Structure Is the Moat: How AI Finds, Navigates, and Ranks Your Content
Explore the SEO Week deck by Andrea Volpini, where he shares insights on how AI is reshaping search, content, and digital discovery.
From Frame Semantics to Natural Language Autoencoders: How AI Models Perceive Brands
What does a language model internally associate with a brand before it generates an answer? Using Natural Language Autoencoders, and Gemma 3, we explore how latent semantic representations shape AI Visibility and brand perception for Renault.
Do We Need LLM For Every Query? Separating Discovery from Ranking in the Era of Agentic RAG
Optimize Agentic RAG by separating discovery from ranking. Learn how RLM-on-KG and selective escalation scale Knowledge Graph search performance.
Sara Is All You Need: How Slow Shopping Shapes AI-Powered Decision-Making
Discover Slow Shopping: a philosophy for intentional AI decision-making. Learn how WordLift’s SARA agent uses multi-turn reasoning to prioritize human-centered commerce over speed.
Your Knowledge Graph Is Now a Search Space: How AI Agents Navigate, Not Just Retrieve
AI visibility is shifting from retrievability to navigability. Learn how AI agents use Knowledge Graphs as search spaces and explore the RLM-on-KG architecture.
Structured Data Is Not Enough: Why AI Search Needs a Memory Layer
Our latest research reveals Schema.org alone isn’t enough for generative engine optimization. Learn how structured entity hubs improve AI accuracy by up to 29.8%.
Why AI Cites Some Pages and Ignores Others
How AI systems like Google, OpenAI, and Perplexity AI retrieve, rank, and cite web content and how to structure pages so they remain visible in AI-powered search.
The Full Stack of the Agentic Web: Why WebMCP is the New Schema.org Moment
Until now, agents have relied on brittle techniques like visual scraping to guess at actions. This breaks easily and doesn’t scale. This is why the standardized Web Model Context Protocol (WebMCP) is critical.
RLM-on-KG: Recursive Language Models and the Future of SEO
Recursive Language Models (RLMs) treat prompts as environments to explore, not consume. We adapted this for Knowledge Graphs and discovered why structure, not bigger context windows, is the key to AI accuracy and search visibility.
The Product Ontology for the Agentic Commerce
Explore how the product ontology and data layers power agentic commerce, ensuring product information is trustworthy, actionable, and protocol-compliant.
The Reasoning Web
The Reasoning Web is coming. Learn how context graphs power agentic AI, as the web shifts from search engines to reasoning engines, with interoperable, actionable, machine-readable context.
WordLift Starts Onboarding First Clients for Agentic Commerce Pilot
Discover WordLift Agentic Storefront – the AI-powered solution to boost ecommerce product discovery and engagement.