1. Creation
Facts, claims, media and structured records are produced by people and systems.
Hidden Radius explains the processes beneath modern discovery: publication, crawling, indexing, recognition, retrieval, generation, attribution, trust and action.
A person may begin with Google, ask a phone, open a map, consult ChatGPT, compare sources in Perplexity or allow an agent to perform part of the task. Each surface may use a different index, retrieval method, model, ranking system and set of controls. The visible answer is the end of a chain, not the chain itself.
Hidden Radius studies that chain. The objective is not to invent a new acronym for every change. It is to distinguish the jobs that are routinely compressed into the phrase “AI visibility” and show which organization, standard, technical discipline or research paper actually explains each job.
Facts, claims, media and structured records are produced by people and systems.
Information is made available through websites, feeds, profiles, APIs and databases.
Crawlers and connected systems encounter URLs, records and references.
Documents, passages and entities are processed into searchable collections.
The system determines which person, organization, product or place is being described.
Relevant pages, passages, fields or records are located for the request.
A model transforms instructions and evidence into a response.
The interface may identify sources, links, brands or supporting material.
Ranking and interface decisions determine what the user can see.
Evidence quality, freshness and system behaviour affect the accuracy of the result.
A person or agent narrows the available options.
The journey produces a click, call, visit, booking, purchase or other outcome.
Hidden Radius uses different authorities for different questions. NIST addresses risk and evaluation. Stanford HAI tracks capability and adoption. OECD clarifies what an AI system is. Google, OpenAI, Perplexity and Microsoft explain their own products and crawler controls. IETF and W3C provide web standards. Schema.org supplies structured vocabulary. Academic papers provide the original GEO and RAG formulations. IRefer is cited only as the original source organization for REG.
The site does not treat any platform as a universal model for the rest of the industry. Each source is used within the limits of what it can establish.
Map where a site or organization can be discovered, where identity breaks and where retrieval becomes unreliable.
Find conflicting names, locations, services, relationships and facts that weaken recognition.
Test robots rules, server responses, CDN controls, internal discovery and index eligibility.
Design pages and information structures that remain useful when retrieved as passages or records.
Explain the changing search environment without reducing the subject to marketing jargon.
Separate traffic, citation, recognition, retrieval, representation and business outcomes.
Cross-sector guidance for governing, mapping, measuring and managing generative-AI risk.
Open the original source at National Institute of Standards and Technology →
Data-driven reporting on AI capability, adoption, economics, public opinion and responsible AI.
Open the original source at Stanford Institute for Human-Centered Artificial Intelligence →
Official guidance on SEO, crawlability, original content, local details and generative Search.
Official information about OAI-SearchBot, GPTBot, referral tracking and agent accessibility.