We separate the signal from the noise in AI search visibility.
Signal & Noise GEO was founded in 2025 because AI search is replacing traditional search and most businesses are invisible to it. The tools that existed measured vanity metrics: citation counts, mention frequency, surface-level presence. None of them measured the structural factors that determine whether an AI model will find, understand, and recommend a brand.
We built an agency around a different premise: AI visibility is an engineering problem, not a marketing problem. The content structures, schema markup, passage quality, and fact density that determine AI citations are measurable, auditable, and fixable. That is what we do.
The name "Signal & Noise" comes from information theory. In a world flooded with AI-generated content, the brands that succeed are the ones whose content carries signal: genuine expertise, structured information, verifiable facts. Everything else is noise. We help brands increase signal and reduce noise.
Signal & Noise GEO follows a four-phase engagement model for every client:
We run a comprehensive GEO audit using GeoScored to establish a baseline score. The audit covers content quality, AI discovery signals, schema markup, passage self-containment, and citation readiness. Every finding is scored and prioritized.
Based on the audit findings, we build a prioritized implementation plan. We identify the highest-impact fixes first: typically structured data gaps, heading hierarchy problems, and passage structure issues that prevent AI extraction.
We implement the fixes directly or work alongside your content team. Schema markup, content restructuring, llms.txt configuration, and heading hierarchy corrections. Every change is documented and tied to a specific audit finding.
We re-audit after implementation to measure improvement. Clients typically see a 30-50 point GEO score increase within the first engagement cycle. We track AI citation frequency and recommendation context to validate real-world impact.
Founder & Principal
Former VP of SEO at a Fortune 500 media company. Recognized the shift to AI search in 2024 and built Signal & Noise GEO to help brands adapt.
Head of Content Strategy
Content strategist specializing in AI-optimized content architecture. 10 years of experience in content operations and structured data implementation.
Technical GEO Lead
Schema markup specialist and technical SEO engineer. Implements the structured data strategies that make content machine-readable for AI crawlers.
We hold three positions about Generative Engine Optimization that inform all of our work:
The cost of producing average content is approaching zero. The bar for content that earns AI citations is rising. We optimize for structural quality, not publication frequency. One well-structured page outperforms ten thin ones in AI search.
Every recommendation we make is tied to a measurable check. We use GeoScored to quantify improvements before and after implementation. If we cannot measure the impact, we do not recommend the change.
We focus on the structural inputs that AI models evaluate when selecting content to cite: passage self-containment, fact density, schema completeness, heading hierarchy. These are the factors within your control. Citation counts are outputs you cannot directly control.
Start with a GEO audit. We will show you exactly where your content stands and what to fix first.
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