Traditional SEO ranks blue links. We engineer knowledge graphs, AI-optimized content structures, and RFC-compliant machine endpoints so ChatGPT, Claude, and Perplexity cite and recommend your firm as the definitive authority.
Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) are the engineering disciplines of structuring a brand's data architecture so that AI models (ChatGPT, Perplexity, Claude) can read, verify, and recommend your business.
While traditional SEO relies on keywords to rank blue links, GEO leverages Knowledge Graph Engineering, JSON-LD Entity Grounding, and Machine Endpoints (/llms.txt) to ensure you are the definitive answer in AI retrieval pipelines.
If ChatGPT or Perplexity are recommending your competitors instead of you, your site is suffering from one of three critical architectural failures:
Your Cloudflare or AWS edge firewall is actively returning HTTP 403 blocks to GPTBot and Claude-Web. If live RAG agents cannot crawl your domain, they drop you from their context window.
You lack a structured JSON-LD @graph tied to canonical Wikidata Q-IDs. Without deterministic entity grounding, LLMs view your brand as an unverified entity and refuse to cite it as an authority.
AI agents actively search for an RFC-compliant /llms.txt file at your domain root to ingest your commercial capabilities. Without it, they are forced to parse bloated HTML DOMs and miss your core value prop.
Foundation models do not scan keyword densities or PageRank backlinks. They execute dense semantic vector retrieval against structured entity clusters.
| System Parameter | Legacy SEO Paradigm | Generative & AEO Architecture (Standard) |
|---|---|---|
| Primary Metric | SERP placement (ranks 1–10) & blue-link click volume | Model synthesis quotation, direct attribution & recommendation share |
| Target Scraper | Googlebot crawling standard HTML and client-side DOM | GPTBot, ClaudeBot, PerplexityBot, Applebot-Extended |
| Content Structure | 2,500-word keyword-dense marketing blogs & narrative filler | High-entropy AI-optimized content structures, RFC-llms.txt, and answer-first tables |
| Technical Core | Meta tags, basic sitemaps, OpenGraph image tags | Deep @graph JSON-LD clusters linking verified Wikidata & license nodes |
| Conversion Outcome | Unqualified visitors bouncing across walls of text | High-intent buyers receiving direct authoritative vendor recommendations |
Over 68% of commercial domains inadvertently block LLM scrapers via firewall challenges. Our edge architecture guarantees sub-45ms responses.
Deep entity injection anchors your organization into canonical Semantic Web models. By explicitly mapping your capabilities via W3C-compliant JSON-LD—utilizing RAG vector retrieval standards, Entity Grounding, and Knowledge Graph Engineering—we eliminate hallucination risks and establish deterministic authority during LLM synthesis.
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "Organization",
"@id": "https://jamesstone.dev/#organization",
"name": "James Stone Advisory",
"url": "https://jamesstone.dev",
"sameAs": [
"https://github.com/KxBxM",
"https://www.wikidata.org/wiki/Special:Search?search=James+Stone"
],
"knowsAbout": [
"https://en.wikipedia.org/wiki/Knowledge_graph",
"https://llmstxt.org/"
]
}
]
}From zero-cost diagnostic teardowns to full-stack Knowledge Graph engineering and continuous LLM prompt drift governance.
Diagnostic teardown of AI crawler blocks and baseline LLM recommendation share.
Deep multi-model prompt benchmarks, citation gaps, and technical SOW.
Turnkey deployment of /llms.txt, JSON-LD @graph, and WAF bot clearance.
Continuous prompt drift monitoring, heartbeat audits, and citation defense.
Phase 1: Edge Ingestion & Semantic Parsing (24–48 Hours): Resolving WAF 403 blocks, deploying root /llms.txt endpoints, and injecting the JSON-LD @graph allows foundational LLM crawlers to instantly ingest your un-cached DOM. (Executed via Charter II: Technical Remediation — $3,800)
Phase 2: Vector Grounding & Algorithmic Consensus (30–90 Days): LLMs do not update their retrieval weights instantaneously. We establish third-party entity grounding through off-page ecosystem seeding, shifting your Brand Mention Share from 0% to the primary recommended entity. (Governed via Charter III: GEO Retainer — $1,850/mo)
Detailed breakdown of deliverables, technical interventions, and service levels across tiers.
| Technical Capability / Scope Item | Tier 0 Snapshot |
Charter I Visibility Audit |
Charter II 14-Day Remediation |
Charter III Governance |
|---|---|---|---|---|
| 1. Commercial Structure & Fee Credit | ||||
| Investment Required | $0 (Free) | $950 Flat | $3,800 One-Time | $1,850 / Month |
| SLA / Delivery Timeline | Same-Day | 3 Business Days | 14-Day Sprint | Ongoing Monthly |
| 100% Fee Credit Guarantee | N/A | ✓ 100% Credited to Ch. II | Includes $950 Credit | N/A |
| 2. Multi-Model Benchmark Evaluations | ||||
| Evaluations Executed | 2 Prompts (Baseline) | 240 Programmatic Evals | Full 240 Evals Included | 50 Weekly (2,600/yr) |
| Model Coverage | SearchGPT & Perplexity | OpenAI, Perplexity, Claude, Gemini | OpenAI, Perplexity, Claude, Gemini | Continuous Multi-Model |
| Citation Gap Matrix | Top 2 (Redacted) | ✓ Full Unredacted | ✓ Full Unredacted | ✓ Monthly Defense Brief |
| 3. Production Code & Infrastructure | ||||
| 4-Node JSON-LD @graph | ✕ | Audit Blueprint Only | ✓ Turnkey Deployment (12+ Q-IDs) | 24/7 Heartbeat Guard |
| RFC /llms.txt Endpoints | ✕ | Specification Only | ✓ Root Production Build | Continuous Sync |
| Cloudflare / AWS WAF Clearance | Detection Only | Rule Specifications | ✓ Custom WAF Rule Config | 24/7 Edge Heartbeat |
| Answer-First Page Refactoring | ✕ | Recommendations | ✓ Top 5 Revenue Pages | Quarterly Refresh |