Overview Leaderboard Methodology
Industry Report

Enterprise Source Code Management Platforms

Self-hosted or managed platforms offering Git repository hosting, fine-grained access controls, compliance features, and large-team workflow support for enterprises.

Brands tracked: 33
Brands analyzed: 33
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 263
Total responses: 1,330
Top Brand Overall?
GitHub
99/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
GitHub
97

Highest score on the LBA metric in this industry.

Authority Leader?
GitHub
100

Highest score on the Authority metric in this industry.

TOM Leader?
GitHub
100

Highest score on the TOM metric in this industry.

GitHub is the default answer in AI responses for Enterprise Source Code Management Platforms

GitHub and Microsoft together dominate AI responses for Enterprise Source Code Management Platforms. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 33 Enterprise Source Code Management 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
GitHub
github.com
 97
100
100
99
2
Microsoft
microsoft.com
 92
100
100
97
3
GitLab
gitlab.com
 88
100
99
95
4
Atlassian
atlassian.com
 79
70
88
79
5
Bitbucket
bitbucket.org
 76
69
88
77
6
Amazon
amazon.com
 74
7
45
31
7
Gitea
gitea.com
 71
9
16
23
8
Gerrit
gerritcodereview.com
 67
7
13
20
9
Forgejo
forgejo.org
 57
6
9
16
10
Beanstalk
beanstalkapp.com
 60
6
6
15
11
Gogs
gogs.io
 58
6
6
15
12
P
Phabricator
phacility.com
 59
6
6
15
13
RhodeCode
rhodecode.com
 59
6
6
15
14
Assembla
assembla.com
 55
5
5
14
15
Gitee
gitee.com
 58
6
6
14
16
SourceForge
sourceforge.net
 54
5
5
14
17
Codeberg
codeberg.org
 50
5
5
13
18
SCM-Manager
scm-manager.org
 50
5
5
13
19
SourceHut
sr.ht
 52
5
5
13
20
Kallithea
kallithea-scm.org
 48
5
5
12
21
Pagure
pagure.io
 46
5
5
12
22
Coding.net
coding.net
 37
4
4
10
23
Gitblit
gitblit.com
 39
4
4
10
24
OneDev
onedev.io
 40
4
4
10
25
Apache
apache.org
 32
3
3
9
26
B
Bonobo Git Server
bonobogitserver.com
 33
3
3
9
27
Helix TeamHub
perforce.com
 28
3
3
8
28
GitFlic
gitflic.ru
 25
3
3
7
29
Codebase
codebasehq.com
 21
2
2
6
30
GitCode
gitcode.com
 16
2
2
5
31
GitVerse
gitverse.ru
 14
1
1
4
32
Radicle
radicle.xyz
 14
1
1
4
33
Launchpad
launchpad.net
 10
1
1
3

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 263 shared Enterprise Source Code Management 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 →