Overview Leaderboard Methodology
Industry Report

Managed DevOps and CI/CD Platforms

Integrated services that combine source hosting with build pipelines, automated testing, deployment workflows, and monitoring to streamline software delivery.

Brands tracked: 37
Brands analyzed: 37
Last updated: 2026-04-22
Model: OpenAI GPT-5
Prompts: 287
Total responses: 1,470
Top Brand Overall?
GitHub
99/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
GitHub
100

Highest score on the LBA metric.

Authority Leader?
GitLab
99

Highest score on the Authority metric.

TOM Leader?
GitHub
100

Highest score on the TOM metric.

GitHub is the default answer in AI responses for Managed DevOps and CI/CD Platforms

GitHub and GitLab together dominate AI responses for Managed DevOps and CI/CD 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 37 Managed DevOps and CI/CD Platforms brands ranked

Ranked by overall AI Visibility Score (geometric mean of LBA, Authority, and TOM). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
GitHub
github.com
 100
97
100
99
2
GitLab
gitlab.com
 95
99
97
97
3
Azure DevOps
azure.com
 88
34
77
61
4
CircleCI
circleci.com
 91
26
78
57
5
Jenkins
jenkins.io
 74
16
33
34
6
Bitbucket
bitbucket.org
 77
3
56
23
7
Harness
harness.io
 88
5
19
21
8
Terraform
hashicorp.com
 80
7
8
16
9
Argo CD
argoproj.io
 86
5
7
15
10
Buildkite
buildkite.com
 76
4
13
15
11
Microsoft
microsoft.com
 100
3
1
6
12
Octopus Deploy
octopus.com
 80
0
5
5
13
Google
google.com
 88
0
20
3
14
Atlassian
atlassian.com
 79
0
8
2
15
Render
render.com
 76
0
15
2
16
Vercel
vercel.com
 85
0
11
2
17
Buddy
buddy.works
 51
0
1
1
18
CloudBees
cloudbees.com
 72
0
1
1
19
Semaphore
semaphoreci.com
 75
0
1
1
20
TeamCity
teamcity.com
 87
0
1
1
21
Travis CI
travisci.com
 69
0
1
1
22
Amazon
amazon.com
 83
0
0
0
23
Appcircle
appcircle.io
 43
0
0
0
24
Assembla
assembla.com
 42
0
0
0
25
Beanstalk
beanstalkapp.com
 57
0
0
0
26
Codeberg
codeberg.org
 42
0
0
0
27
Codefresh
codefresh.io
 76
0
0
0
28
Codemagic
codemagic.io
 73
0
0
0
29
Concourse
concourse-ci.org
 55
0
0
0
30
Drone
drone.io
 54
0
0
0
31
Gitea
gitea.com
 64
0
0
0
32
GoCD
gocd.org
 74
0
0
0
33
Nevercode
nevercode.io
 50
0
0
0
34
RhodeCode
rhodecode.com
 42
0
0
0
35
SourceHut
sr.ht
 66
0
0
0
36
Upsource
jetbrains.com
 12
0
0
0
37
Woodpecker
woodpecker.co
 37
0
0
0

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 287 shared Managed DevOps and CI/CD 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
Geometric mean of LBA, Authority and TOM: (LBA × Authority × TOM)^(1/3). Geometric mean is used so that any single weak metric pulls the overall score down, rather than being masked by strength elsewhere.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 287 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 →