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Epovest

With Epovest, businesses make AIs recommend them. From the questions their customers ask to the sources that shape the answers, everything is measured, dated and verifiable. And everything leads to action: where to appear, what to fix, and proof of what changed.

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https://epovest.com/llms.txt
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2021-03-13
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# Epovest

> With Epovest, businesses make AIs recommend them. From the questions their customers ask to the sources that shape the answers, everything is measured, dated and verifiable. And everything leads to action: where to appear, what to fix, and proof of what changed.

Epovest is an AI visibility platform built as a method. A business decides what the AIs should say about it (its canon: a reference text, versioned), measures what the engines actually answer on its own prompts (trackers that archive every raw answer, extract the cited sources and build longitudinal citation series per keyword and engine), aligns every page about it where it has the final say against the canon, records as dated proof the pages where someone else has the final say, and dates every action in a logbook read against the citation curves. The tools of the method: Canon, Tracking, Surfaces, Corroborations, Atlas and Logbook, plus Competitors, which turns a basket of competitors into the places that corroborate them, and Quests, which holds what is left to do across them.

## AI Authority (AA)

AI Authority, or AA, is the metric Epovest publishes on every source of its Atlas: how much an engine leans on that source, on a scale of 0 to 100 where 100 is the source that engine cites most. Definition page: https://epovest.com/en/ai-authority.

How it is computed, in full:

- The number is a COUNT, not a composite index: the detections of a source over a rolling 30-day window, scaled against the count of that engine's leading source on the same date. AA = round(100 x detections / leader). No constant to calibrate, no weighting to arbitrate
- The scale is computed over the ENTIRE corpus of sources Epovest knows, across every survey run on the platform, and not over the sources of the reader's own account. A client reads the AA of the sources their own surveys revealed, but the 100 that sets the scale is the leader of the whole corpus. Restricting the set of sources shown never rescales the metric, which is what makes two accounts' AA comparable and a client's own AA stable as their coverage grows
- One AA PER ENGINE: each engine has its own leading source, so its own scale, and an AA always places a source against the leader of ITS engine. Per-engine rankings are close to disjoint, and one AA per engine keeps that relief, which is what makes each number actionable
- The leader is read from the same daily snapshot as the detections it scales, so a past point stays attributable: a drop in a source's AA comes from that source losing citations, never from a leader that moved underneath
- A cited source can never round down to 0; a source not cited by an engine in the window has no AA on it at all, rather than a zero. Absent is not zero
- Snapshots are recorded daily, so an AA is a series and not just a number: a source rising on an engine is readable over time

What it is for: it ranks the work. A source list ordered by AA says which sources to appear in first, engine by engi
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