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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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- AI Visibility: Do You Need a Platform, Monitoring, an Audit or a Managed Service?
Choose the job you need: access to measurement, recurring observation, bounded diagnosis or ongoing execution. Compare deliverables, cadence and responsibility.
Last reviewed 25 September 2026
- How Can You Verify a GEO, AEO or AI Visibility Claim?
Assess a GEO, AEO or AI visibility claim by its evidence, comparison basis and attribution. Separate an observed increase from proof that an intervention caused it.
Last reviewed 25 September 2026
- AI Visibility vs AI Authority
Appearing on an AI surface is not the same as being treated as a reference. How to tell visibility from authority, and what an authority gap indicates.
Last reviewed 3 June 2026
- Can an AI Know Why It Ranks a Brand?
A language model can describe possible ranking factors, but cannot reliably state current cross-surface behavior for a live market without governed observation.
Last reviewed 3 June 2026
- How AI Systems Frame Market Leaders
An AI answer frames some actors as leaders through observed signals — opening, benchmark framing, citation — on a surface and window. Surface framing is not commercial leadership.
Last reviewed 3 June 2026
- How to Read an AI Market Ranking
Read a ranking with its Reading Basis, signal styles, and divergences. A ranking is a scoped reading of an answer surface, not a universal or commercial truth.
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 Does a Brand Rank in AI Answers?
Read a brand’s observed position, citation and framing separately. A ranking describes the result; explaining its cause requires additional evidence.
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
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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