How ChatGPT, Claude, Perplexity and Grok Actually Search the Web (and How to Check If Your Site Is Ready)

It's not magic: each AI searches differently

When someone asks ChatGPT, Claude, Perplexity or Grok "which companies do X in Barcelona?", it feels like the AI just "knows." In reality, behind every answer is a very specific retrieval mechanism, with its own web crawler, its own index, and its own rules about which content it prioritises. Understanding those differences is the foundation of any real AI-visibility strategy — the alternative is guessing.

ChatGPT

OpenAI combines several sources: for real-time search, ChatGPT leans on Bing's index; OpenAI also operates its own crawlers — GPTBot (for model training), OAI-SearchBot (for indexing content used by the search feature) and ChatGPT-User (when a user asks ChatGPT to browse a page live). If any of these user-agents are blocked in your robots.txt, ChatGPT can't cite you in search results or live answers.

Claude

Anthropic clearly separates training from real-time use: ClaudeBot crawls the web for training, while the web search tool Claude uses in conversation combines a search engine with the ability to browse specific pages when a question requires it. Claude tends to favour sources with clear structure and easily extractable content — which is why structured data markup (schema.org) and a clean heading hierarchy directly influence whether it cites you.

Perplexity

Of the four, Perplexity behaves most like a traditional search engine: PerplexityBot crawls the web continuously and runs a live search on every query, not just when needed. As we covered in an earlier analysis, Perplexity strongly favours recent content (articles under 30 days old get up to 3.2x more citations) and leans heavily on Reddit as a source. It's the engine where content freshness matters more than anywhere else.

Grok

Grok (xAI) has a retrieval architecture unlike the others: it combines standard web crawling with privileged access to X's (Twitter's) real-time data stream. Beyond its web search, Grok has a separate "X Search" tool, and its DeepSearch mode runs multi-step research — formulating sub-questions, retrieving, evaluating results and iterating before answering. The result is that Grok cites both web pages and X posts, with a weighting toward real-time conversation no other engine has.

The common thread across all four: every one of them depends on your site being crawlable (a robots.txt that doesn't block them), having complete structured data, and — increasingly — speaking the technical language these systems now expect: an llms.txt file, markdown content negotiation, and error pages that don't trick the agent into believing every path exists.

Tools to check if your site is ready

You no longer have to guess. Free tools — some very recent — now analyse your site specifically from an AI agent's perspective:

Is Agentic — launched by Vercel in late August 2026, it uses Ora's audit engine to score your site out of 100 across 100+ checks: whether your error pages are real, whether your content is accessible without depending on JavaScript, whether your structured data is complete, whether an agent can fill out your forms, and more. Just enter your domain.
Google PageSpeed Insights — alongside the usual performance and SEO metrics, it now includes a dedicated "Agentic Browsing" score for whether an automated agent can navigate your site correctly.
acceptmarkdown.com — checks whether your site correctly responds when an agent requests content in markdown format (Accept: text/markdown header), increasingly common among AI agents to save tokens.
Google's Rich Results Test and the schema.org validator — to check your structured data (Organization, FAQPage, Article) is complete and syntax-error-free.
Manual llms.txt check — just visit yourdomain.com/llms.txt. If it 404s, no agent has a readable summary of who you are and what you do.

Our own case: what we found auditing ourselves

We ran dataversesolutions.net through Is Agentic and started at 77 out of 100. The issues weren't about content — they were technical and very specific:

Nonexistent paths returned the correct 404 status code, but with the hosting provider's generic error page — no recovery links, no useful content for an agent to know where to go next.
We didn't respond with markdown when an agent explicitly requested it via the Accept header.
Our structured data had gaps: no complete ContactPoint block, and no explicit Organization type a strict validator could unambiguously recognise.
We had no dedicated "about" or "contact" URLs — only anchors within the homepage, invisible to an agent checking those paths directly.

We fixed all four: an error page with real content and markdown negotiation, complete structured data, and dedicated trust pages. The result, verified across repeated live scans: above 90 out of 100.

What to do this week

Run your domain through Is Agentic. It takes under a minute and gives you a prioritised list of what to fix first.
Check your robots.txt. Make sure it doesn't block GPTBot, ClaudeBot, PerplexityBot or Google-Extended.
Test a URL that doesn't exist. If your site returns a 200 with the app loaded anyway, any agent assumes every path exists.
Check whether you have an llms.txt. If you don't, it's one of the fastest changes to implement with the most impact.
Validate your structured data with Google's Rich Results Test.

Conclusion

Every AI searches differently, but they all share one minimum requirement: your site needs to be technically readable by an agent, not just by a human with a browser. That's no longer an optional layer of advanced SEO — it's the foundation any real AI-visibility strategy is built on.

At Dataverse Solutions we audit and fix these technical gaps so your site is findable by both Google and the AI agents increasingly deciding who gets recommended.