Overview Leaderboard Methodology
Industry Report

Documentation Platforms

Tools designed for creating and maintaining technical documentation, product manuals, API docs, and developer guides with versioning and collaboration features.

Brands tracked: 39
Brands analyzed: 39
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 294
Total responses: 1,530
Top Brand Overall?
Atlassian
79/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Notion
91

Highest score on the LBA metric in this industry.

Authority Leader?
GitBook
75

Highest score on the Authority metric in this industry.

TOM Leader?
Atlassian
98

Highest score on the TOM metric in this industry.

Atlassian leads the Documentation Platforms category in AI responses

Atlassian is the most consistently-surfaced brand when users ask AI assistants about Documentation Platforms, but not to the point of monopolising the conversation. Notion and a handful of others appear regularly, giving users a reasonable set of alternatives to compare. The top of this leaderboard is where most of the AI-driven traffic will go.

Brand Leaderboard All 39 Documentation 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
 85
60
98
79
2
Notion
notion.so
 91
54
98
79
3
GitBook
gitbook.com
 79
75
81
78
4
ReadMe
readme.com
 83
36
56
56
5
Docusaurus
docusaurus.io
 87
33
50
53
6
Document360
document360.com
 71
16
55
41
7
MkDocs
mkdocs.org
 87
12
43
37
8
Slab
slab.com
 63
7
53
31
9
Guru
getguru.com
 74
7
40
30
10
Zendesk
zendesk.com
 81
8
25
27
11
Coda
coda.io
 76
8
23
26
12
M
Material for MkDocs
squidfunk.github.io
 85
8
17
25
13
Nuclino
nuclino.com
 67
7
27
25
14
Help Scout
helpscout.com
 68
7
14
21
15
Mintlify
mintlify.com
 68
11
8
20
16
Read the Docs
readthedocs.io
 82
8
8
20
17
Swagger
swagger.io
 84
8
8
20
18
MadCap Flare
madcapsoftware.com
 78
8
8
19
19
Stoplight
stoplight.io
 76
8
8
18
20
Outline
getoutline.com
 63
6
8
17
21
Redocly
redocly.com
 67
7
7
16
22
Archbee
archbee.com
 60
6
6
15
23
KnowledgeOwl
knowledgeowl.com
 59
6
6
15
24
Paligo
paligo.net
 60
6
6
15
25
Slite
slite.com
 58
6
6
15
26
Tettra
tettra.com
 59
6
6
15
27
Apiary
apiary.io
 57
6
6
14
28
Docsy
docsy.dev
 50
5
5
13
29
Helpjuice
helpjuice.com
 49
5
6
13
30
Antora
antora.org
 47
5
5
12
31
ClickHelp
clickhelp.com
 45
5
5
12
32
Fern
buildwithfern.com
 45
5
5
12
33
HelpDocs
helpdocs.io
 48
5
5
12
34
Sphinx
sphinx-doc.org
 48
5
5
12
35
Stonly
stonly.com
 42
4
4
11
36
Docsie
docsie.io
 40
4
4
10
37
Documize
documize.com
 32
3
3
9
38
Notaku
notaku.so
 25
3
3
7
39
DeveloperHub
developerhub.io
 5
1
1
2

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 294 shared Documentation 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 294 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 →