Overview Leaderboard Methodology
Industry Report

Wiki Platforms

Collaborative web-based platforms that allow teams to create, edit, and interlink pages for shared documentation, policies, and project information.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 263
Total responses: 304
Top Brand Overall?
Atlassian
33/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Atlassian
0

Highest score on the LBA metric in this industry.

Authority Leader?
Atlassian
100

Highest score on the Authority metric in this industry.

TOM Leader?
Atlassian
100

Highest score on the TOM metric in this industry.

Wiki Platforms is an emerging or highly fragmented category

No brand in Wiki Platforms scored above 40 on overall AI visibility. That means AI assistants do not currently recommend specific brands for this category with any consistency. Either the category is too new or too regional for the models to have converged on a default set of answers, or the queries users ask don't lend themselves to brand-specific responses.

Brand Leaderboard All 33 Wiki Platforms brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Atlassian
atlassian.com
 0
100
100
33
2
Notion
notion.so
 0
96
100
33
3
Slab
slab.com
 0
35
58
18
4
Nuclino
nuclino.com
 0
28
43
15
5
BookStack
bookstackapp.com
 0
27
41
14
6
Guru
getguru.com
 0
16
59
14
7
MediaWiki
mediawiki.org
 0
17
47
13
8
GitBook
gitbook.com
 0
12
32
10
9
Microsoft
microsoft.com
 0
14
31
10
10
Slite
slite.com
 0
5
19
6
11
Document360
document360.com
 0
3
18
5
12
DokuWiki
dokuwiki.org
 0
4
12
4
13
Coda
coda.io
 0
1
11
3
14
Outline
getoutline.com
 0
1
9
3
15
Tettra
tettra.com
 0
0
4
1
16
W
Wiki.js
wikijs.org
 0
1
4
1
17
XWiki
xwiki.com
 0
0
3
1
18
Archbee
archbee.com
 0
0
0
0
19
Bloomfire
bloomfire.com
 0
0
0
0
20
BlueSpice
bluespice.com
 0
0
0
0
21
eXo Platform
exoplatform.com
 0
0
0
0
22
Fandom
fandom.com
 0
0
0
0
23
Foswiki
foswiki.org
 0
0
0
0
24
Helpjuice
helpjuice.com
 0
0
0
0
25
Kipwise
kipwise.com
 0
0
0
0
26
Miraheze
miraheze.org
 0
0
0
0
27
MoinMoin
moinmo.in
 0
0
0
0
28
Papyrs
papyrs.com
 0
0
0
0
29
PBworks
pbworks.com
 0
0
0
0
30
PmWiki
pmwiki.org
 0
0
0
0
31
TiddlyWiki
tiddlywiki.com
 0
0
1
0
32
TWiki
twiki.org
 0
0
0
0
33
Wikidot
wikidot.com
 0
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Wiki Platforms prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 263 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →