ChatGPT recommends my competitor when asked about my industry.
Whoever the LLM trusts as a source gets the recommendation. We make you the trusted source.
Large language models do not rank links — they pick sources to quote. The brands earning those citations now are compounding visibility for years. The ones that wait pay customers to compare them with AI tools that have never heard of them.
LLM citations are the new "rank #1." Whoever the model trusts is the only brand the buyer hears about.
ChatGPT recommends my competitor when asked about my industry.
Whoever the LLM trusts as a source gets the recommendation. We make you the trusted source.
I am invisible to large language models.
Invisibility to LLMs has fixable causes — entity gaps, missing structured data, no authority signals.
My website content does not get cited in AI answers.
Content has to be written for retrieval, not just for human readers. We do both.
I do not even know what data AI uses to answer questions.
There is a real, knowable list. We work the list deliberately.
A buyer asking ChatGPT "best [your service] in Pasig" does not get a list of ten links. They get a paragraph that names two or three businesses with confidence. The model picked those names from a small set of sources it trusted enough to retrieve and cite. If you are not in that set, you are not in the conversation — even if your Google rankings are strong.
LLM SEO is the work of getting into that trusted set. It runs on a specific stack: published content depth that LLMs cannot get elsewhere, schema and entity clarity so the model knows exactly who you are, citation patterns from sources LLMs disproportionately pull from, and content structure built for retrieval (atomic facts, clean headings, embedded citations). The signals are concrete. The work is doable. The window for cheap wins is open right now.
The brands that invest in 2026 will compound through 2030. The brands that wait will spend years catching up to whoever moved first.
For a deeper look at the fundamentals, read my guide to data-driven content — or see Google's helpful content guidelines for the official reference.
Every engagement gets the full LLM retrieval stack — audit, content, entity work, authority signals, and tracking.
Test your brand and priority queries against ChatGPT (live retrieval), Perplexity, Gemini, and Claude to see exactly which sources each LLM reaches for and whether you appear among them.
Restructure key pages so LLMs can chunk and retrieve them cleanly — proper headings, atomic facts per paragraph, citations included, and machine-readable structured data.
Build the entity graph LLMs trust. Wikipedia entries where possible, Wikidata records, schema markup that disambiguates your brand, and NAP consistency.
Earn mentions and citations on the platforms that LLM training data and retrieval engines repeatedly pull from. Not all backlinks are equal here — only specific sources count. Pair this with AI SEO for maximum impact.
LLMs disproportionately cite original research, statistics, and proprietary data. We help you publish the kind of content that becomes a quotable source.
Re-run the audit each month to see whether LLMs are starting to retrieve and cite your content consistently. Pairs with GEO Pasig.
Roughly one in three buyers now uses ChatGPT, Perplexity, Claude, or Gemini somewhere in their research before deciding. That ratio is climbing every quarter. The brands those tools cite get the consideration. The brands they skip do not even enter the comparison set. There is no second-place LLM result — the model picks two or three names and stops.
The unsexy truth: most Pasig businesses are not in any of those name lists. Not because the businesses are bad, but because no one has done the structural work that gets them onto the LLM''s shortlist. The work is technical, slow, and unglamorous. It is also the highest-leverage thing a serious Pasig brand can do in 2026. For more on what Google values, see Schema.org.
I also serve businesses in Makati and Manila, bringing the same senior-level LLM SEO approach to every engagement across Metro Manila.
Real client testimonials and verified portfolio numbers — not stock photos with first-name fictional reviewers.
"I had a fantastic experience working with Joe! They were professional, responsive, and delivered high-quality work on time. I highly recommend them for anyone looking for reliable and skilled web developers and SEO experts."
"Joe really became my huge partner in my local business here in Wisconsin. Truly appreciate his work and support making me one of the top businesses in Green Bay for a very minimal cost."
LLM SEO is the slice of AI SEO focused specifically on how large language models like ChatGPT, Claude, and Gemini retrieve and cite content. AI SEO is the umbrella; LLM SEO is the specialist work for ranking inside the LLM's retrieval and reasoning layer. Most engagements bundle both because the underlying signals overlap, but if your goal is specifically to be quoted by AI assistants, LLM SEO is the right framing.
Two phases. First, training: LLMs are trained on a huge corpus of public web content, which gives them background knowledge. Second, retrieval: when a user asks a question, modern LLMs (ChatGPT, Perplexity, Gemini) retrieve fresh content live and pick which sources to quote. Retrieval favours sources with clean schema, authoritative content depth, original data, and entity clarity. We work both layers — published depth + live retrieval optimisation.
On focused niche queries, yes. LLMs do not always pick the highest-traffic source — they pick the cleanest, most directly relevant source for the specific query. A small Pasig dentist with strong local content can win citations on "best dentist in Ortigas" against a national platform. The work is more about content fitness than domain size.
Both, in that order of priority. The single biggest LLM SEO lever is publishing original information LLMs cannot get elsewhere — primary research, proprietary data, real case studies. Optimising existing content is faster but has a ceiling. Most engagements split: 60% on new authoritative content, 40% on restructuring existing pages for retrieval.
Three to six months for first citations on specific queries. Six to twelve months for consistent recognition. Twelve to eighteen months for displacing entrenched competitors on broad industry queries. The brands that started in 2024 are now seeing compounding citation wins. Starting now is still cheaper than waiting another year. See my case studies for examples of real client results.
Send the form. I will reply within 24 hours with a real LLM retrieval audit — which AI tools cite you, where you are missing, and what to fix in the next 90 days.