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Argeo – AI Visibility and Generative Engine Optimization (Geo) Advisory

Argeo – AI Visibility and Generative Engine Optimization (Geo) Advisory

by faruk_tugtekin·Feb 19, 2026·1 point·0 comments

AI Analysis

MidBig Brain

GEO advisory is a real problem, but 'Perception Control' is repackaged SEO consulting.

Strengths
  • Identified genuine gap: LLMs form brand understanding differently than search crawlers.
  • Systematic methodology around entity signals, schema markup, and citation authority.
  • Serves a real pain point: brands have no control over AI-generated recommendations.
Weaknesses
  • Core service is consulting/advisory, not a tool or platform — no defensible IP or scale.
  • Unproven whether signal control actually influences LLM behavior at meaningful scale.
  • Landing page heavy on vision, light on concrete case studies or measurable outcomes.
Category
Target Audience

Enterprise brands, SaaS companies, agencies concerned with AI-driven discovery and brand representation

Similar To

Traditional SEO agencies pivoting to AI · PR firms managing digital reputation · Schema.org markup optimization services

Post Description

Hi HN, I'm Faruk, founder of ARGEO (argeo.ai).

We're an advisory firm focused on AI visibility and Generative Engine Optimization (GEO) — helping brands manage how AI systems like ChatGPT, Claude, and Gemini interpret and reference them.

The core insight: traditional SEO optimizes for search engine crawlers, but AI systems form brand understanding differently — through training data patterns, citation authority, and semantic consistency. We call this gap "Perception Control."

I've written about this on Medium and published a whitepaper on SSRN. Happy to discuss the technical side of how LLMs form entity associations, or the broader implications for brand strategy in an AI-mediated world.

What's your experience with AI systems referencing (or misrepresenting) your projects?

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The Potatometer nails a fun, focused angle: deterministic SEO checks plus an explicit 'GEO / AI visibility' score and support for modern signals like llms.txt and schema detection. The site promises instant, prioritized fixes (code snippets and time estimates) and a playful 'Potato Scale' that actually helps frame results for non-SEO folks. That said, the real value will hinge on how accurately its checks map to actual LLM citation behavior — the landing page shows confidence but stops short of proof or case studies.

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