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00 · The methodology

Generative Engine Optimization for AI Visibility

Prime Sentia GEO is a Generative Engine Optimization platform for B2B marketing, SEO, brand, and content teams. It audits how AI answer engines describe your brand, prioritizes the fixes that move citation readiness, and plans 30/60/90-day execution. Start with a free audit.

16
Empirical grounding
pre-registered signals, derived from a 2,000-site observational study registered on OSF before data collection (DOI 10.17605/OSF.IO/XCG7J).
39
Audit breadth
GEO citation signals across four GEF dimensions — Accessibility, Extractability, Authority, Citability — plus 22 Agent-Readiness checks.
7
Evidence base
public-source entries from Adobe, Bain, Princeton, OpenAI, and Google.
17
Architecture
agents across four audit phases, with every output carrying provenance back to the signal and page that produced it.

Brief

What this hub is

A structured operating model for how brands are retrieved, cited, and represented inside AI.

Methodology layer

Prime Sentia GEO is the methodology and proof layer behind the AI Visibility offer.

Agents
17
Audit phases
4
Artifacts
6
Program
1

Every output carries provenance back to the signal and page that produced it. Not a commercial landing page: the deeper layer.

Audit engine

39 GEO citation signals — scored across the four GEF dimensions (Accessibility, Extractability, Authority, Citability) — plus 22 Agent-Readiness checks across six categories. Of those, 16 are pre-registered and empirically grounded in an observational study of 2,000 websites; the rest are validators from production experience. No probabilistic scoring, no black-box optimization — each maps to a concrete fix.

Research basis

Pre-registered

The 16 GEO signals are derived from an observational study (DOI 10.17605/OSF.IO/XCG7J) across 2,000 websites. Study design, variable definitions, and the analytical plan were registered on the Open Science Framework before any data was collected — so every signal carries documented empirical provenance, not a marketing claim.

Evidence layer

Market signals from Adobe and Bain, research from Princeton and KDD 2024, and platform documentation from OpenAI and Google support the framework. The full dossier is in the Evidence section. Where proprietary client results are not published, the site says so plainly — no invented case-study language.

I.

The workflow

4 phases · 6 stages · serial flow

Protocol · flow map

see full protocol →
  1. Diagnose
  2. Construct
  3. Decide
  4. Ship
  1. 01

    Discover

    Extract brand entities, narrative, products, audiences, and proof signals.

  2. 02

    Audit

    Measure AI visibility and evaluate citation-readiness across priority pages.

  3. 03

    Structure

    Standardize brand context so recommendations and roadmap planning stay consistent.

  4. 04

    Recommend

    Rank actions by visibility impact, complexity, and business relevance.

  5. 05

    Prioritize

    Convert findings into a 30/60/90 roadmap with dependencies.

  6. 06

    Implement

    Hand teams executable guidance for content, SEO, brand, and web work.

II.

The atlas

06 sections · explore

III.

Core outputs

06 artifacts

  1. 01AI Visibility Audit

    Diagnostics

  2. 02Citation-Readiness Assessment

    Diagnostics

  3. 03Prioritized Recommendations

    Strategy

  4. 0430 / 60 / 90 Execution Roadmap

    Execution

  5. 05On-Demand Task-Level Implementation Guidance

    Execution

IV.

The evidence

03 signals · public sources

Position

Evidence, not invented case-study language.

Underlying researchDOI 10.17605/OSF.IO/XCG7JLuis Oleart

This hub uses an evidence layer built from market signals, published research, and platform documentation. Where proprietary client results are not being published, the site says so plainly instead of pretending market proof is a case study.

  • Market signal

    Adobe · 2025

    693.4%

    Adobe reported AI-driven retail traffic growth year over year, reinforcing AI discovery as a real acquisition channel.

  • Research signal

    Princeton · KDD 2024

    Up to 40%

    Princeton GEO research showed measurable visibility lift when content is structured for generative engine retrieval.

  • Behavior signal

    Bain · 2025

    80%

    Bain reported heavy reliance on AI-written summaries, confirming that answer layers influence consideration before the click.

V.

Reference

10 questions

The shortest path to the answers most teams need before they engage.Open the full reference →

Q01

What is Prime Sentia GEO?

Prime Sentia GEO is a structured operating model for improving how brands are retrieved, cited, and represented inside AI-generated answers. It combines brand discovery, AI visibility auditing, standardized brand context, recommendations, prioritization, and implementation planning.

Q02

How is GEO different from SEO?

SEO focuses on ranking in traditional search results. Prime Sentia GEO focuses on how a brand is understood and cited inside AI-generated answers, including AI Overviews, ChatGPT, Perplexity, and Bing Copilot.

Q03

What does Prime Sentia GEO produce?

Prime Sentia GEO produces an AI visibility audit, a citation-readiness assessment, prioritized recommendations, and a 30/60/90 roadmap for content, SEO, brand, and web execution. Teams can resolve selected dashboard tasks on demand when they need implementation detail.

Q04

Who is Prime Sentia GEO designed for?

Prime Sentia GEO is designed for marketing directors and growth teams at mid-size and enterprise brands that need a clearer system for AI visibility, citation readiness, and answer-engine discoverability.

Q05

What is the first step in the Prime Sentia GEO workflow?

The first step is Discover, where Prime Sentia extracts brand entities, narrative, products, audiences, and proof signals before moving into visibility analysis and structured remediation.

Q06

How does Prime Sentia support onboarding?

Prime Sentia turns audit findings into implementation-ready outputs so internal teams can move from analysis to action with clear priorities, dependencies, and execution guidance.

Q07

What GEO signals does the audit measure?

The Prime Sentia AI Visibility Audit evaluates 39 GEO citation signals across four GEF dimensions — Accessibility, Extractability, Authority, and Citability. Of these, 16 are pre-registered in an observational study of 2,000 websites (DOI 10.17605/OSF.IO/XCG7J); the remaining 23 are validators added from production experience.

Q08

What are A2A agents and how do they work in GEO?

A2A (Agent-to-Agent) agents are autonomous workers that run structured tasks — brand discovery, page capture, visibility auditing, recommendation generation, and roadmap planning — coordinated by a geo-strategist orchestrator. Each agent emits traceable events, so every recommendation carries provenance back to the signal that triggered it.

Q09

What does a typical engagement look like?

A standard engagement runs four phases: Discover (brand extraction and crawl), Audit (visibility measurement and citation-readiness scoring), Decide (prioritized recommendations), and Ship (30/60/90 roadmap with task-level guidance). Most teams complete the full cycle in two to three weeks.

Q10

How long until we see results from GEO?

GEO is a structural discipline, not a traffic switch. Early signals — improved entity representation and structured data — take effect within days of implementation. Visibility lift in AI-generated answers typically materializes over four to eight weeks as answer engines re-index and re-rank. The 30/60/90 roadmap is designed to match this cadence.

VI.

Field notes

view all →

GEO Strategy

№ 01

AI Killed the Mobile Star

Pull raw web traffic and desktop looks like it is winning again — until you filter the bots, and humans are still mobile-first. Bots are now 57.5% of requests to HTML content. The real shift isn't device, it's species: human or agent?

GEO Strategy

№ 03

Socrates and citability

The Socratic method — questions, not answers — is why human, experience-grounded content gets cited. A look at citability, the Compose ethic, and how ChatGPT, Perplexity, and Gemini actually cite in 2026.

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