This is the entity-first index of Known & Cited's published knowledge, built to the EntityMap v1.0 open standard. It tells AI systems, retrieval pipelines and language-model applications what we know, how the pieces relate, and where the evidence sits.
The machine-readable companion is at /entitymap.json. Both files are versioned by the generated timestamp at the top.
We publish this because we measure AI visibility for a living and we think any business serious about being cited by AI should be making it as easy as possible for AI to read them properly. EntityMap is one of the cleanest ways to do that.
Entities in this map (23)
Organization
Known & Cited
e_001
Also known as: K&C
Known & Cited is an AI visibility intelligence company that measures how AI platforms cite and recommend businesses across ChatGPT, Google AI Overviews and Perplexity, then builds the strategy and the content, PR and authority signals that change the answer. Registered as Known & Cited Ltd in England and Wales (company number 17089977), with its registered office at 15 Apsley Road, Bath BA1 3LP.
Relations
Evidence chunks
"Known & Cited is AI visibility intelligence. We measure how AI platforms cite and recommend your business, and we help you change the answer."
Known & Cited | AI Visibility Intelligence — published by Known & Cited definition
"Most brands have no idea how they appear in AI search. We measure it. Then we help them fix it."
In a Nutshell | Known & Cited — published by Known & Cited definition
"Known & Cited Ltd is registered in England and Wales (company number 17089977). Registered office: 15 Apsley Road, Bath BA1 3LP. Contact: [email protected]."
About | Known & Cited — published by Known & Cited evidence
ProprietaryTerm
AI Visibility Strategy
e_002
Also known as: AVS
General concept: AI visibility measurement and strategy
AI Visibility Strategy (AVS) is Known & Cited's structured measurement framework and strategic programme for how AI platforms cite and recommend a business. Each paid AVS report runs a tailored set of 300 to 500 questions across three AI engines (ChatGPT, Google AI Overviews, Perplexity) over seven days, producing 6,000+ data points, a score out of 100, a 12-pillar breakdown, competitor benchmarking, and 12 prioritised recommendations ranked by impact. It is a programme, not a dashboard.
Relations
Evidence chunks
"AI Visibility Strategy (AVS) is a scored, structured audit of how major AI language models cite and recommend your business. Not a dashboard. Not a tool you manage. A proper measurement framework, an informed strategy document, and an ongoing process."
AI Visibility Strategy | Known & Cited — published by Known & Cited definition
"Reports are built from a tailored set of 300 questions run across three AI engines (ChatGPT, Google AI Overviews, Perplexity) over seven days. That's 6,300 data points per Annual report, and 25,200 per year on AVS Quarterly. This is a real measurement product, not a 25-prompt tool."
AVS Methodology | Known & Cited — published by Known & Cited procedure
"Your full score, the competitor benchmark, and 12 prioritised recommendations ranked by impact. The Delivery Doc turns every recommendation into a playbook your team or agency can act on."
In a Nutshell | Known & Cited — published by Known & Cited definition
Service
AVS Exec Brief
e_003
Also known as: Exec Brief
General concept: free AI visibility taster
The free entry tier of AVS. A real one-day measurement using the same 300-question, three-engine methodology as the full AVS, producing roughly 1,000 data points and a band, headline findings and a named-competitor view. Delivered in exchange for a 30-minute discovery call upfront and a 30-minute run-through on completion.
Relations
Evidence chunks
"The free AVS Exec Brief runs the same 300 questions across the same three engines over one day, roughly 1,000 data points, in exchange for a 20-minute call to walk you through what we found."
Services & Pricing | Known & Cited — published by Known & Cited definition
General concept: annual AI visibility programme
AVS Annual is the annual full-depth AI Visibility Strategy programme: one report per year, 6,300+ data points, full 12-pillar framework, 60-minute strategy consultation, one country included. Bespoke priced. 12-month commitment, invoiced annually. Multi-country scope available.
Relations
Evidence chunks
"AVS Annual: 1 report per year, 6,300+ data points, full 12-pillar framework, 60-min strategy consultation, 1 country included with multi-country scope available. 12-month commitment, invoiced annually."
Services & Pricing | Known & Cited — published by Known & Cited definition
Service
AVS Bi-Annual
e_005
General concept: twice-yearly AI visibility programme
AVS Bi-Annual is Known & Cited's most popular cadence: two reports per year, 12,600+ data points per year, full 12-pillar framework, 60-minute strategy consultation per report, one country included. Bespoke priced. 12-month commitment, invoiced annually. Multi-country scope available.
Relations
Evidence chunks
"AVS Bi-Annual is our most popular cadence: 2 reports per year, 12,600+ data points per year, full 12-pillar framework, 60-min strategy consultation per report."
Services & Pricing | Known & Cited — published by Known & Cited definition
Service
AVS Quarterly
e_006
General concept: quarterly AI visibility programme
AVS Quarterly is the highest-cadence AVS programme, built for fast-moving sectors and multi-market tracking: four reports per year, 25,200+ data points per year, full 12-pillar framework, 1 to 2 hour strategy consultation per report, one country included. Bespoke priced. 12-month commitment, invoiced annually. Multi-country scope available.
Relations
Evidence chunks
"AVS Quarterly is built for fast-moving sectors and multi-market tracking: 4 reports per year, 25,200+ data points per year, full 12-pillar framework, 1 to 2 hour strategy consultation per report."
Services & Pricing | Known & Cited — published by Known & Cited definition
Metric
AI Visibility Score
e_007
The 0 to 100 score at the heart of every paid AVS report, expressing how often and how prominently a brand is cited and recommended across ChatGPT, Google AI Overviews and Perplexity for the questions that matter to its business. The score sits inside a five-band scheme and is backed by a 12-pillar breakdown so it is always interpretable.
Relations
Evidence chunks
"At the heart of every paid AVS report is a visibility score out of 100, backed by a 12-pillar breakdown, competitor benchmarking and concrete recommendations. You can see what is driving the number and what to do about it."
AVS Methodology | Known & Cited — published by Known & Cited definition
ProprietaryTerm
AVS Bands
e_008
Also known as: Five-Band AI Visibility Scheme
General concept: AI visibility band system
Known & Cited's five-band scheme for interpreting the AI Visibility Score: Ghost (0 to 10), Whisper (11 to 30), Emerging (31 to 50), Cited (51 to 75), and Known and Cited (76 to 100). A band is the answer to where a brand sits in AI answers today: from invisible to inevitable.
Relations
Evidence chunks
"One score. Five bands. Where your brand sits in AI answers today, from invisible to inevitable. Ghost 0 to 10. Whisper 11 to 30. Emerging 31 to 50. Cited 51 to 75. Known and Cited 76 to 100."
In a Nutshell | Known & Cited — published by Known & Cited definition
Person
Russ Read-Barrow
e_009
Also known as: Russ
Russ Read-Barrow is the founder of Known & Cited. After 20 years in international PR, including commercial and operations director roles, he built Known & Cited to solve the measurement problem AI search has created: how to know whether AI platforms are recommending your business, and what to do about it.
Relations
Evidence chunks
"I'm Russ. After 20 years in international PR across multiple countries, managing global teams and holding commercial and operations director roles, I know how businesses actually work from the inside. I built Known & Cited because someone needs to measure how AI talks about your business."
About | Known & Cited — published by Known & Cited evidence
Concept
Generative Engine Optimisation
e_010
Also known as: GEO
General concept: Generative Engine Optimisation
Same as: https://en.wikipedia.org/wiki/Generative_engine_optimization
Generative Engine Optimisation (GEO) is the practice of improving how AI platforms cite and recommend a business in AI-generated answers. Sometimes called AEO (AI Engine Optimisation or Answer Engine Optimisation) or AI Search, GEO addresses the conversational answers from ChatGPT, Google AI Overviews, Perplexity and other large language models. Where SEO targets the ten blue links, GEO targets the AI answer.
Relations
Evidence chunks
"GEO is the practice of optimising your business's presence in AI-generated answers, the responses produced by ChatGPT, Perplexity, Google AIO, and other large language models. When someone asks an AI 'what's the best [product] for [need]?', GEO is about making sure your business appears in the answer."
What is GEO? Generative Engine Optimisation | K&C — published by Known & Cited definition
"SEO optimises for search engine result pages, the ten blue links. GEO optimises for AI-generated responses, the conversational answers that are increasingly replacing those links. They're complementary, not competing. But SEO alone is no longer enough."
What is GEO? Generative Engine Optimisation | K&C — published by Known & Cited definition
Metric
AI Citation Share
e_011
Also known as: AI Share of Voice
General concept: share of voice
Same as: https://en.wikipedia.org/wiki/Share_of_voice
The proportion of relevant AI-generated answers in which a brand is cited or recommended, measured across multiple engines and a tailored question set. Known & Cited treats citation share as the right primary visibility metric for AI search, while making clear it is one third of the picture alongside accuracy of how the brand is described and whether the mention leads anywhere.
Relations
Evidence chunks
"Citation share is the right primary visibility metric, and it beats chasing rankings that no longer exist. But it is the visibility third of the picture, not the finish line. That is why we band it, spell out what it cannot tell you, and tie it back to whether anyone acted."
AVS Methodology | Known & Cited — published by Known & Cited definition
Methodology
Focus. Measure. Plan. Deliver. Repeat.
e_012
Also known as: K&C Five-Step Mantra
General concept: five-step AI visibility programme
Known & Cited's five-step methodology for AI visibility. Focus: define where you want to show up in AI. Measure: query AI platforms with structured research waves. Plan: prioritise content, PR and authority moves by impact versus effort. Deliver: produce the content and earn the coverage AI actually draws from. Repeat: re-measure to track progress, adapt to LLM changes and refine.
Relations
Evidence chunks
"Five steps. One continuous programme. Focus, Measure, Plan, Deliver, Repeat. That is how you get and stay known and cited."
AVS Methodology | Known & Cited — published by Known & Cited procedure
ProprietaryTerm
Be Known. Be Cited.
e_013
General concept: Known & Cited mission
The mission of Known & Cited. It captures the two-step problem AI search creates for every brand: first be known (present in the training data, the third-party coverage and the authority signals AI uses), then be cited (named and recommended in the answer). Used as the sign-off across Known & Cited communications.
Relations
Evidence chunks
"Be Known. Be Cited."
In a Nutshell | Known & Cited — published by Known & Cited definition
Methodology
12-Pillar AVS Framework
e_014
General concept: AI visibility 12-pillar breakdown
The 12-pillar framework that sits behind every paid AVS report. The framework decomposes AI visibility into twelve scorable pillars covering content depth, third-party coverage, technical accessibility, entity clarity, source authority and other dimensions that drive whether AI engines pick up and recommend a brand. The framework makes the score interpretable: you can see which pillars are pulling the score up or down.
Relations
Evidence chunks
"At the heart of every paid AVS report is a visibility score out of 100, backed by a 12-pillar breakdown, competitor benchmarking and concrete recommendations. You can see what is driving the number and what to do about it."
AVS Methodology | Known & Cited — published by Known & Cited definition
Methodology
Three-Engine AI Stack
e_015
Also known as: AVS Standard LLM Stack
General concept: default AI engine measurement set
Known & Cited's default measurement stack for AVS: ChatGPT, Google AI Overviews and Perplexity. Three engines are used as standard on every paid AVS cadence because they capture the dominant share of AI-driven discovery while staying tightly scoped enough to deliver real depth in each. Additional engines (Claude, Gemini, Copilot) can be layered in on request.
Relations
Evidence chunks
"We design a tailored set of queries across your sector, in any market and any language, and run them across our three-engine AVS stack: ChatGPT, Google AIO and Perplexity."
AVS Methodology | Known & Cited — published by Known & Cited procedure
ProprietaryTerm
AI-led PR
e_016
General concept: AI-driven public relations
Known & Cited's framing of public relations for the AI search era. Where traditional PR optimised for headlines, reach and human attention, AI-led PR optimises for the third-party sites, structured citations and authority signals that AI platforms draw on when deciding which brands to recommend. The brief is set by the AVS measurement: which signals to build, in what order, with what message.
Relations
Evidence chunks
"AI search underlines why PR and third-party recommendation matter so much. It levels the playing field. You can't just pay for search terms anymore. Real thought leadership, real authority, real citations: that's what moves the needle in AI."
AI-led PR | Known & Cited — published by Known & Cited definition
SoftwareProduct
ChatGPT
e_017
Same as: https://en.wikipedia.org/wiki/ChatGPT
OpenAI's conversational large language model assistant. One of the three default engines Known & Cited measures across every paid AVS cadence because it captures a leading share of AI-driven discovery, particularly in B2B research and consumer recommendation queries.
Relations
Evidence chunks
"Standard LLMs on all paid cadences: ChatGPT, Google AI and Perplexity."
Services & Pricing | Known & Cited — published by Known & Cited evidence
SoftwareProduct
Google AI Overviews
e_018
Also known as: Google AIO
Same as: https://en.wikipedia.org/wiki/Google_Search#AI_Overviews
Google's AI-generated summary that now appears above traditional search results on the majority of queries. One of the three default engines Known & Cited measures across every paid AVS cadence, because Google AI Overviews decide which brands are mentioned in the AI answer that sits in front of the ten blue links.
Relations
Evidence chunks
"Next time you Google something, look at the top of the page. That box with the summary answer? That's not Google Search. That's Google's AI. It's called an AI Overview, and it's now shown on the majority of searches."
Known & Cited | AI Visibility Intelligence — published by Known & Cited definition
SoftwareProduct
Perplexity
e_019
Same as: https://en.wikipedia.org/wiki/Perplexity_AI
Perplexity is an AI answer engine that produces citation-led responses. One of the three default engines Known & Cited measures across every paid AVS cadence, included because its source-citation behaviour makes it a useful comparator to the other engines and a strong indicator of which third-party sources AI is treating as authoritative.
Relations
Evidence chunks
"Millions of business people and consumers are now asking ChatGPT, Perplexity, Microsoft Copilot, Apple Intelligence, and Amazon Alexa for recommendations every day."
Known & Cited | AI Visibility Intelligence — published by Known & Cited evidence
Same as: https://entitymap.org/spec/v1.0
EntityMap is an open standard for publishing a structured, entity-first index of a website's content for consumption by AI agents, large language models and RAG pipelines. Where sitemap.xml tells crawlers what pages exist, entitymap.json tells AI systems what a site knows: which entities it covers, how they relate, and where the evidence is. Initiated by Fred Laurent with the support of Dixon Jones.
Relations
Evidence chunks
"EntityMap is an open standard for publishing a structured, entity-first index of website knowledge for AI systems, retrieval pipelines, and language-model-based applications. Known & Cited publishes its entitymap.json so AI systems can read the K&C knowledge graph directly."
EntityMap | Known & Cited — published by Known & Cited definition
Service
AI-led PR Service
e_021
General concept: PR delivery referral
Known & Cited operates AI-led PR on a referral basis only. K&C identifies the third-party coverage and authority signals an AVS shows a brand is missing, then refers the delivery to vetted PR partners. K&C does not deliver PR in-house. A 15 percent referral fee applies.
Relations
Evidence chunks
"We deliver content, PR and consultancy through trusted freelance partners so the cost stays low and the quality stays high."
In a Nutshell | Known & Cited — published by Known & Cited definition
Service
AI Consultancy
e_022
General concept: AI strategy advisory
Known & Cited's AI Consultancy is a bespoke advisory engagement for businesses that want a structured view of how AI applies to their operations beyond search visibility: which workflows to automate, which tools to adopt, where the strategic opportunities are. Scoped and priced per engagement.
Relations
Evidence chunks
"Pricing for all of our services is bespoke and tailored to your business. AI Consultancy and GEO Advisory engagements are priced per engagement."
Services & Pricing | Known & Cited — published by Known & Cited definition
Service
AI Discovery
e_023
General concept: fixed-fee AI opportunity audit
AI Discovery is Known & Cited's fixed-fee, short-form AI opportunity audit for businesses that want a fast, structured assessment of where AI could move the needle for them. Priced at GBP 1,000. Typically used as a starting point before a larger AI Consultancy or AVS engagement.
Relations
Evidence chunks
"AI Discovery is a fixed-fee, short-form audit at GBP 1,000, typically used as a starting point before a larger AI Consultancy or AVS engagement."
Services & Pricing | Known & Cited — published by Known & Cited definition