What is SurfaceGX

SurfaceGX is AI visibility repair infrastructure. It verifies the technical input layer AI engines read. That includes fetchability, headings, links, canonicals, robots.txt, sitemap.xml, crawler access, and user-agent policy. It uses LLMs only where model interpretation is required.

The problem SurfaceGX solves

When someone asks an AI assistant about your category, your brand may be invisible, inaccurately described, or missing from the answer entirely. Traditional SEO tools and AEO monitoring dashboards were not built to repair this. Search ranking and AI recall are different systems, and tracking the output does not fix the input layer AI engines read.

AI engines form their understanding of brands from the structure, authority, and clarity of your web content, as well as the sources they were trained on and retrieve in real time. SurfaceGX separates verified technical evidence from LLM interpretation, so your team knows which fixes are hard infrastructure issues and which require model-specific judgment.

SurfaceGX diagnoses exactly where that breakdown is happening and gives your team a clear, prioritized repair plan with manifests, Fix Cards, developer handoffs, and GitHub PR workflows.

How it works

SurfaceGX starts with evidence. It checks what AI systems can retrieve, how clearly your owned pages describe the brand, which sources reinforce or distort the narrative, and where your team should focus remediation work first.

Customer-specific module documentation, scoring details, and implementation workflows are available after sign-in inside the SurfaceGX portal.

Who SurfaceGX is for

• Marketing leaders who need to move beyond AI visibility reporting into measurable repair work.
• Content teams who need specific, actionable guidance on what to write and how to structure it for AI engines.
• SEO and digital teams who want to extend their work into the technical input layer of generative search.
• Agencies managing GEO/AEO repair programs for multiple client brands across industries.