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Public Intelligence Library
Every public work of The Observatory — readings, context, method, reference and actors — ready to find, cite and reuse.
Every public work of The Observatory, in one searchable place: the governed readings served today, the contextual readings of each market, the method and reference that govern them, and the organisations they observe. Each entry states what it is, what it covers and when it is from, and cites it in the form its nature allows. The source page remains authoritative — this library describes it, never replaces it.
Public tables and prepared capsules may be reused free of charge, including commercially, under our Terms. Free reuse, including commercial republication, under The Observatory’s Terms. Retain attribution, source link, scope and date. See the citation and reuse standards. Observed by The Observatory — not approved or endorsed by it.
Find, cite and reuse Observatory intelligence.
Search across published evidence, context and reference works. Narrow the library by market or work type, open the original source, cite a work in the format you need, or build a selection to export for research.
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- Ranking
A ranking is an Observatory card reporting who the answer layer names first on a market and surface, ordered by observed position over a stated window.
Last reviewed 3 June 2026
- Ranking vs Behavior
A ranking is one public expression of AI behavior. Every Observatory ranking is a scoped reading, not universal truth.
Last reviewed 3 June 2026
- Reading Basis
The reading basis is the stated scope of a figure: the surface it describes, the observation window, and the run count behind it. Every Observatory metric carries one, so a number can be read rather than assumed.
Last reviewed 3 June 2026
- Semantic Authority
The condition of being treated by AI systems as a central reference for a market.
Last reviewed 3 June 2026
- Sentinel Query
A sentinel query is a fixed, representative question The Observatory tracks over time to see which actors an AI surface names for it — the unit by which presence on the answer layer is observed.
Last reviewed 3 June 2026
- Signal Style
A signal style is the role an AI model assigns an actor when it names it — opening sentence, benchmark, platform, curated, example.
Last reviewed 3 June 2026
- Source-of-Record
A Source-of-Record is the traceable canonical publication of a scoped observation or claim. The Observatory aims to become a widely used reference for observed AI and search positioning in premium markets.
Last reviewed 3 June 2026
- Spotlight
Spotlight is the desk built around a single query: what one premium question returns on a given surface, and which actors the models name in response to it.
Last reviewed 3 June 2026
- Surface Competitor
A surface competitor is an actor that competes for visibility, citation, or framing on an answer surface without necessarily being a commercial operator in the underlying market.
Last reviewed 3 June 2026
- Surface Divergence
A measured gap between two surfaces — organic versus AIO, or one model versus another.
Last reviewed 3 June 2026
- Surface Tier
A surface tier groups actors by the strength of their position on a given surface — leader, contested, periphery — so a leaderboard can be read as a structure, not just a column of ranks.
Last reviewed 3 June 2026
- Visibility vs Authority
Appearing on a surface is not the same as being treated as a trusted reference.
Last reviewed 3 June 2026
- What an Authority Gap Means
An authority gap means a brand is visible but not treated as a reference on a surface and window. It is an observed reading, not a judgment of commercial standing.
Last reviewed 3 June 2026
- What It Means When AI Models or Search Surfaces Differ
Read differences between specified surfaces or models within a stated window. Surface Divergence does not, by itself, establish instability or change over time.
Last reviewed 3 June 2026
- When a Platform, Media, or Aggregator Becomes a Surface Competitor
A platform, media site, or aggregator becomes a surface competitor when it holds visibility, citation, or opening on a market's answer surface — without being a commercial operator.
Last reviewed 3 June 2026
- When to Trust AI Answers About a Market
Trust an AI answer about a market to the extent it is scoped, dated, and tied to a governed reading. Treat unscoped assertions about current answer-surface standing as opinion.
Last reviewed 3 June 2026
- Why Do Competitors Appear More Often in AI Answers?
Compare resolved actors on a stated query mix, denominator, surface, mode and window. More appearances describe a difference, not its cause or commercial superiority.
Last reviewed 3 June 2026
- Why Is My Brand Missing from AI Answers?
Check entity identity, surface, query set, window and available evidence before calling a brand absent. Missing output is not observed absence.
Last reviewed 3 June 2026
- 1 Hotels
Luxury Hospitality
Present in 2 markets: Luxury Hospitality US Urban-Resort (NY/Miami), Luxury Hospitality London.
How each kind of work is cited
- Measured readings — rankings and Query Spotlight
- Governed measured reading. Cite it with its market, surface and observed window. The published metric table is available as data.csv and the complete record as citation.txt.
- Narrative readings — DNC Lens and Model Watch
- Governed narrative reading. Model statements are recorded verbatim and fact-checked; no metric table exists, so no CSV is offered. The complete record is available as citation.txt.
- Context, method and reference
- Editorial and contextual work. Cite it as context; for a factual or ranking claim, cite the dated governed readings it links to.
- Actor records
- Living record. Cite it with the date you retrieved it. For a ranking or factual claim, cite the dated evidence the record links to — never the record in its place.
Dates mean what they say: Observed is the window the surface was read; Published is when a reading went public; Text revision is when the exact accepted text first existed; Last reviewed is the review date a page declares. No digital object identifier is assigned; cite the canonical address.
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