Subcategory · AI Citation Index

Wiki & Docs

Wiki & docs is a two-brand race in AI discovery, with Notion and Built each surfacing in more than 85% of buyer queries across all four engines. Microsoft 365 follows at 60% share, visible on every engine but clearly a tier behind. The consensus pick is Microsoft 365 — it wins more head-to-head comparisons than it loses, while Notion appears in more discovery prompts but barely participates in evaluation-stage queries. Nuclino is the absent giant: wins most head-to-heads it enters but only surfaces on two of the engines we track, leaving fragile visibility. This is a contested category — AI engines agree on a shortlist but split on who to pick when buyers ask direct matchup questions.

50 discovery queries · 385 head-to-heads · refreshed May 1, 2026

Discovery stage

The shortlist

Across 50 buyer-style "Wiki & Docs" queries

Notion and Built trade AI discovery share within two percentage points of each other, both visible across ChatGPT, Claude, Gemini, and Perplexity. Microsoft 365 shows up in 60% of buyer queries and surfaces on every engine, while coda.io and Google Workspace each land in just over half of queries with full-engine coverage. Tettra and readme.com surface on only three of the four engines, leaving single-engine blind spots.

1%20%39%57%76%Coverage — share of discovery prompts where the brand surfaces71%76%80%85%89%Engine diversity

Hover or click a logo to see brand details

X = coverage across discovery prompts · Y = engine diversity · Bubble size = total mentions
Tracked acrossChatGPT,Gemini,Claude

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Signal by intent

By topic

Top 5 most-cited brands per intent cluster. Brands with zero citations in a topic are not shown.

1Built
15/15
2Notion
14/15
3Confluence
10/15
4Practice
7/15
5Readme
6/15
1Built
7/7
2Microsoft
7/7
3Practice
4/7
4Google Workspace
4/7
5Comprehensive
4/7
1Notion
6/6
2Google Workspace
6/6
3Microsoft
6/6
4Coda
5/6
5Built
5/6
1Internal
6/6
2Confluence
6/6
3Notion
6/6
4Plan
6/6
5Comprehensive
5/6
1Notion
5/5
2Tettra
5/5
3
Gitbook
5/5
4Coda
5/5
5Microsoft
5/5
1Built
5/5
2Readme
4/5
3Notion
3/5
4GitLab
3/5
5
Gitbook
3/5
1Confluence
5/5
2Notion
5/5
3Built
4/5
4Comprehensive
4/5
5Internal
4/5
1Notion
4/4
2Built
4/4
3Tettra
4/4
4Document360
4/4
5Coda
2/4
≥50% cited
25–49%
<25%
Topics are discovery-stage prompt clusters · wiki-docs

Evaluation stage

Head-to-head

How often AI cites each brand across uniform category evaluation prompts · median 50/100

Microsoft 365 wins more head-to-head comparisons than it loses — averaging above the category median across ten matchups. Nuclino and Seismic Knowledge both score above the median as well, each across a dozen or more comparison queries. Document360, Archbee, and Glean lose more head-to-heads than they win, landing below the median despite meaningful comparison volume.

0255075100Evaluation citation rate — % of category evaluation prompts citing this brand04998147196Evaluation prompts cited inmedian citation ratemedian exposure

Hover or click a logo to see brand details

X = evaluation citation rate · Y = evaluation prompts cited in · Bubble size = citation exposure
Median citation rate 50/100

Each brand's score is the share of category evaluation prompts where AI cited them across all four engines — the same prompt pool for every brand. Brands above the median citation rate have stronger presence in evaluation-stage queries.

Citation sources

Where AI pulls citations from

726 citations captured across Wiki & Docs prompt runs.

Vendor pages

220

Product, help, and marketing pages from tracked vendors

Independent sources

175

Reviews, encyclopedias, forums, press — not vendor-owned

Buyer questions

What AI cites for top Wiki & Docs questions

Every query in the prompt set is top-of-funnel exploration — buyers ask AI for the best wiki or documentation tool by role and use case. Sample phrasings include 'As a compliance officer, what is the most effective tool for policy documentation?' and 'As a software engineer, what is the best tool for documenting API specifications?' No head-to-head comparison queries or pricing questions appear in the mix.

Discovery

Buyers exploring the category

Evaluation

Buyers comparing options

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