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Technical Reference

The 6 Layers of XEO

GEO: Generative Engine Optimization (Stability)

GEO ensures that your brand entity remains stable and recognizable when models synthesize answers across multiple disparate source pages.

What it measures: Cohesion of brand mentions.
Why it matters: Prevents LLM hallucinations or entity confusion.

LEO: Latent Engine Optimization (Latent Space)

LEO analyzes the proximity of your brand vectors to high-demand industry concepts inside vector database embeddings.

What it measures: Vector cosine similarity scores.
Why it matters: Drives organic discovery on conceptual queries.

MEO: Model Ecosystem Optimization (Consistency)

MEO tracks the consistency of recommendation rates and mentions across the primary models (ChatGPT, Claude, Gemini).

What it measures: Cross-platform visibility rates.
Why it matters: Ensures brand presence regardless of user interface choice.

PEO: Prompt Ecosystem Optimization (Retrieval)

PEO targets how reliably your structured data is retrieved in response to specific, complex prompt payloads.

What it measures: In-context retrieval match rate.
Why it matters: Guarantees placement in structured comparisons.

AEO: Agent Ecosystem Optimization (Selection)

AEO optimizes content structure for machine-readability so automated AI agents choose your service over competitors.

What it measures: Tool-calling integration success.
Why it matters: Powers actions completed by autonomous agents.

TEO: Trust Engine Optimization (Credibility)

TEO benchmarks your brand's authority, reference citations, and sentiment markers across the semantic web.

What it measures: Sentiment validation & citation weight.
Why it matters: Determines if a model trusts you enough to recommend you.