> ## Documentation Index > Fetch the complete documentation index at: https://docs.peakmark.cc/llms.txt > Use this file to discover all available pages before exploring further. # Technical GEO: Making Your Site Crawlable and Citable by AI > Peakmark audits and fixes the technical signals affecting AI crawlability and citation likelihood — schema markup, entity clarity, llms.txt, and rendering. You can produce exceptional content, earn placements on every publication AI cites in your category, and build a thriving Reddit presence — and still not appear in AI answers if the technical fundamentals are broken. AI models rely on crawlers to read your site, and those crawlers have to be able to access, render, and extract your content cleanly before any of it can influence what the model says. Technical GEO is the set of on-site signals that determines whether AI crawlers can read your site, whether AI models understand who you are as an entity, and whether your content can be cleanly extracted and cited. Peakmark audits every one of these signals at the start of a managed engagement and addresses any issues before the execution sprints begin. Technical GEO is usually a one-time investment that unlocks the value of everything else. If AI can't read your site, content and PR efforts are less effective. ## What Peakmark audits and fixes ### 1. AI bot crawlability The first question is the most fundamental: can AI crawlers actually reach and read your site? Peakmark checks your `robots.txt` to ensure it doesn't inadvertently block AI crawlers — including GPTBot (OpenAI), ClaudeBot (Anthropic), and Googlebot, among others. It's surprisingly common for `robots.txt` configurations to block these bots, either because the file was last updated before AI crawlers existed or because a blanket disallow was applied without considering the downstream effect on AI visibility. Beyond access, Peakmark verifies that your site loads and renders correctly for bots — not just human visitors. Crawlers don't interact with pages the way a browser does; they need to be able to retrieve your content without relying on user actions. ### 2. Schema and structured data Schema markup is how you communicate the structure of your content directly to machines. Peakmark adds or fixes `Organization`, `Product`, `FAQ`, `HowTo`, and `Article` schema across the pages that matter most, so AI models can understand what each page is about, what kind of content it contains, and how it relates to other entities. Well-implemented structured data reduces the chance of your content being misunderstood or misattributed — and increases the likelihood that AI can extract a clean, citable answer from it. ### 3. Entity and sameAs markup AI models build a picture of your brand as an entity — a coherent identity with properties, relationships, and credibility signals — from everything they've indexed about you across the web. `sameAs` markup helps AI models understand that your website, your Wikipedia page, your LinkedIn profile, your Crunchbase entry, and your other profiles all refer to the same entity. Without it, the model may treat those profiles as separate or unrelated, diluting the trust signal each one provides. Peakmark implements `sameAs` markup and ensures your entity properties (name, description, founding date, industry, location) are consistent and machine-readable across the sources that matter. ### 4. llms.txt `llms.txt` is the AI-era equivalent of `robots.txt` — a structured file hosted at the root of your domain that gives large language models a curated summary of who you are, what you offer, and which pages on your site matter most. Where `robots.txt` controls access, `llms.txt` provides context: it tells the model how to understand your brand and where to find your most important content. Peakmark creates and maintains your `llms.txt` file, keeping it current as your site evolves and as best practices for the format develop. ### 5. Rendering fixes Many modern websites rely heavily on JavaScript to load and display content — and JavaScript-rendered content is frequently invisible to crawlers. If a crawler requests your page and receives an empty shell that only populates once JavaScript executes, the content Peakmark helped you create may never be indexed by AI. Peakmark identifies pages that fail to render correctly for crawlers and recommends or implements the appropriate fixes: server-side rendering, static generation, or other approaches that ensure crawlers receive fully populated HTML. ## How technical GEO relates to everything else Technical GEO is foundational. The [content](/managed/content) work, the community presence, and the PR placements all depend on AI models being able to read, understand, and trust your site. Fixing crawlability and entity clarity doesn't just unlock citations from your own pages — it also reinforces the credibility signals coming from external sources, because the model can now clearly connect those external mentions to a coherent, trustworthy entity on your domain. Peakmark completes the technical audit in Weeks 1–2 alongside the visibility baseline, so that any blocking issues are resolved before content starts publishing and PR placements start going live. Technical fixes addressed early compound the impact of everything that follows.