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Lab Notes.

Our publicly available research and methodology on Generative Engine Optimisation, RAG pipeline ingestion, and Enterprise SEO architecture.

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From Keywords to Context

Why traditional SEO is the foundation, and Generative Engine Optimisation (GEO) is the future. How to evolve your search strategy for 2026.

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Search Grounding: Fact Ingestion

How RAG pipelines evaluate brand trust and the three-pillar protocol for eliminating AI hallucinations through entity confidence.

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Vector Proximity Analysis

Why traditional keywords are failing the retrieval test. Learn the geometry of search and the math of N-dimensional meaning.

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Query Fan-out & Intent

Predict the machine's reasoning. Discover the framework to satisfy the latent intent of AI agents through strategic prompt expansion.

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Schema 2.0 Mapping

Traditional Schema was for rich snippets. Schema 2.0 is an API for LLMs. Learn how to explicitly program the machine's knowledge graph.

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RAG Pipeline Optimization

Retrieval-Augmented Generation (RAG) is the architecture that powers modern AI search.

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The BLUF Protocol

Why human-first storytelling destroys your AI search visibility, and how to engineer immediate context.

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Vector Payload Engineering

Discover how to survive the AI 512-token chunk and ensure your brand facts remain semantically locked.

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Agentic vs. Static AI

Why most enterprise 'AI' is just a glorified If/Then statement, and how true agentic architecture drives operational efficiency.

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