System Architecture v1.0

The GEO Operating System

GenRankEngine is built on three layers: Observability to scan models, Intelligence to score entities, and Remediation to fix visibility gaps.

01

Observability Layer

Inputs: Prompts & Models

Multi-Model Interrogation

We don't simulate results. We query live models via API including GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro, and Perplexity.

  • Top-N Ranking (Is your product in the list?)
  • Token Position Analysis (How early are you mentioned?)
  • Cross-Model Consensus Checks
scanner_log.json
> Initiating scan: "Best AI SEO tools for SaaS"
> GPT-4o: Detected (Rank #2)
> Claude 3.5: Detected (Rank #1)
> Gemini 1.5: Not Found
> Analysis complete. Delta found.
02

Intelligence Layer

Processing: Scoring & Diagnostics

Share of Voice (SoV)

We calculate your precise ownership of the "Answer Box" relative to competitors across thousands of permutations.

Hallucination Detector

We identify when a model claims your product is "too expensive" or "missing features" when it actually isn't.

Sentiment Vector

Beyond positive/negative. We analyze attributes: "Easy to use", "Enterprise only", "Startup friendly".

03

Remediation Layer

Outputs: Code & Content

The Entity Engine

Fixing AI visibility requires speaking the model's language: Structured Data. Our engine generates engineering-ready JSON-LD patches that explicitly define your product's pricing, features, and relationships to the model.

4x
Faster Indexing
90%
Entity Accuracy
{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "GenRankEngine",
  "applicationCategory": "BusinessApplication",
  "offers": {
    "@type": "Offer",
    "price": "49.00",
    "priceCurrency": "USD"
  },
  "description": "The operating system for GEO...",
  "sameAs": [
    "https://twitter.com/genrankengine",
    "https://linkedin.com/company/genrankengine"
  ]
}

Ready to debug your brand?