SurfaceGX was founded by operators who saw the same pattern across brands: AI visibility problems were being measured after the fact, but the machine-readable source layer was still broken.
Jeanine brings 20 years of expertise in communications, media relations, and content strategy, having built and led PR and earned media programs for some of the most reputation-sensitive brands in business.
She envisioned and co-founded SurfaceGX after experiencing firsthand how AI was distorting brand narratives in ways no traditional communications measurement tool could detect or explain.
John leads the product architecture behind the platform's audit, diagnostic, and repair workflows.
John's background spans product development in AI, data infrastructure, enterprise access layers, machine learning visualization, and hands-on product engineering. At SurfaceGX, he focuses on making complex technical signals actionable for the teams responsible for shipping the fix.
Most AI visibility platforms help teams monitor where a brand appears in generated answers. SurfaceGX focuses on the layer before that answer exists: schema, crawlability, canonical signals, source authority, page structure, and AI-readable manifests.
The goal is practical repair. Diagnose what AI systems cannot read, explain why it matters, and produce work that content, SEO, and engineering teams can ship.
Run a free scan, then choose a plan when your team is ready for deeper diagnosis, repair artifacts, and verification workflows.
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