Crawlability and agent access
We test robots.txt, rendering, internal links, sitemaps, canonicals and server behaviour for search engines and relevant AI user agents.
Be easier for AI assistants to find, understand, verify and recommend.
Webheads helps businesses improve their visibility across ChatGPT, Gemini, Perplexity, Google AI experiences and other answer engines. We combine technical SEO, website development, entity signals and useful first-party content, then test what the systems can actually access and cite.
There is no guaranteed ChatGPT ranking. llms.txt can help agents navigate a site, but it is not a substitute for crawlability, authority, clear evidence and a well-structured website.
Answer engines do not rely on one signal. They combine indexed web content, recognised entities, third-party references, reviews, structured data and the evidence available on each page.
Our work focuses on the parts a business can improve: technical access, clarity, proof, consistency and measurement.
We test robots.txt, rendering, internal links, sitemaps, canonicals and server behaviour for search engines and relevant AI user agents.
We strengthen the consistency of company facts, people, locations, services, profiles and third-party references across the web.
We structure service pages, case studies, FAQs and evidence so answers can extract specific, useful and verifiable information.
We implement relevant schema carefully, linking organisations, services, people, reviews and content without marking up claims the page cannot support.
We identify gaps in reviews, citations, expert attribution and first-party evidence that make a recommendation easier to justify.
We repeat representative prompts, record citations and recommendations, and connect changes to organic visibility, enquiries and revenue where possible.
Test the questions that matter and record which brands, pages and sources are surfaced.
Find the technical, content, entity and authority gaps behind weak visibility.
Our strategists, developers and content specialists make the changes on the website.
Track whether access, citations, recommendations and commercial outcomes improve.
Most worthwhile AI visibility work also improves conventional search and website quality: clear architecture, fast crawlable pages, strong first-party content, recognised entities and credible external evidence.
No. Outputs vary by product, model, prompt, location and time. We can improve the evidence and technical conditions that make a business easier to find and verify, then measure the result.
There is no strong evidence that llms.txt directly improves rankings or recommendations. It can be a useful machine-readable guide, but it should support rather than replace good architecture, sitemaps and clear content.
Not by itself. Correct structured data can reduce ambiguity and connect facts, but systems still look for accessible content and credible supporting evidence.
We use a defined set of commercially relevant questions, track the brands and sources surfaced, monitor conventional search performance and connect the work to enquiries where tracking allows.
We can audit your current visibility, identify the most useful changes and implement them with the same team.
