Decoding DartmouthIntelligence Layer 01

Helping Brands Become Discoverable in the Age of AI

Decoding Dartmouth helps businesses understand how AI systems discover, reference, and trust brands. No hype. No rank guarantees. Only evidence.

AI Entity Graph · Simulated
Your BrandTopic AGPT-5GeminiPerplexityClaudeSource
What is GEO

Generative Engine Optimization is the strategy of verifiable presence.

Traditional SEO optimized for keywords and backlinks. GEO optimizes for how Large Language Models cite, synthesize, and recommend your brand inside generated answers.

We map how Claude, GPT, Gemini, and Perplexity represent your domain — and ensure your brand is referenced as a credible primary source rather than absent or misattributed.

Process · 04

The Synthesis Pipeline

01

Retrieval

The engine surfaces relevant documents and signals across the open web's semantic layer.

02

Re-ranking

Sources are weighted by authority, recency, structured data clarity, and cross-reference frequency.

03

Generation

The model synthesizes a single answer, citing the entities that anchor each truth-claim.

Comparative Observation

The Good, The Bad & The Ugly

The Good

Your brand is cited verbatim as the source of truth for its category. AI responses link back, drive qualified traffic, and reinforce authority.

The Bad

The model summarizes your methodology correctly but omits your name, attributing the insight to general common knowledge or aggregators.

The Ugly

Total erasure or hallucination. Conflicting signals lead the engine to misrepresent your features, pricing, or position. Discovery collapses.

The Transparency Manifesto

Generative engines are non-deterministic. The same prompt yields different citations across sessions. Anyone promising "#1 in ChatGPT" is selling an impossibility. We focus on the probability of citation through structural integrity and semantic clarity.

— The Decoding Dartmouth commitment