you are, what you offer, and why it matters. It's the difference between being mentioned vaguely and being accurately cited.
Better structured data leads to:
Accurate Brand Attribution – Proper structured data ensures your brand is clearly defined, making it far more likely that platforms like ChatGPT, Bard, Claude, and Perplexity correctly attribute quotes, summaries, and mentions to your business.
Increased Citation Likelihood – Structured data enhances clarity and authority by reinforcing your content's context, improving the chance that your articles, product pages, or executive bios are selected as reference sources in model responses.
Reduced Hallucinations – By disambiguating people, places, and entities through schema markup, you lower the odds of hallucinated facts and help AI systems generate responses grounded in truth.
Better LLMO – Structured data lays the foundation for effective LLMO by signaling clean entity relationships, authoritative context, and semantic clarity.
Cross-Platform Recognition – Structured data—especially with SameAs links and brand entities—helps establish your digital footprint across platforms.
Improved AI Agent & Voice Searches – Structured data is essential for voice agents like Alexa, Siri, and Google Assistant.
Schema Implementation
We set up and validate the appropriate schema.org types for your site—Organization, Person, Product, Article, Review, LocalBusiness, FAQ, and more—using clean JSON-LD that speaks directly to LLM crawlers and Google's Knowledge Graph.
Entity Disambiguation
If your brand shares a name with other companies or your CEO is often confused with others online, we fix that. Our markup and linking strategies clarify who's who—and help AI get it right.
SameAs + Knowledge Graph Connectivity
We link your brand, people, and products to authoritative third-party sources like Wikidata, LinkedIn, Crunchbase, and GitHub.
Schema Audit & Repair
Already using structured data but unsure if it's helping? We'll audit your current markup, identify errors, suggest enhancements, and implement improvements.
Semantic Content Structuring
Beyond code, we structure your content's hierarchy—headings, metadata, internal linking—for better machine readability.
Our Structured Data Methodology
Entity Mapping – We define your core brand entities—people, products, services, content assets, and relationships—to ensure complete, correct representation.
Schema Strategy – Based on your goals, we select the most appropriate schema types and extensions to target both LLMs and traditional search engines.
Implementation & Validation – We write, test, and validate schema using tools like Google's Rich Results Test, Schema.org guidelines, and model-specific parsing behavior.
Knowledge Graph Integration – We connect your entities to trusted public databases to strengthen their semantic identity.
Testing & Monitoring – We track downstream effects in AI platforms, search engines, and citation visibility—adjusting as needed.
Why LLM.co?
At LLM.co, we bring together deep expertise in SEO, large language model behavior, and structured data implementation to deliver one unified goal: helping AI understand your brand with precision. Unlike one-size-fits-all schema plugins, our approach is built on real-world application and technical depth.
Whether you're a fast-scaling SaaS company, a global media brand, or a founder looking to protect and project your digital identity, we make sure public LLMs like ChatGPT, Claude, and Gemini represent you correctly, consistently, and authoritatively—across platforms and across time.
Common questions
01How is this different from regular SEO schema?
Traditional SEO schema is aimed at search engines. Our structured data work is engineered with AI/LLM parsing in mind—adding disambiguation, authoritative linking, and deeper entity definition.
02Will this help me show up in ChatGPT and other LLMs?
Yes—while you can't 'rank' in ChatGPT like Google, structured data increases your chances of being cited, referenced, or correctly summarized by the model.
03How long until I see results?
Initial changes in crawlability and representation can occur within a few weeks. Ongoing refinement may take 30–90 days depending on model retraining and data exposure.
04What if I already have schema on my site?
We'll audit it. Most implementations are incomplete, incorrect, or don't speak to modern LLM requirements. We'll improve what you have and expand it as needed.
Private AI On Your Terms
Tell us your use case and constraints — on-prem, cloud, or edge — and we'll map a compliant deployment within one business day.
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