Citation Stack, step 2
Technical GEO: schema markup for AI optimization and crawler access
LLMReach fixes the technical signals ChatGPT, Claude, Perplexity and Gemini rely on: crawler access, rendering, schema markup, llms.txt and entity consistency, so your key pages are easier to read and cite.
The gap
AI engines cannot cite what they cannot parse.
- Access: AI crawlers blocked in robots.txt never read the pages you want cited.
- Rendering: Content that only appears with JavaScript may be invisible to crawlers that read the raw HTML.
- Entity: An entity described differently across the web is harder for a model to recognise and repeat.
- Foundation: Strong SEO can sit on top of weak AI readiness. The technical layer is where many citations are lost before content or authority even come into play.
Google says its AI features have no additional technical requirements, and OpenAI says sites opted out of its search crawler will not be shown in ChatGPT search answers. If a crawler cannot read a page, it cannot be cited.
Our own results
We do this for our own brand first.
Gemini · Named
“best agency for getting cited in LLMs”
ChatGPT · Named
“agency that gets you cited in AI models”
ChatGPT · Named
“best agency for getting cited in LLMs”
AI answers vary by platform and moment, so these show the method working on those days, not a promise of identical answers.
See all resultsWhat's included
Everything an assistant needs to read your site.
Start with the free AI audit. You leave with a clear roadmap, and if you decide to move forward, the work can expand into a full GEO engagement. If not, you still keep the data.
- A technical GEO audit of AI crawler access, rendering, schema and entity signals
- An llms.txt file that explains your brand and key pages to AI systems
- Schema markup for AI: Organization, Service, FAQPage, Article and BreadcrumbList where relevant
- robots.txt configured for the AI crawlers that matter in your category
- A rendering review, so key content is in the raw HTML
- Entity signal cleanup across your site and main profiles
- A sitemap that puts your most important pages first
- Monitoring that catches technical regressions early
How it works
Technical GEO best practices, in order of impact.
- 01
Prompt research
We agree the buyer prompts that matter, so technical work starts with the pages those prompts should reach.
- 02
Technical optimization
Crawler access, llms.txt, schema, rendering and sitemaps, fixed in order of impact, directly or as a specification for your developers.
- 03
Content
Pages restructured so the answer comes first and each claim can be extracted on its own.
- 04
Reddit authorityResearch into the communities assistants draw on, so the facts on your site match what buyers read elsewhere.
- 05
Visibility tracking
Crawl access, schema health and citations monitored against a baseline taken before work begins.
This service is one of five steps in the Citation Stack. Fixed access with no content worth citing, or good content on a site assistants cannot read, both stall. We can implement directly or work with your development team.
Who this is for
Built for brands ready to fix the foundation.
The work pays off where your content is worth citing but your site makes it hard for AI systems to read. LLMReach tracks mentions, citations, share of voice, cited URLs, sentiment, position and competitor visibility across AI answers. Optimization recommendations come from that data, and the Citation Stack is measured end to end. The sources give no published outcome figures for this step.
Not for you
If any of these are you.
- You expect results in a few weeks
- You can't give us or your developers site access
- You only want a one-off checklist
- Your site is about to be rebuilt from scratch
For you
If this is you.
- Your content is good but rarely cited
- Your site relies on JavaScript or a complex CMS
- You want the work done for you, not another report
- You're ready to commit to a 90-day window
FAQ
Questions about technical GEO.
What is the technical side of GEO?
Technical Answer Engine Optimization is the set of technical signals that help AI engines understand, access and cite your site. It covers llms.txt, schema markup, crawler access, entity consistency, rendering fixes and sitemap prioritization, so your most important pages are easier to extract and cite.
Can AI crawlers execute JavaScript?
AI crawlers may not read JavaScript-dependent content reliably. If important content only appears after JavaScript runs, server-side rendering makes it available in the raw HTML response, where crawlers can read it.
What is llms.txt and why does it matter?
llms.txt is a structured file at the root of your site. It explains your brand, services and authoritative pages to AI systems in a machine-readable format, so they do not have to guess.
Which schema markup does LLMReach add for AI?
LLMReach adds Organization, Service, FAQPage, Article and BreadcrumbList schema where relevant. These give AI systems clear, structured facts about your company, your services and each page.
Do I need AI readability work if my SEO is already strong?
Yes. Strong SEO can coexist with weak AI citation readiness. The work addresses the signals AI engines use to parse, classify and cite a brand, which ranking in Google alone does not cover.
Will the changes break my existing site?
No. The changes are additive and designed to improve technical clarity without disrupting the visible site experience, so your pages look and work the same for visitors while becoming easier for AI systems to read.
Can you work with our development team?
Yes. LLMReach can implement the changes directly or provide a technical specification that your development team ships with our guidance. The work covers crawler access, llms.txt, schema, rendering and sitemaps, fixed in order of impact.
How does fixing AI readability connect to the rest of the Citation Stack?
Technical optimization sits in the middle of the five-step Citation Stack, after prompt research and before content, Reddit authority and visibility tracking. Prompt research defines the fifty buyer prompts the work is built around. Tracking then measures citations per day across those prompts, so you see whether the technical fixes worked.
Does LLMReach promise a measurable result?
The engagement as a whole is backed by a 30% increase in total citations across your site, measured against your own baseline, within 90 days. If that is not reached, LLMReach keeps working at no charge until it is.
Free AI Audit
See what stops AI engines from reading your site.
You leave knowing where the gap is, what is causing it, and which changes would matter first, whether we work together or not.
What to expect
Audit
Before the call, we run your buyers' questions through ChatGPT, Claude, Perplexity and Gemini.
Map
On the call, we show you where competitors are cited and you are not, and what's causing it.
Decide
An honest read on whether the Citation Stack fits. If it doesn't, you'll hear it on the call.
Don't see a time that works? Email Karim directly: contact@llmreach.ai